Miracle-dz/UniFAR-FTUs huggingface dataset:
BPM for change management: two process diagnosis techniques

Purpose – This paper focuses on organizational change through the business process management approach. While “business process modeling” permits understanding process activities and their activities with other participants, “current reality tree (CRT)” technique promotes the identification of process constraints. The purpose of this study is to compare the results from applying both diagnostic techniques, process modeling, using the business process modeling notation, and root cause analysis, using the CRT. Design/methodology/approach – The comparison is made using a pre-experiment in which two teams conducted diagnoses concomitantly in the information technology management (ITM) process of one unit of the biggest and prestigious higher education institution (HEI) in Brazil. Findings – The modeling technique and the CRT should be considered complementary techniques, since applying one does not diminish or exclude the importance of using the other. Results were compared analyzing which dimensions of the p.
Color image retrieval and classification using fuzzy similarity measure and fuzzy clustering method

Color image retrieval and classification are very important in the field of image processing. In this paper, we propose a method which is in token of color characteristic of one image using hue and thereby is used to calculate similarity between two pictures. We also take F-Stat. Measure to find the best threshold so that we can realize fuzzy partition, and finally fuzzy c-means algorithm is used to do image classification and the calculation of subjection degree of one picture in the corresponding class. The corresponding mathematical model is established. Also, we construct a frame in which image comparability is obtained through fuzzy similarity measure based on hue feature vector of image, thus image retrieval is finished, and image classification is realized by fuzzy clustering. The comparison of image retrieval result between RGB feature vector and only-hue feature vector in token of image characteristic is taken. The experiment shows that the idea which takes this fuzzy similarity measure and fuzzy clustering method as the scheme of image retrieval and classification is reasonable and effective.
Efficient online validation with delta execution

Software systems are constantly changing. Patches to fix bugs and patches to add features are all too common. Every change risks breaking a previously working system. Hence administrators loathe change, and are willing to delay even critical security patches until after fully validating their correctness. Compared to off-line validation, on-line validation has clear advantages since it tests against real life workloads. Yet unfortunately it imposes restrictive overheads as it requires running the old and new versions side-by-side. Moreover, due to spurious differences (e.g. event timing, random number generation, and thread interleavings), it is difficult to compare the two for validation. To allow more effective on-line patch validation, we propose a new mechanism, called delta execution, that is based on the observation that most patches are small. Delta execution merges the two side-by-side executions for most of the time and splits only when necessary, such as when they access different data or execute different code. This allows us to perform on-line validation not only with lower overhead but also with greatly reduced spurious differences, allowing us to effectively validate changes. We first validate the feasibility of our idea by studying the characteristics of 240 patches from 4 server programs; our examination shows that 77% of the changes should not be expected to cause large changes and are thereby feasible for Delta execution. We then implemented Delta execution using dynamic instrumentation. Using real world patches from 7 server applications and 3 other programs, we compared our implementation of Delta execution against a traditional side-by-side on-line validation. Delta execution outperformed traditional validation by up to 128%; further, for 3 of the changes, spurious differences caused the traditional validation to fail completely while Delta execution succeeded. This demonstrates that Delta execution can allow administrators to use on-line validation to confidently ensure the correctness of the changes they apply.
Efficiently detecting outlying behavior in video-game players

In this paper, we propose a method for automatically detecting the times during which game players exhibit specific behavior, such as when players commonly show excitement, concentration, immersion, and surprise. The proposed method detects such outlying behavior based on the game players’ characteristics. These characteristics are captured non-invasively in a general game environment. In this paper, cameras were used to analyze observed data such as facial expressions and player movements. Moreover, multimodal data from the game players (i.e., data regarding adjustments to the volume and the use of the keyboard and mouse) was used to analyze high-dimensional game-player data. A support vector machine was used to efficiently detect outlying behaviors. We verified the effectiveness of the proposed method using games from several genres. The recall rate of the outlying behavior pre-identified by industry experts was approximately 70%. The proposed method can also be used for feedback analysis of various interactive content provided in PC environments.
Exceedence Probabilities of Local Maxima of Non-isotropic Random Elds, with an Application to Shape Analysis via Surface Displacements

Data used for the analysis of shape change has been modeled as non-isotropic Gaussian random elds, and local changes in shape are detected by local maxima of a random eld of test statistics derived from this data. In this paper we use the Sampson & Guttorp (1992) model for non-isotropy in which their exists an unknown mapping of the support of the data to a space in which the random elds are isotropic. We derive a simple estimator of this mapping, and use it to derive estmators of parameters required to nd the exceedence probability of local maxima based on the expected Euler characteristic of the excursion set of the test statistic random eld. The results are used to detect shape changes in the outer cortical surface of the brain.
Can Neutrino-cooled Accretion Disks Be an Origin of Gamma-Ray Bursts?

It is often proposed that a massive torus with approximately solar mass surrounding a stellar-mass black hole could be a central engine of gamma-ray bursts. We study the properties of such massive accretion tori (or disks) based on the α viscosity model. For surface density exceeding about 1020 g cm-2, which is realized when ~1 M☉ of material is contained within a disk of size ~5 × 106 cm, we find that (1) the luminosity of photons is practically zero because of significant photon trapping, (2) neutrino cooling dominates over advective cooling, (3) the pressure of degenerate electrons dominates over the pressure of gas and photons, and (4) the magnetic field strength exceeds the critical value of about 4 × 1013 G, even if we take 0.1% of the equipartition value. The possible observable quantum electrodynamical (QED) effects arising from supercritical fields are discussed. Most interestingly, photon splitting may occur, producing a significant number of photons of energies below ~511 keV, thereby possibly suppressing e± pair creation.
An Architecture for Ubiquitous and Collaborative 3D Position Sensing for Ubiquitous 3D Drawing

Many methods for 3D position sensing using magnetic sensors, the ultrasonic sensors, special cameras, and so on have been proposed. Most of them, however, require specialized equipment that must be installed in the environment in question. This drawback prevents prototype 3D systems from reaching practical use in real fields. gUbiquitous 3D drawingh (namely, drawing a sketch in any 3D space in front of a designer), which appears as a common feature in a conventional 3D system, is investigated, and a new method for 3D position detection, called gUbiC3D (ubiquitous and collaborative 3D position sensing) architecture, is proposed. UbiC3D uses only a single camera with sensors and generates a global 3D map of visual feature points through users' collaboration. A preliminary experiment shows that the UbiC3D architecture is feasible.
On the Modularity Assessment of Software Architectures: Do my architectural concerns count?

Much of the complexity of software architecture design is derived from the inadequate modularization of key broadly-scoped concerns, such as exception handling and persistence. However, conventional architecture metrics are not sensitive to the driving architectural concerns, thereby leading a number of false positives and false negatives in the design assessment process. Hence, there is a need for assessment techniques that support a more effective identification of early design modularity anomalies relative to crosscutting concerns. In this context, this paper proposes a concern-driven measurement framework for assessing architecture modularity. It encompasses a mechanism for documenting architectural concerns, and a suite of concern-driven architecture metrics. We evaluated the usefulness of the proposed framework while comparing the modularity of aspect-oriented (AO) and non-AO architecture design alternatives in three different case studies.
Information Theory Orthogonality-embedded space-time codes

We present a unified construction of full-diversity space-time block codes (STBC) called orthogonality-embedded space-time (OEST) codes. Other existing STBC, including orthogonal, quasi-orthogonal and rate-one linear threaded algebraic space-time (LTAST) codes, can also be derived from OEST codes. The new OEST construction is of the form , where Ak and Bk are linear-dispersion matrices of orthogonal STBC and Cks are circulant matrices. The circulant matrices encode the data vectors, which can be completely separately detected at the receiver, greatly reducing the decoding complexity. For the same number of transmit antennas, several variants of OEST codes can be constructed allowing a tradeoff among the rate, performance and decoding complexity. A new rate-one STBC derived from OEST codes, called semi-orthogonal algebraic space-time codes, is shown to achieve near capacity of multi-input single-output channels and performs better than several existing STBC. Copyright © 2007 John Wiley & Sons, Ltd.
A future for usability engineering

This paper reviews the “unusability culture” and its symptoms. For usability engineering to have an effective future it must take advantage of new design tools and techniques. A particular approach is discussed in detail. It is argued that the approach, based on “interactive design assistants” is effective, and can be used to make radical improvements to design processes and to usability research. The approach reduces barriers between participants in usability: between designers, programmers, technical authors, users. By running on the World Wide Web, the assistants would open access to usability engineering, and increase public awareness and participation in design. The approach is argued to contribute to a new future for usability engineering.
Speaker Representations for Speaker Adaptation in Multiple Speakers' BLSTM-RNN-Based Speech Synthesis

Training a high quality acoustic model with a limited database and synthesizing a new speaker’s voice with a few utterances have been hot topics in deep neural network (DNN) based statistical parametric speech synthesis (SPSS). To solve these problems, we built a unified framework for speaker adaptive training as well as speaker adaptation on Bidirectional Long ShortTerm Memory with Recurrent Neural Network (BLSTM-RNN) acoustic model. In this paper, we mainly focus on speaker identity control at the input layer of our framework. We have investigated i-vector and speaker code as different speaker representations when used in an augmented input vector, and also propose two approaches to estimate a new speaker’s code. Experimental results show that the speaker representations input to the first layer of acoustic model can effectively control speaker identity during speaker adaptive training, thus improving the synthesized speech quality of speakers included in training phase. For speaker adaptation, speaker code estimated from MFCCs can achieve higher preference than other speaker representations.
Differential changes in Neuregulin-1 signaling in major brain regions in a lipopolysaccharide-induced neuroinflammation mouse model

Neuregulin 1 (Nrg1) is involved in multiple biological processes in the nervous system. The present study investigated changes in Nrg1 signaling in the major brain regions of mice subjected to lipopolysaccharide (LPS)-induced neuroinflammation. At 24 h post-intraperitoneal injection of LPS, mouse brain tissues, including tissues from the cortex, striatum, hippocampus and hypothalamus, were collected. Reverse transcription-polymerase chain reaction was used to determine the expression of Nrg1 and its receptors, Neu and ErbB4, at the mRNA level. Western blotting was performed to determine the levels of these proteins and the protein levels of phosphorylated extracellular signal-regulated kinases (Erk)1/2 and Akt1. Immunohistochemical staining was utilized to detect the levels of pNeu and pErbB4 in these regions. LPS successfully induced sites of neuroinflammation in these regions, in which changes in Nrg1, Neu and ErbB4 at the mRNA and protein levels were identified compared with controls. LPS induced a reduction in pNeu and pErbB4 in the striatum and hypothalamus, although marginally increased pErbB4 levels were found in the hippocampus. LPS increased the overall phosphorylation of Src but this effect was reduced in the hypothalamus. Moreover, increased phosphorylation of Akt1 was found in the striatum and hippocampus. These data suggest diverse roles for Nrg1 signaling in these regions during the process of neuroinflammation.
An Analysis Framework for Mobility Metrics in Mobile Ad Hoc Networks

Mobile ad hoc networks (MANETs) have inherently dynamic topologies. Under these difficult circumstances, it is essential to have some dependable way of determining the reliability of communication paths. Mobility metrics are well suited to this purpose. Several mobility metrics have been proposed in the literature, including link persistence, link duration, link availability, link residual time, and their path equivalents. However, no method has been provided for their exact calculation. Instead, only statistical approximations have been given. In this paper, exact expressions are derived for each of the aforementioned metrics, applicable to both links and paths. We further show relationships between the different metrics, where they exist. Such exact expressions constitute precise mathematical relationships between network connectivity and node mobility. These expressions can, therefore, be employed in a number of ways to improve performance of MANETs such as in the development of efficient algorithms for routing, in route caching, proactive routing, and clustering schemes.
On Energy-optimal Cooperation Strategy in Cognitive Radio Networks

Taking into account the overall energy consumption during consecutive processes of opportunistic spectrum access in cognitive radio networks, including sensing locally, reporting sensing results and transmitting data, etc., an energy efficient cooperation strategy is investigated in this paper. First, we formulate the energy-efficient cooperation problem for two special scenarios with SUs in different distribution ranges. By determining how many SUs to cooperate and which SUs to cooperate in the spectrum sensing, the overall sensing and transmitting energy is minimized. Based on the theoretic analysis, a low-complexity heuristic algorithm is proposed to find the most appropriate set of cooperative SUs corresponding to the minimal energy consumption. The simulation results show that the proposed algorithm can achieve a near-optimal performance.
The association between human papillomavirus (HPV) 16, HPV18, and other HR-HPV viral load and the histological classification of cervical lesions: Results from a large-scale cross-sectional study.

Background The relationship between HPV viral load and histological grades in the development of cervical cancer is in argument. It is helpful to better understand the association by quantitatively detecting viral load of HPV16, 18 and a pool of 12 other high risk HPV type (OT) independently on the samples of precancer and cancer. Methods A cross-sectional study was performed in five medical centers of China. Histological diagnosis made by local pathologists was adjudicated via a pathology expert panel. A fully automated real-time PCR test was used for the measurement of HPV16, 18, OT and human β-globin gene. Results A total of 2513 women [1341 normal, 209 low grade intraepithelial lesion (LSIL), 392 high grade intraepithelial lesion (HSIL), 520 squamous cell carcinoma (SCC) and 51 adenocarcinoma (ADC)] were included. There is a linear increase in the total 14 HPV viral load with histological grade from normal to SCC. This trend was not observed in HPV18 infection but HPV16. The viral load for OT was low in normal, peaked in LSIL and HSIL, and declined in SCC and ADC. In the co-infection of HPV16 and HPV18, HPV16 viral load was significantly higher than HPV18 in LSIL and HSIL. In co-infection of HPV16 and OT, higher HPV16 viral load was also seen in SCC and ADC. Conclusions Viral load of HPV16 increases with cervical lesion grade and is predominant in cervical cancer. HPV18 viral load is low in precancer, but going up in cancer. OT viral load shows inverse trend of HPV18. This article is protected by copyright. All rights reserved
Cluster Analysis to Understand Socio-ecological Systems: a Guideline

In coupled human-environment systems where well established and proven general theories are often lacking cluster analysis provides the possibility to discover regularities – a first step in empirically based theory building. The aim of this report is to share the experiences and knowledge on cluster analysis we gained in several applications in this realm helping to avoid typical problems and pitfalls. In our description of issues and methods we will highlight well-known mainstream methods as well as promising new developments, referring to pertinent literature for further information, thus offering also some potential new insights for the more experienced. The following aspects are discussed in detail: data-selection and pre-treatment, selection of a distance measure in the data space, selection of clustering method, performing clustering (parameterizing the algorithm(s), determining the number of clusters etc.) and the interpretation and evaluation of results. We link our description – as far as tools for performing the analysis are concerned-to the R software environment and its associated cluster analysis packages. We have used this public domain software, together with own tailor-made extensions, documented in the appendix.
1 What Happened to Japanese Banks ?

The author was a visiting scholar at the Institute for Monetary and Economic Studies at the Bank of Japan when this research was started. He is grateful for the financial support and hospitality that he received at the institute. He benefited from numerous conversations with the researchers at the institute, especially Masahiro Higo, Shuji Kobayakawa, Hisashi Nakamura, Shigenori Shiratsuka, and Tatsuya Yonetani. The author also thanks Frank Packer, also a visiting scholar at the same time, for helpful discussion, and an anonymous referee for useful comments. MONETARY AND ECONOMIC STUDIES/FEBRUARY 2001
A Low-Voltage Chopper-Stabilized Amplifier for Fetal ECG Monitoring With a 1.41 Power Efficiency Factor

This paper presents a low-voltage current-reuse chopper-stabilized frontend amplifier for fetal ECG monitoring. The proposed amplifier allows for individual tuning of the noise in each measurement channel, minimizing the total power consumption while satisfying all application requirements. The low-voltage current reuse topology exploits power optimization in both the current and the voltage domain, exploiting multiple supply voltages (0.3, 0.6 and 1.2 V). The power management circuitry providing the different supplies is optimized for high efficiency (peak charge-pump efficiency = 90%). The low-voltage amplifier together with its power management circuitry is implemented in a standard 0.18 μm CMOS process and characterized experimentally. The amplifier core achieves both good noise efficiency factor (NEF=1.74) and power efficiency factor (PEF=1.05). Experiments show that the amplifier core can provide a noise level of 0.34 μVrms in a 0.7 to 182 Hz band, consuming 1.17 μW power. The amplifier together with its power management circuitry consumes 1.56 μW, achieving a PEF of 1.41. The amplifier is also validated with adult ECG and pre-recorded fetal ECG measurements.
The core/envelope symmetry in pulsating stars

We demonstrate that there is an inherent symmetry in the way high-overtone stellar pulsations sample the core and the envelope, which can potentially lead to an ambiguity in the asteroseismologically derived locations of internal structures. We provide an intuitive example of the source of this symmetry by analogy with a vibrating string. For the stellar case, we focus on the white dwarf stars, establishing the practical consequences for high-order white dwarf pulsations both analytically and numerically. In addition, we verify the effect empirically by cross-fitting two different structural models, and we discuss the consequences that this approximate symmetry may have for past and present asteroseismological fits of the pulsating DBV, GD 358. Finally, we show how the signatures of composition transition zones that are brought about by physically distinct processes may be used to help alleviate this potential ambiguity in our asteroseismological interpretation of the pulsation frequencies observed in white dwarf stars.
New Insights into Network Motif Clusters from the Views of Cellular Localizations and Signal Pathways ∗

Biological complex networks, such as protein-protein interaction network (PPIN), represent the underlying living mechanisms in cell. Begin with the PPIN, distinct level modular organizations appear, like so-called network motifs, protein complexes and signal pathways. The network motifs defined as spandrels are highly clustered. Here, the motif clusters are divided into two categories, i.e. inner motif clusters (IMC) and outer motif clusters (OMC), based on protein complexes. IMC contains more network motifs inside some protein complex contrasting to OMC. In topological structure, the IMCs are connected more loosely than OMCs and in biology roles the IMCs mainly located in nucleus and serve for the signal pathways closely related to nucleus while OMCs mainly located in cytoplasm and reach for the signal pathways unrelated to nucleus, moreover, in contrast to OMCs, IMCs can reach less cellular localizations. Therefore, from the protein-protein interaction level, subsets of proteins that define functionally meaningful entities can reveal the underlying living mechanisms in cell.