Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards Fast Deploying the Coordinated Storage, Computing, and Networking Cloud Service: the Ezilla Toolkit

With the growth of Cloud based technologies, so have the cloud-based services has grown over the past few years. To meet the demands from the Cloud users, service providers have to provide such a service environment that can be deployed and provisioned quickly and easily. To help tackling such an issue, the Ezilla, which is considered as a private Cloud toolkit, has been developed by the PerComp Team in the National Center for High-performance Computing. The Ezilla integrates the de facto Cloud middleware, Web-based interface, and coordinated cloud infrastructure services such as Storage, computing and networking services to form an integrated virtual computer. With the Ezilla toolkit, a virtual computer, which is configured specifically to meet the needs of an individual Cloud user, is just one click away. The merit of the Ezilla is simplifying the complexity of the Cloud system for easier deployment for the users. Scientist as well as genera users can deploy the Cloud for their works without dealing with the painful process of building the Cloud system. The proposed Ezilla toolkit leverages genetic virtualization techniques, DRBL–SSI (Diskless Remote Boot in Linux – Single System Image), the cluster scheduling policy, and distributed filesystem, to orchestrate distributed computing resources dynamically .
After The Flood: A Follow Up on the Trophic State of Lake Blackshear, Georgia

Chlorophyll a based trophic state conditions during the summer in Lake Blackshear in 2001 were compared to pre-flood conditions of 1992. Median values were similar in the transition zone but lower in the middle and lower portions of the reservoir. It is not possible to determine whether lower chlorophyll a values in 2001 represent a change in lake productivity following the flooding event or simply reflect low flows during severe drought. Phytoplankton growth in the lake did not achieve the potential level predicted by nutrient concentrations or lake transparency.
The link between Allergic disease and depression in young adults: A structural equation modelling analysis

Background: The co-occurrence of multiple interacting medical and psychological disorders is extremely common. A significant association between allergic disease (ADz - e.g., asthma, allergic rhinitis, allergic dermatitis) and depression has been reported. Objective: Path analysis models using cross-sectional data were constructed to evaluate the inter-relationships among underlying co-occurring factors known to impact depression in young adults. Method: 885 college students (21.80 ± 3.22 years old) completed an online survey assessing current ADz, sleep quality, pain/discomfort, Body Mass Index, stress, substance use, Internet addiction, physical activity, social support and depression.
Photonic crystal tunable slow light device integrated with multi-heaters

We fabricated photonic crystal slow light waveguides integrated with multi-heaters, using CMOS-compatible process. By optimizing heating powers and adjusting the index distribution, a clear delay peak was observed, which suggests that the fabrication errors were compensated for completely. When a linear index chirp was added to this condition, the delay was tuned by 54 ps. When a quadratic chirp was added, arbitrary group delay dispersion was generated at wavelengths around 1550 nm within a 3 nm bandwidth. The continuously tunable range was from −32 to 54 ps/nm/mm. Using this as a dispersion compensator, we compressed pre-chirped pico-second pulses.
Distributed Fault Estimation of Nonlinear Networked Systems: Application to Robotic Manipulator

This paper is concerned with the distributed fault estimation for a class of nonlinear networked systems, where the T-S fuzzy model is utilized to approximate the nonlinear plant and the whole fault estimation task is operated by a wireless sensor network. Due to the limited power in sensors, signal is quantized before transmission. Based on the Lyapunov stability theory and the robust control approach, a sufficient condition is obtained such that the estimation error system is asymptotic stable with a prescribed performance level. Finally, a case study on the actuator fault estimation of robotic manipulator is given to show the effectiveness of the proposed design.
Self-efficacy and ICT integration into initial teacher education in Saudi Arabia: Matching policy with practice

Success factors for integration of ICTs in higher education teaching and learning reveal a complex mixture of old and new paradigms. A review of the relevant literature and findings from research conducted in Saudi Arabia highlights the importance of actual and perceived self-efficacy within the new paradigms. The research reported reflects these perceptual dilemmas. Participants were 325 Saudi pre-service teachers from the Faculty of Education at King Abdulaziz University. Findings reveal that participants have generally high skill levels with computing tasks and their perceptions of self-efficacy as university teachers increase with computer experience and computer qualifications. These findings imply that increasing Saudi pre-service teacher access, training, and exposure to computers and ICTs will contribute effectively to boosting their self-efficacy, motivation, and computing habits. However, where traditional views of teacher directed learning remain unchallenged change is conservative and context specific. To overcome the perceptual gap, data underline the importance of sympathetic and strategic leadership, effective curriculum design and innovative pedagogies to sustain outcomes.
DETERMINANTS OF TEA EXPORT SUPPLY IN KENYA

The aim o f the study was to identify the factors that determine tea export supply in Kenya. Specifically, the study attempts to describe the tea export performance of Kenya for the period 1970 2007, investigate the determinants of tea exports and make policy recommendations for improving tea export performance in Kenya. It explains how real exchange rate, input prices, price of t^a substitute, weather pattern, real wage rate in tea sub industry and structural adjustment programme affect the tea export supply in Kenya. To do this, a simple log linear model was estimated using ordinary least squares (OLS). Eviews Statistical Program was used to analyze the time series data for the period 1970-2007. The finding of the study indicate that real producer price of tea and the real exchange rate are highly significant in explaining tea export performance at any given time period. The real milk price and input price variables were also found to be significant in explaining amount of tea exported from the country. The weather variable was also found to influence amount of tea exported at a given time period. However, the SAP and input price variables were found to be insignificant in explaining tea export supply. Based on the findings of the study, policy recommendations have been made which can remedy the situation. This includes price stabilization or price guarantee scheme, flexibility in the exchange rate movements in line with the economic fundamental, value addition and innovative marketing designed to improve tea producer prices. To compete globally, the government should help to reduce costs including transaction costs like electricity and fuel that make tea production and marketing expensive and hence uncompetitive in the region. The government through ministry of trade should also take the advantage of economic integration, particularly the East Africa Cooperation, COMESA, together with African Growth Opportunity Act (AGOA); in these partnerships there is potential for export opportunities that I can be explored to Kenya’s advantage . s
Distribution of Cerebral Blood Flow during Biofeedback Training

1Center of Career Development and Support, University of Fukui, 3-9-1 Bunkyo, Fukui 910-8507, Japan 2Center for Advanced Research on Political Institutions, Meiji University, 1-1 Kanda-Surugadai, Chiyoda-ku, Tokyo 101-8301, Japan 3Department of Human and Artificial Intelligent Systems, Graduate School of Engineering, University of Fukui, 3-9-1 Bunkyo, Fukui 910-8507, Japan ∗E-mail address: takada@u-fukui.ac. jp
Detection of Vandalism in Wikipedia using Metadata Features – Implementation in Simple English and Albanian sections

In this paper, we evaluate a list of classifiers in order to use them in the detection of vandalism by focusing on metadata features. Our work is focused on two low resource data sets (Simple English and Albanian) from Wikipedia. The aim of this research is to prove that this form of vandalism detection applied in one data set (language) can be extended into another data set (language). Article views data sets in Wikipedia have been used rarely for the purpose of detecting vandalism. We will show the benefits of using article views data set with features from the article revisions data set with the aim of improving the detection of vandalism. The key advantage of using metadata features is that these metadata features are language independent and simple to extract because they require minimal processing. This paper shows that application of vandalism models across low resource languages is possible, and vandalism can be detected through view patterns of articles.
Community of Inquiry for Graduate Certificate in Higher Education

The Graduate Certificate in Higher Education (GCHE) programme is conducted in a blended mode (workshop learning activities and online forum discussion) using the Community of Inquiry (CoI) framework where the three interdependent elements, Teaching Presence, Social Presence and Cognitive Presence, provide the frame to design, facilitate and teach the units in the programme. In line with the framework requirements, the workshop learning activities are designed to engage students in active learning and to build a sense of community among GCHE students who are full-time lecturers. This programme is compulsory for all lecturers except those who have acquired similar qualification or have many years of teaching experience. The Practical Inquiry (PI) model is used to analyze the cognitive dimension of the knowledge-building processes occurring in online discussions. This analysis focuses on the top and bottom 10th percentile of the students’ discussions. Incidentally, exploration is the most frequently coded category of messages posted by the students (overall, 38%). The results from the PI model also indicate when there were limited interventions from the facilitator in the forum discussions it did not lead to students adrift. But the cognitive presence indicator shows that it fails to take the discussion to the resolution stage. Hence, even for students who are lecturers with postgraduate degrees “guide on the side” for online learning may not work. The facilitator needs to prompt the students and post messages to inspire them to move on to the resolution stage.
Dos algoritmos para estimar el periodo de una señal discreta

In this paper, we present two algorithms for approximating a period given a discrete data set. These algorithms superimpose two consecutive sections of the data for several candidate periods. The first algorithm counts the number of shuffling points per candidate period, whereas the second algorithm computes a distance between points when sorted by time. The best candidate period maximizes the number of shuffling points in the first algorithm, whereas the second algorithm minimizes the distance between points. The experimental validation with noiseless data demonstrates that the relative error for the estimations is less than half of the sampling period and shows that this error does not depend on the harmonic content, as normally occurs with algorithms that estimate a period. The application of the algorithms demonstrates that they properly track the frequency of a power grid and accurately estimate the period of a Van der Pol oscillator, which serves to confirm their applicability to real-time problems.
Data pre-processing in the neural network identification of the modified walls natural frequencies

Two techniques of neural network input data pre-pro cessing are discussed in the paper: (i) data compre ssion with the application of the principal component analysis method, (ii) vario us forms of data scaling. Neural networks are appli ed for the prediction of the first natural frequencies of horizontal vibrations of mod ified medium height load-bearing walls. The small a nd the large changes of the wall stiffness and mass resulted from the new door openings size and position are taken into account. The influence of the type of data pre-processing technique on the accuracy of th e frequencies neural prediction is discussed.
Correlating plagiocephaly skull deformations with facial asymmetry using projected pattern 3D imaging

In this paper, we present a statistical study into skull deformations caused by positional plagiocephaly. We also consider the hardware used for the assessment of both severity and treatment. State-of-the-art external imaging hardware is employed to assess the three-dimensional geometry of the cranium and face of 69 affected babies. The hardware used for most of this study is based on projected-pattern range finding, although we also experiment with photometric stereo techniques. We then explain how the severity of the condition can be parameterised, based on the 3D data, using the Extended Gaussian Image (EGI) construction. The EGI is a method of compactly representing the overall geometry of surface (unlike existing metrics used in plagiocephaly), based on its distribution of surface gradients. In this study, we calculate EGIs for both the face and cranium of each patient. We then deduce metrics to parameterise cranial distortions and facial asymmetries. A clear but fluctuating relationship between facial asymmetry and cranial deformation was found. Our results point towards an improvement in both metrics through treatment by banding, although a more detailed study with a control group will be needed in future work.
Comparison of CRM Programs Basing on Improving Customer Profitability: Using the AHP Method

In this paper, we generalize the cause-related marketing (CRM) methods that used by most current enterprises. And then, we probe into the difference of the effects of different types of CRM programs aiming at improving customer profitability by analytic hierarchy process (AHP). Consequently, we find out the sequencing results and provide some reference to the enterprises while performing CRM programs.
Indices of bluefin tuna (Thunnus thynnus thynnus) abundance derived from sale records of French purse seine catches in the Mediterranean sea

Sampling operations are not routinely conducted in France to monitor the landings of bluefin tuna caught by purse seiners in the Mediterranean. The length, weight and age frequencies of bluefin caught by this fleet are predicted based on sale records, length-at-age and weight-length relations, trends in fishing and natural mortality rates, and other ancillary data. The resulting length frequencies are more accurate than those predicted by Liorzou and Bigot (1992) using a simpler algorithm, and are spread more evenly across adjacent size classes. Catch-per-unil-effort (CPUE) was expressed as the numbers of age 2 bluefin caught per successful seine fishing trip in the Gulf of Lions fall fishery. CPUE indices were computed by several methods, and compared to that of the spanish baitboat fishery in the Bay of Biscay. The index trends of the french and spanish fleets exhibit a general increase during 1970-95, but the results do not demonstrate which of these is the best indicator of juvenile abundance. Complementary surveys are required to determine the temporal and spatial distributions of surface schools and fishing effort, and identify the most reliable index of abundance.
Causes of Greenland temperature variability over the past 4000 yr: implications for northern hemispheric temperature changes

Abstract. Precise understanding of Greenland temperature variability is important in two ways. First, Greenland ice sheet melting associated with rising temperature is a major global sea level forcing, potentially affecting large populations in coming centuries. Second, Greenland temperatures are highly affected by North Atlantic Oscillation/Arctic Oscillation (NAO/AO) and Atlantic multidecadal oscillation (AMO). In our earlier study, we found that Greenland temperature deviated negatively (positively) from northern hemispheric (NH) temperature trend during stronger (weaker) solar activity owing to changes in atmospheric/oceanic changes (e.g. NAO/AO) over the past 800 yr (Kobashi et al., 2013). Therefore, a precise Greenland temperature record can provide important constraints on the past atmospheric/oceanic circulation in the region and beyond. Here, we investigated Greenland temperature variability over the past 4000 yr reconstructed from argon and nitrogen isotopes from trapped air in a GISP2 ice core, using a one-dimensional energy balance model with orbital, solar, volcanic, greenhouse gas, and aerosol forcings. The modelled northern Northern Hemisphere (NH) temperature exhibits a cooling trend over the past 4000 yr as observed for the reconstructed Greenland temperature through decreasing annual average insolation. With consideration of the negative influence of solar variability, the modelled and observed Greenland temperatures agree with correlation coefficients of r = 0.34–0.36 (p = 0.1–0.04) in 21 yr running means (RMs) and r = 0.38–0.45 (p = 0.1–0.05) on a centennial timescale (101 yr RMs). Thus, the model can explain 14 to 20% of variance of the observed Greenland temperature in multidecadal to centennial timescales with a 90–96% confidence interval, suggesting that a weak but persistent negative solar influence on Greenland temperature continued over the past 4000 yr. Then, we estimated the distribution of multidecadal NH and northern high-latitude temperatures over the past 4000 yr constrained by the climate model and Greenland temperatures. Estimated northern NH temperature and NH average temperature from the model and the Greenland temperature agree with published multi-proxy temperature records with r = 0.35–0.60 in a 92–99% confidence interval over the past 2000 yr. We found that greenhouse gases played two important roles over the past 4000 yr for the rapid warming during the 20th century and slightly cooler temperature during the early period of the past 4000 yr. Lastly, our analysis indicated that the current average temperature (1990–2010) or higher temperatures occurred at a frequency of 1.3 times per 1000 yr for northern high latitudes and 0.36 times per 4000 yr for NH temperatures, respectively, indicating that the current multidecadal NH temperature (1990–2010) is more likely unprecedented than not (p = 0.36) for the past 4000 yr.
Integrity Verification of Applications on Radium Architecture

Trusted Computing capability has become ubiquitous these days, and it is being widely deployed into consumer devices as well as enterprise platforms. As the number of threats is increasing at an exponential rate, it is becoming a daunting task to secure the systems against them. In this context, the software integrity measurement at runtime with the support of trusted platforms can be a better security strategy. Trusted Computing devices like TPM secure the evidence of a breach or an attack. These devices remain tamper proof if the hardware platform is physically secured. This type of trusted security is crucial for forensic analysis in the aftermath of a breach. The advantages of trusted platforms can be further leveraged if they can be used wisely. RADIUM (Race-free on-demand Integrity Measurement Architecture) is one such architecture, which is built on the strength of TPM. RADIUM provides an asynchronous root of trust to overcome the TOC condition of DRTM. Even though the underlying architecture is trusted, attacks can still compromise applications during runtime by exploiting their vulnerabilities. I propose an application-level integrity measurement solution that fits into RADIUM, to expand the trusted computing capability to the application layer. This is based on the concept of program invariants that can be used to learn the correct behavior of an application. I used Daikon, a tool to obtain dynamic likely invariants, and developed a method of observing these properties at runtime to verify the integrity. The integrity measurement component was implemented as a Python module on top of Volatility, a virtual machine introspection tool. My approach is a first step towards integrity attestation, using hypervisor-based introspection on RADIUM and a proof of concept of application-level measurement capability.
Fuzzy -based TTL (Time To Live) Determination for Improving The Energy Efficiency of The WODEM for Wormhole Attack In WSN

Sungkyunkwan University, Suwon, 440-746, Republic of Korea Summary One of the typical attacks in Wireless Sensor Networks (WSN), is setting up the wrong route with using a wormhole. The wormhole attack, which is accomplished by selectively relaying packets between adversaries, can ruin the routing and communication of the network without compromising any legitimate nodes. To overcome this threat, there are a few countermeasures against the wormhole attack in WSN. The WODEM (WOrmhole attack DEfense Mechanism) can detect and counter any wormhole attacks. In this scheme, the WODEM can detect and counter wormhole attacks by comparing hop count with the pre-determined initial TTL (Time To Live). The selection of the initial TTL is important since it can provide a tradeoff between the detection ability ratio and the energy consumption. In this paper, we propose a fuzzy rule-based system that can conserve energy for determining the TTL, while it provides a sufficient detection ratio for a wormhole attack.
OrthoPanels: An R Package for Estimating a Dynamic Panel Model with Fixed Effects Using the Orthogonal Reparameterization Approach

This article describes the R package OrthoPanels, which includes the function opm(). This function implements the orthogonal reparameterization approach recommended by Lancaster (2002) to estimate dynamic panel models with fixed effects (and optionally: wave specific intercepts). This article provides a statistical description of the orthogonal reparameterization approach, a demonstration of the package using real-world data, and simulations comparing the estimator to the known-to-be-biased OLS estimator and the commonly used GMM estimator.