Miracle-dz/UniFAR-FTUs huggingface dataset:
Energy-Oriented Partial Desktop Virtual Machine Migration

Modern offices are crowded with personal computers. While studies have shown these to be idle most of the time, they remain powered, consuming up to 60% of their peak power. Hardware-based solutions engendered by PC vendors (e.g., low-power states, Wake-on-LAN) have proved unsuccessful because, in spite of user inactivity, these machines often need to remain network active in support of background applications that maintain network presence. Recent proposals have advocated the use of consolidation of idle desktop Virtual Machines (VMs). However, desktop VMs are often large, requiring gigabytes of memory. Consolidating such VMs creates large network transfers lasting in the order of minutes and utilizes server memory inefficiently. When multiple VMs migrate concurrently, networks become congested, and the resulting migration latencies are prohibitive. We present partial VM migration, an approach that transparently migrates only the working set of an idle VM. It creates a partial replica of the desktop VM on the consolidation server by copying only VM metadata, and it transfers pages to the server on-demand, as the VM accesses them. This approach places desktop PCs in low-power mode when inactive and switches them to running mode when pages are needed by the VM running on the consolidation server. To ensure that desktops save energy, we have developed sleep scheduling and prefetching algorithms, as well as the context-aware selective resume framework, a novel approach to reduce the latency of power mode transition operations in commodity PCs. Jettison, our software prototype of partial VM migration for off-the-shelf PCs, can deliver 44--91% energy savings during idle periods of at least 10 minutes, while providing low migration latencies of about 4 seconds and migrating minimal state that is under an order of magnitude of the VM’s memory footprint.
Initial Establishment of the Chinese Affective Words Categorize System used in Research of Emotional Disorder

Objective: To establish the Chinese effective words categorize system used in research of emotional disorder,and offer standard material for study of abnormal emotion.Methods:Fifty-four subjects in different levels of education were collected to rate the valence,arousal and familiarity by self-report in a 9-point rating scale for 344 Chinese two-character effective words.Results: According to analysis of variance there were main effects in the valence(F=2514.96,P=0.000),arousal(F=147.43,P=0.000) and familiarity(F=106.81,P=0.000) respectively.The average valence score of positive words(7.29±0.41) was higher than that of negative words and neutral words,and the average valence score of neutral words(5.47±0.66) was higher than that of negative words(2.81±0.30);the average arousal score of positive words(6.57±0.39) was higher than that of negative words(5.33±0.41) and neutral words(5.23±0.67);the average familiarity score of positive words(5.98±0.57) was higher than that of negative words and neutral words,and the average familiarity score of neutral words(5.21±0.93) was higher than that of negative words(4.63±0.53). Conclusion: The Chinese affective words system used in research of emotional disorder is established well,and provides material of word for further study of abnormal emotion.
Lifted Linear Programming

Lifted inference approaches have rendered large, previously intractable probabilistic inference problems quickly solvable by handling whole sets of indistinguishable objects together. Triggered by this success, we show that another important AI technique is liftable, too, namely linear programming. Intuitively, given a linear program (LP), we employ a lifted variant of Gaussian belief propagation (GaBP) to solve the systems of linear equations arising when running an interiorpoint method to solve the LP. However, this #
State-Dependent and Timing-Dependent Bidirectional Associative Plasticity in the Human SMA-M1 Network

The supplementary motor area (SMA-proper) plays a key role in the preparation and execution of voluntary movements. Anatomically, SMA-proper is densely reciprocally connected to primary motor cortex (M1), but neuronal coordination within the SMA-M1 network and its modification by external perturbation are not well understood. Here we modulated the SMA-M1 network using MR-navigated multicoil associative transcranial magnetic stimulation in healthy subjects. Changes in corticospinal excitability were assessed by recording motor evoked potential (MEP) amplitude bilaterally in a hand muscle. We found timing-dependent bidirectional Hebbian-like MEP changes during and for at least 30 min after paired associative SMA-M1 stimulation. MEP amplitude increased if SMA stimulation preceded M1 stimulation by 6 ms, but decreased if SMA stimulation lagged M1 stimulation by 15 ms. This associative plasticity in the SMA-M1 network was highly topographically specific because paired associative stimulation of pre-SMA and M1 did not result in any significant MEP change. Furthermore, associative plasticity in the SMA-M1 network was strongly state-dependent because it required priming by near-simultaneous M1 stimulation to occur. We conclude that timing-dependent bidirectional associative plasticity is demonstrated for the first time at the systems level of a human corticocortical neuronal network. The properties of this form of plasticity are fully compatible with spike-timing-dependent plasticity as defined at the cellular level. The necessity of priming may reflect the strong interhemispheric connectivity of the SMA-M1 network. Findings are relevant for better understanding reorganization and potentially therapeutic modification of neuronal coordination in the SMA-M1 network after cerebral lesions such as stroke.
Somatomotor and Behavioral Changes Following Traumatic Brain Injury

Overpressurization blast (OB) exposure used to induce traumatic brain injury (TBI) in the rodent model can result in somatomotor and behavioral changes. Increased anxiety is evidenced after OB TBI in Dorsal and Frontal blast-wave exposed injured animals. Sustained impaired somatosensory functions occur after multiple OB injuries in Dorsal animals. Somatomotor function is impaired acutely but partially recovers after OB injury in Frontal animals. The Dorsal Group had reduction in risk-taking behavior in Group 1 (low pressure OB) and in total exploration in Group 2 (high pressure OB). The critical time point for somatosensory and somatomotor function impairment occurs at 24 hours post-OB injury with Group 1 demonstrating somatosensory and Group 2 demonstrating somatomotor deficits. The results suggest orientation and pressure magnitude have a significant impact on behavioral outcome measures following OB injuries as well as cumulative ef fects of repeated OB.
Effect of External Bending Moment and Creep on Sealing Behavior of Bolted Flanged Connections

A mechanical model based on the tightness of bolted flanged connections subjected to external bending moment was developed by numerical simulation with finite element method (FEM), in which creep and relaxation of bolts, flanges and gasket were taken into consideration. The residual stress distribution of gasket under different operating conditions was obtained. The effect of external bending moment and creep on the tightness of sealing connections was revealed. The FEM results were compared to that of analytical method established on the basis of the former research, and the leakage rate of the connection was predicted. The results obtained by both FEM and analytical method were in good agreement. The research can be used to analyze and assess the tightness of the bolted flanged connections in active service subjected to external bending moment and creep
Validity and reliability of the Malaysian creativity and innovation instrument (MyCrIn) using the Rasch measurement model

The Malaysian Creativity and Innovation Instrument (MyCrIn) is a test designed to identify creativity and innovation among University students in Malaysia. A sample of 285 students from a local public university in Malaysia were randomly selected for the study. This study aims to determine the reliability and validity of MyCrIn by using item analysis. MyCrIn comprises of 5 constructs which include High Order Thinking (HOT), Curiosity (CUR), Sensitivity (SEN), Visionary (VIS) and Adaptable to Change (ATC). Using the Rasch Measurement Model, analysis shows that eleven items in the form of a five-point Likert-scale were detected as misfits while no Dichotomous and Partial credit items were detected as misfits. Differential Item Functioning (DIF) based on gender was detected in three Likert-scale items, two Dichotomous items and three Partial Credit items. DIF based on race was found in ten Likert-scale items and one Partial Credit item. The results of the study can be used to determine more accurately the level of creativity and innovation among Malaysian students.
Training of neural classifiers by separating distributions at the hidden layer

A new cost function for training of binary classifiers based on neural networks is proposed. This cost function aims at separating the distributions for patterns of each class at the output of the hidden layer of the network. It has been implemented in a Generalized Radial Basis Function (GRBF) network and its performance has been evaluated under three different databases, showing advantages with respect to the conventional Mean Squared Error (MSE) cost function. With respect to the Support Vector Machine (SVM) classifier, the proposed method has also advantages both in terms of performance and complexity.
Well-Defined Semantic Templates for Pornographic Images Identification

Skin-color is proved to be powerful to pornographic images identification. However, skin-color is not determinant but heuristic. If we find documents with the same topic and some same keywords, we usually regard them as the same class. Based on this motivation, we proposed a well-defined semantic template, including topic template and bag-of-visual-words, to incorporate global semantics and local semantics for pornographic images identification. Topic template is designed to capture the patterns of whole images, such as areas of skin-color and some objects or scenes related to pornographic content. Visual words are intended to find some patterns of pornographic parts or poses which can be determinant to pornographic images identification. Our semantic templates can be applied for concept understanding and content analysis.
Stereo Correspondence with Occlusion Handling in a Symmetric Patch-Based Graph-Cuts Model

A novel patch-based correspondence model is presented in this paper. Many segment-based correspondence approaches have been proposed in recent years. Untextured pixels and boundaries of discontinuities are imposed with hard constraints by the discontinuity assumption that large disparity variation only happens at the boundaries of segments in the above approaches. Significant improvements on performance of untextured and discontinuity area have been reported. But, the performance near occlusion is not satisfactory because a segmented region in one image may be only partially visible in the other one. To solve this problem, we utilize the observation that the shared edge of a visible area and an occluded area corresponds to the discontinuity in the other image. So, the proposed model conducts color segmentation on both images first and then a segment in one image is further cut into smaller patches corresponding to the boundaries of segments in the other when it is assigned with a disparity. Different visibility of patches in one segment is allowed. The uniqueness constraint in a segment level is used to compute the occlusions. An energy minimization framework using graph-cuts is proposed to find a global optimal configuration including both disparities and occlusions. Besides, some measurements are taken to make our segment-based algorithm suffer less from violation of the discontinuity assumption. Experimental results have shown superior performance of the proposed approach, especially on occlusions, untextured areas, and near discontinuities
N-gram distribution based language model adaptation

This paper presents two techniques for language model (LM) adaptation. The first aims to build a more general LM. We propose a distribution-based pruning of n-gram LMs, where we prune n-grams that are likely to be infrequent in a new document. Experimental results show that the distribution-based pruning method performed up to 9% (word perplexity reduction) better than conventional cutoff methods. Moreover, the pruning method results in a more general ngram backoff model, in spite of the domain, style, or temporal bias in the training data. The second aims to build a more task-specific LM. We propose an n-gram distribution adaptation method for LM training. Given a large set of out-of-task training data, called training set, and a small set of task-specific training data, called seed set, we adapt the LM towards the task by adjusting the n-gram distribution in the training set to that in the seed set. Experimental results show non-trivial improvements over conventional methods.
Ways of Integrating Media Literacy Education into Ideological and Political Education for College Students in the New Media Era

In the new media age, the rapid quantity growth of media and the unlimited increasing of media information content have promoted the mediaâ€™s influence to peopleâ€™s daily life. In the college and university, it is not only changing greatly the university student's life, it also shaping university studentâ€™s life, value and the world outlook. Thus, it has become the necessity that improving media literacy of the ideological and political workers to make media literacy education being integrated into the ideological and political workers and teach students carry out a scientific, rational contact and use with media. Based on all these, this paper discusses the inevitability and feasibility of the combination of media literacy education and ideological and political education, and puts forward some proposed means of their integrations.
- 1-An Improved Algorithm on Calculating the Minimum Dominating Connected Set for Efficient Routing in Ad hoc Wireless Network

This paper presents a new approach to compute the MCDS (Minimum Connected Dominating Set) for Mobile Ad hoc Network (MANET). The problem of finding a MCDS is NP-hard. This approach is based on linear programming theory. In first step, we formulate the problem to find the minimum dominating set as an integer linear programming problem. Next, we add constraints to the original problem to force the minimum dominating set to be a connected set. The effectiveness of the approach is confirmed through simulation study and comparison with other approaches.
An Empirical Review of Methods for Temporal Distribution and Interpolation in the National Accounts

THE Bureau of Economic Analysis has adopted a new method for the interpolation of quarterly and monthly estimates in the national accounts. The new method uses a variant of the Denton procedure. National statistical agencies routinely face the task of compiling a large number of quarterly and monthly estimates using relatively complete annual data and less complete quarterly and monthly information from various indicators. Annual data are usually detailed and of high precision, providing the most reliable in­ formation on the overall level and long-term move­ ment in the series. Quarterly or monthly data, while they are less detailed and of lower precision, provide timely and explicit information about the short-term movement in a series. The objective of interpolation in the national eco­ nomic accounts is to use annual data to derive quar­ terly or monthly estimates that preserve as much as possible the short-term movement in the indicator se­ ries while still summing to a benchmark set by the an­ nual data.1 Typically, the annual sums of the quarterly or monthly indicator values are not consistent with the annual values. This means the two series may display inconsistent movements over time. Over the years, the Bureau of Economic Analysis (BEA) has used a variety of techniques for interpola­ tion of the national accounts.2 These techniques yielded varying degrees of success, and analysts at BEA identified some technical challenges in the estimation process: ● Final quarterly or monthly series do not always fol­ low the short-term movement in the indicator series.
Identification of time-varying modal parameters using linear time-frequency representation

A new method of parameter identification based on linear time-frequency representation and Hilbert transform is proposed in this paper to identify modal parameters of linear time-varying systems from measured vibration responses. With Gabor expansion and synthesis theory, measured responses are represented in time-frequency domain and modal components are reconstructed by time-frequency filtering. Hilbert transform is applied to obtain time histories of the amplitude and phase angle of each modal component, from which time-varying frequencies and damping ratios are identified. The proposed method has been demonstrated with a numerical example in which a linear time-varying system of two degrees of freedom is used to validate the identification scheme based on time-frequency representation. Simulation results have indicated that time-frequency representation presents an effective tool for modal parameter identification of time-varying systems. NOMENCLATURE ) , ( k n GS Gabor coefficient ) (t gnk Gabor basis ) (k g Synthetic window function ) (k h Analytic widow function ) (t M ) (t C ) (t K Mass ,damping, stiffness matrices r r r p u t a , ), ( rth scale factor, modal vector, eigenvalue r r q t), ( η amplitudes of scale factor and modal vector r r t γ θ ), ( phases of scale factor and modal vector r r β α , Real part and image part of eigenvalue ) (t yr rth modal component ) (i r ω , ) (i r ξ rth modal frequency, damping ratio ) ( ˆ t yr Hilbert transform of ) (t yr
Information analysis of microwave hyperspectral remote sensing for inversed water vapour content in atmosphere

A measurement, about the atmosphere from the ground-based microwave radiometers with high spectral resolution, would appear to contain a large amount of information about water vapour content. In this paper, the use of Shannon Entropy in information theory and the Multi-resolution wavelet transform, which can be defined without relating to the given retrieval method, can apportion measures of resolution to specific altitude ranges and pattern scales. Simulation study is done to examine the different performance of the information gain of hyperspectral technology compared with the traditional sounder.
Incorporating distance constraints into species distribution models

Summary 1. Species distribution models (SDM) are increasingly applied as predictive tools for purposes of conservation planning and management. Such models rely on the concept of the ecological niche and assume that distribution patterns of the modelled species are at some sort of equilibrium with the environment. This assumption contrasts with empirical evidence indicating that distribution patterns of many species are constrained by dispersal limitation. 2. We demonstrate that the performance of SDM based on presence-only data can be significantly enhanced by incorporating distance constraints (functions relating the likelihood of species’ occurrences at a site to the distance of the site from known presence locations) to the modelling procedure. This result is highly consistent for a variety of niche-based models (ENFA, DOMAIN and Mahalanobis distance), distance functions (nearest neighbour distance, cumulative distance and Gaussian filter) and taxonomic groups (plants, snails and birds, a total of 226 species). 3. Distance constraints are expected to enhance the accuracy of niche-based models even in the absence of strong dispersal limitation by accounting for mass effects and spatial autocorrelation in environmental factors for which data are not available. 4. While distance-based methods outperformed niche-based models when all data were used, their accuracy deteriorated sharply with smaller sample sizes. Niche-based methods are shown to cope better with small sample sizes than distance-based methods, demonstrating the potential advantage of niche-based models when calibration data are limited. 5. Synthesis and applications. Incorporating distance constraints in SDM provides a simple yet powerful method to account for spatial autocorrelation in patterns of species distribution, and is shown empirically to improve significantly the performance of such models. We therefore recommend incorporating distance constraints in future applications of SDM.
MIRAGE: The minimum information required for a glycomics experiment

The MIRAGE (minimum information required for a glycomics experiment) initiative was founded in Seattle, WA, in November 2011 in order to develop guidelines for reporting the qualitative and quantitative results obtained by diverse types of glycomics analyses, including the conditions and techniques that were applied to prepare the glycans for analysis and generate the primary data along with the tools and parameters that were used to process and annotate this data. These guidelines must address a broad range of issues, as glycomics data are inherently complex and are generated using diverse methods, including mass spectrometry (MS), chromatography, glycan array-binding assays, nuclear magnetic resonance (NMR) and other rapidly developing technologies. The acceptance of these guidelines by scientists conducting research on biological systems in which glycans have a significant role will facilitate the evaluation and reproduction of glycomics experiments and data that is reported in scientific journals and uploaded to glycomics databases. As a first step, MIRAGE guidelines for glycan analysis by MS have been recently published (Kolarich D, Rapp E, Struwe WB, Haslam SM, Zaia J., et al. 2013. The minimum information required for a glycomics experiment (MIRAGE) project – Improving the standards for reporting mass spectrometry-based glycoanalytic data. Mol. Cell Proteomics. 12:991–995), allowing them to be implemented and evaluated in the context of real-world glycobiology research. In this paper, we set out the historical context, organization structure and overarching objectives of the MIRAGE initiative.
SARF: Smart activity recognition framework in Ambient Assisted Living

Human activity recognition in Ambient Assisted Living (AAL) is an important application in health care systems and allows us to track regular activities or even predict these activities in order to monitor healthcare and find changes in patterns and lifestyles. A review of the literature reveals various approaches to discovering and recognizing human activities. The presence of a vast number of activity recognition issues and approaches has made it difficult to make adequate comparisons and accurate assessment. Introducing the five basic components of activity recognition in the smart homes as a famous environment to remote monitoring of patients and independent living for elderly, the present paper proposes SARF framework to classify each of activity recognition approaches and then it is evaluated based on the proposed classification by some proposed measures. Using SARF proposed framework can play an effective role in selecting the appropriate method for human activity recognition in smart homes and beneficial in analysis and evaluation of different methods for various challenges in this field.