Miracle-dz/UniFAR-FTUs huggingface dataset:
The Decadal Climate Prediction Project

20 The Decadal Climate Prediction Project (DCPP) is a coordinated multi-model investigation into decadal climate prediction, predictability, and variability. The DCPP makes use of past experience in simulating and predicting decadal variability and forced climate change gained from CMIP5 and elsewhere. It builds on recent improvements in models, in the reanalysis of climate data, in methods of initialization and ensemble generation, and in data treatment and analysis to propose an extended comprehensive decadal prediction investigation as part of CMIP6. The DCPP consists of three 25 Components. Component A comprises the production and analysis of an extensive archive of retrospective forecasts to be used to assess and understand historical decadal prediction skill, as a basis for improvements in all aspects of end-toend decadal prediction, and as a basis for forecasting on annual to decadal timescales. Component B undertakes ongoing production, dissemination and analysis of experimental quasi-real-time multi-model forecasts as a basis for potential operational forecast production. Component C involves the organization and coordination of case studies of particular 30 climate shifts and variations, both natural and naturally forced (e.g. the “hiatus”, volcanoes), including the study of the mechanisms that determine these behaviours. Groups are invited to participate in as many or as few of the Components of the DCPP, each of which are separately prioritized, as are of interest to them. Geosci. Model Dev. Discuss. , doi:10.5194/gmd-2016-78, 2016 Manuscript under review for journal Geosci. Model Dev. Published: 11 April 2016 c © Author(s) 2016. CC-BY 3.0 License.
Design and analysis of industrial experiments

Design and analysis of industrial experiments This paper is based on a lecture on the “Design and Analysis of Industrial Experiments” given by Dr O. L. Davies on the 8th of May 1954 to the Industrial Section of the “Vereniging voor Statistiek”. Production, formulation, and testing are distinguished as three separate fields of chemical activity where experimental designs can be applied, and various numerical examples of such experiments are discussed in detail. They consist of a 23factorial design, a 24half replicate and a 25quarter replicate fractional factorial design, and a three‐way classification. In a final section the recent designs developed by Box for the exploration of response surfaces are briefly considered.
Applying Open Source Softwares Fritzing and Arduino to Course Design of Embedded Systems

The failure of education reform in Taiwan brings about the serious disorder of elementary technicians in Taiwan manufacturing industries in today. In this study, authors strongly emphasize the spirit of "learning by doing" to improve students’ practical operating abilities. In the course design of embedded systems, open source softwares Fritzing and Arduino are chosen to teach our students the abilities of drawing the layout of breadboard wiring, the electronic circuit sketch and the PCB layout of a practical electrical circuit as well as the abilities of Arduino programming for electronic hardware. This sort of training can help students fully understand how to integrate hardware and software together. After running two-years teaching program on it, our students joining this elective course give us very positive feedback, that is, this novel lecturing way in conjunction with Arduino and Fritzing precedes better than our conventional lecturing way.
Towards Scalable Analysis of Images and Videos

With widespread availability of low-cost devices capable of photo shooting and high-volume video recording, we are facing explosion of both image and video data. The sheer volume of such visual data poses both challenges and opportunities in machine learning and computer vision research. In image classification, most of previous research has focused on small to mediumscale data sets, containing objects from dozens of categories. However, we could easily access images spreading thousands of categories. Unfortunately, despite the well-known advantages and recent advancements of multi-class classification techniques in machine learning, complexity concerns have driven most research on such super large-scale data set back to simple methods such as nearest neighbor search, one-vs-one or one-vs-rest approach. However, facing image classification problem with such huge task space, it is no surprise that these classical algorithms, often favored for their simplicity, will be brought to their knees not only because of the training time and storage cost they incur, but also because of the conceptual awkwardness of such algorithms in massive multi-class paradigms. Therefore, it is our goal to directly address the bigness of image data, not only the large number of training images and high-dimensional image features, but also the large task space. Specifically, we present algorithms capable of efficiently and effectively training classifiers that could differentiate tens of thousands of image classes. Similar to images, one of the major difficulties in video analysis is also the huge amount of data, in the sense that videos could be hours long or even endless. However, it is often true that only a small portion of video contains important information. Consequently, algorithms that could automatically detect unusual events within streaming or archival video would significantly improve the efficiency of video analysis and save valuable human attention for only the most salient contents. Moreover, given lengthy recorded videos, such as those captured by digital cameras on mobile phones, or surveillance cameras, most users do not have the time or energy to edit the video such that only the most salient and interesting part of the original video is kept. To this end, we also develop algorithm for automatic video summarization. Finally, we further extend our research on video summarization into a supervised formulation, where users are asked to generate summaries for a subset of a class of videos of similar nature. Given such manually generated summaries, our algorithm learns the preferred storyline within the given class of videos, and automatically generates summaries for the rest of videos in the class, capturing the similar storyline as in those manually summarized videos.
Measuring Political Knowledge in Web-Based Surveys

Does the opportunity to deliver visual instead of verbal stimuli of political knowledge to respondents in web-based surveys make a difference in terms of data quality? For instance, does the presentation of visual knowledge items reduce cheating, that is, looking up the answer via the Web? And do visual and verbal stimuli capture the same underlying construct? To test whether the use of visuals to measure political knowledge effectively makes a difference, we administer a question form experiment in an online survey of the German Longitudinal Election Study. Respondents are randomly assigned to one of two question formats—visual or verbal—and are asked to solve a set of eight questions on political leaders and their offices. The instruments are validated based on nonparametric item response theory and analyses of response latency. While there is no clear evidence for cheating behavior under either of the conditions, both instruments form strong knowledge scales. Results from a regression analysis indicate that the scales provide measures of closely related but not identical concepts.
Joint maximum likelihood approach in overloaded array processing

We demonstrate that, signal extraction in overloaded environments is achieved by employing a nonlinear maximum-likelihood detector. We define the overloaded interference scenario as one where the number of near equal-power co-channel interferers exceeds the number of antenna array elements. The iterative least squares with enumeration (ILSE) technique is a maximum likelihood joint detector that provides an optimum solution for the overloaded antenna array scenarios in the presence of synchronous cochannel users in an AWGN channel. A linearized version of ILSE, called iterative least-squares with projection (ILSP) is shown to fail in overloaded environments due to an implicit beamformer assumption. ILSE is shown to extract signals with very small angular separations in highly overloaded scenarios at reasonable SNRs. We also show that when the channel is a priori unknown, ILSE can still demodulate more users than elements by incorporating short training sequences for channel estimation as well as employing a completely blind channel estimation technique.
The Third Information Systems International Conference Improving Automated Programming Assessments : User Experience Evaluation Using FaSt-generator

Automatic Programming Assessment (APA) has been known as a method used to automatically mark and grade students’ programming solutions. In order to realise APA as a tangible deliverable, a number of automated tools which are called Automated Programming Assessment Systems (APAS) have been developed and tested for decades. Basically, the need for decreasing the load of work among lecturers, timely feedback to students and accuracy on the grading results are the common reasons that motivate the need for APAS. In order to carry out a dynamic testing in APA, it is necessary to prepare an appropriate and adequate set of test data to judge the correctness quality of students’ programming solutions in terms of the aspects of functional and/or structural testing. Manual preparation of quality test data becomes a hard, time consuming, and feasible task in the practice of both software testing and APA. Thus, the generation of automated test data is highly desirable to alleviate the humans’ burden from performing repetitive tasks. This paper aims to describe the design, implementation and user experience when evaluating a tool developed to support APA as a test data generator that is called FaSt-generator. The tool plays an important role to furnish a test set that includes an adequate set of test data to execute both the functional and structural testing in APA. Results collected from the conducted user experience evaluation using FaSt-generator reveal that all the subjects had relatively positive opinions and greatly favour the criteria of User Perception and End-User Computing Satisfaction (EUCS). © 2015 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of the scientific committee of The Third Information Systems International Conference (ISICO 2015)
Structural Model Explains High Potency Homoeopathic Medicines and Leads to a Generalized Understanding of Medicines

Conventional chemistry has no answer to either the secret of medicinal value of high potency (above 12c) homoeopathic medicines or how they can be identified, that is, differentiated from one another. Original medicinal substance being diluted away these are chemical-free medicines. This gives leverage to skeptics to brand cures by such medicines as placebo effect or mental cure. This article shows major contradictions in their hypothesis. Thereafter, as a logical derivation it arrives at the structural model: A substance is to be recognized as a medicine if it has the capability of curing disease(s) while its medicinal property is to be attributed to molecular structure of vehicle like water or of distinct chemical substance when it exists. It is a shift of focus from chemical formula to physical structure. Several works are cited to show that the no-chemical homoeopathic medicines have water structures. Structure, be it of crude medicinal substance or of molecular structure of water vehicle, plays the predominant role throughout the potency range. So, structures give us the generalized understanding of medicines. The article also shows that there is a link between structure, medicinal value and biological effect.
Handover criteria for city microcellular radio systems

1700 MHz attenuation and bit error rate (BER) measurements were conducted at the center of a major urban area in southern England in order to compile a radio propagation and BER database for handover criteria study in city microcellular radio systems. The focus of the experiments was to provide realistic data for handover simulation in typical city microcell environments, thus minimizing inaccuracies due to the inadequacies in propagation modeling. Results revealed the path loss followed the inverse third to fourth power law in majority of the cases using simple regression fitting. The short-term signal fading statistics varied with Rice factors in excess of ten down to zero, as the distance between the mobile unit and the microcellular base station increased. Computer simulation indicated that both RSSI (received signal strength indicator) and BER could be used as handover criteria. The optimal threshold level for handover request, however, differed from location to location. <<ETX>>
ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH

Public finance theory states that, related to the causality relationship between budgetary revenues and expenditures, it could be investigated if revenues adjust due to changes in expenditures, or otherwise, depending on the sense of the causality. This theory could, also, be applied to the components of current account in order to analyze the synchronization between inflows and outflows of international trade. In the case where the two time series are cointegrated, classical Granger causality test could reveal distorted results. Consequently, it can be used an adjusted Granger test based on cointegration equation between the two variables. The aim of this paper is to investigate the causal relationship between exports and imports of Romanian current account, according to the methodology of Engle and Granger. The results could reveal some insights related to the formation of current account deficit, based on the adjustments of inflows caused by changes in outflows, or, otherwise. Abstract. This paper is organised as follows: first, it is given a brief introduction of a simple model for European options price and next, the parallel algorithms applied to this model. Considering the idea given by odd%even cyclic reduc tion, we start from an explicit scheme obtained by means of finite differences, and give an alternative of evaluating the approximate values using an odd%even cyclic reduction which generates a logarit hmic time of execution. Also, it is solved numerically using a parallelised domain decomposition method. The spatial domain is splitted among several processors, with data communicated among the processors using MPI. Interface conditions between domains are calculated using finite differences. For smaller sized problems the communication time is much longer than the computation time.
Simple learning control made practical by zero-phase filtering: applications to robotics

Iterative learning control (ILC) applies to control systems that perform the same finite-time tracking command repeatedly. It iteratively adjusts the command from one repetition to the next in order to reduce the tracking error. This creates a two-dimensional (2-D) system, with time step and repetition number as independent variables. The simplest form of ILC uses only one gain times one error in the previous repetition, and can be shown to converge to the zero-tracking error independent of the system dynamics. Hence, it appears very effective from a mathematical perspective. However, in practice, there are unacceptable learning transients. A zero-phase low-pass filter is introduced here to eliminate the worst transients. The main purpose of this paper is to supply a presentation of experiments on a commercial robot that demonstrate the effectiveness of this approach, improving the tracking accuracy of the robot performing a high speed maneuver by a factor of 100 in six repetitions. Experiments using a two-gain ILC reaches this error level in only three iterations. It is suggested that these two simple ILC laws are the equivalent for learning control of proportional and PD control in classical control system design. Thus, what was an impractical approach, becomes practical, easy to apply, and effective.
Trust-Discount Tradeoff in Three Contexts: Frugality Moderating Privacy and Security Concerns

This study examines the role individuals' frugality plays in moderating the impact of privacy and security concerns on trust-discount tradeoff. Trust-discount tradeoff measures a user's intention on a continuum to transact with a higher-trust, higher-premium website as opposed to lower-trust, higher-discount website. The hypotheses are examined in three different contexts: e-commerce, health and finance. The findings suggest that frugality does moderate the impact of privacy and security concerns on trust-discount tradeoff in all three contexts, such that security concern is positively associated with preference for higher-trust, higher-premium websites for individuals with a high level of frugality, and that privacy concern is positively associated with preference for higher-trust, higher-premium websites for individuals with a low level of frugality. However, the subsequent analysis reveals that the reasons for the above moderating impact differ depending upon the underlying contextual sensitivity. This study is one of the first to provide contextual examination of the role of frugality, privacy and security concerns in trust-discount tradeoff.
Model-based mine verification with scanning laser Doppler vibrometry data

The combination of a powerful acoustic transmitter with high resolution laser spectroscopy has led to a promising approach for the detection of buried landmines, especially for those with no or only minor metal content. This paper summarizes current R&D work on this new technology including a brief sensor overview and a more detailed description of our data processing methods. The SLDV sensor picks up tiny vibrations of the soil surface in the order of some μm/s in a rectangular grid of measuring points. We use a multi-threshold algorithm for the segmentation of mine cues and reduce false alarms by analyzing the stability of object size, contrast and shape in the frequency domain. In addition to the amplitude of soil vibration the phase is investigated as a secondary information channel to optimize the classification procedure.
Enhancing Students’ Mathematical Reasoning By Algebrator-Assisted Inquiry Method

Mathematical reasoning ability is initiated by identifying and analyzing facts and information in a mathematical concept, analyzing relationships between two or more concepts by applying a set of principles/theoremswhich have been proved, and formulating temporary conclusions until a final conclusion is obtained. Students’ mathematical reasoning, however, is one of the problems occurs in teaching and learning process, where many teachers and lecturers encounter with. Their ability in understanding and analyzing mathematical conceptsusing deductive methodsand drawing a conclusion for constructing valid argumentsare still poor. This research was quasi experiment in nature, with pretest-posttest control group design. Inquiry method was implemented with the use of Algebrator for enhancing students’ mathematical reasoning. The subject in this research was 80 students from 8 classes in one of junior high schools, in Bandung, West Java, selected by applying purposive sampling technique. The subject of the research was grouped into 2 different groups. The first group was treated under Algebrator-assisted Inquiry method while the second group was given conventional method. The instruments used in this research were mathematical reasoning test and attitude scale. Indicators covered in the test weremathematical connections, relational understanding, deductivereasoning, and critical-mathematical thinking. The measured aspects of attitude consist of interest, motivation, and activities related to mathematics lesson, inquiry method, and mathematical problems in reasoning-based test. From the data analysis related to mathematical reasoning, it is obvious that the students’ weaknesses were in mathematical connections, relational understanding, deductive reasoning, and critical-mathematical thinking. The main factors which made the problems occuredis that there was no sufficient mathematical reasoning integrated into the lecture conducted. Further, there was only a few lectures which integrated logic into the concepts in other subjects intensively. The lack of challenging, divergent, and open ended problems, as well as inadequate exercises given to students,were also the other factorswhich contributed to the students’ difficulty.
FASCINATING PERSPECTIVES OF STATE AND PARAMETER ESTIMATION TECHNIQUES

This paper discusses how the state and parameter estimation techniques as applied to aerospace problems can be viewed in many fascinating and refreshing ways. This paper is addressed mainly to aerospace students and to experts in other fields to provide a broad appreciation of many useful features of the subject. The conceptual framework is discussed so that the details can be handled with ease. It is assumed that they have some exposure to probability, statistics, random process, matrix, systems theory as well as optimization techniques. About twenty ways of looking at estimation techniques (ET) is provided along with typical references for further detailed studies.
Early visual and morphologic changes after half-fluence photodynamic therapy in chronic central serous chorioretinopathy.

PURPOSE To evaluate the early functional and morphologic changes in patients with chronic central serous chorioretinopathy (CSC) after half-fluence photodynamic therapy (PDT) and to compare with fellow eyes. METHODS This prospective study included 32 symptomatic and 28 fellow eyes of 32 patients with chronic CSC. Indocyanine green angiography-guided half-fluence PDT (25 J/cm(2)) was performed. Best-corrected visual acuity (BCVA), central foveal thickness (CFT), and subfoveal choroidal thickness (SFCT) were evaluated at baseline and at days 1, 3, 7, 30, and 60 after PDT. RESULTS The mean age was 48.1±7.9 years. Baseline BCVA [logarithm of the minimum angle of resolution (logMAR)] improved from 0.56±0.23 to 0.54±0.24, 0.45±0.25, 0.38±0.23, 0.36±0.23, and 0.35±0.21 at days 1, 3, 7, 30, and 60. (P=0.91, P=0.004, P=0.002, P=0.001, and P<0.001, respectively). Baseline CFT decreased from 315±131 to 312±136, 305±136, 235±106, 174±44, and 165±36 μm at days 1, 3, 7, 30, and 60 (P=0.41, P=0.33, P=0.004, P<0.001, and P<0.001, respectively). Baseline SFCT in the symptomatic eyes was significantly greater compared with the fellow eyes (P=0.002) and changed from 517±98 to 546±109, 528±110, 495±119, 462±124, and 457±123 μm at days 1, 3, 7, 30, and 60 (P=0.02, P=0.42, P=0.07, P=0.004, P=0.003, respectively). CONCLUSION The SFCT in the symptomatic eyes was greater in the fellow eyes at baseline. Functional and morphological chorioretinal changes started in very early period of treatment. Half-fluence PDT for chronic CSC resulted in thinner CFT and SFCT, and also showed a significant improvement in visual acuity.