Miracle-dz/UniFAR-FTUs huggingface dataset:
“Look! A Black Ethnographer!”: Fanon, Performance, and Critical Ethnography

This article engages the possibility of a critical Black ethnography and a performative fugitivity. Drawing on the author’s ethnographic research, it examines the tension between being a racialized and gendered person and becoming an ethnographic self. This tension rises when critical Black ethnographers are visually rendered outside the domain of the ethnographer, a category forged against the template of Western White male subjects. Instead, they are interchangeable with the populations they perform research with and suspect to performances of racialized and gendered violence. This opens up an emergent politics for the possibility of a critical Black ethnographer who alters how ethnographic practice is undertaken to grapple with the realities of race and gender by the critical Black ethnographer in the field. That said, the critical Black ethnographer must reconcile being Black, becoming an ethnographer, and what it would mean to be a critical Black ethnographer. To do so, this article draws on Frantz Fanon and situates him as both a performer and a critical ethnographer to analyze how does a critical Black ethnographer engage with performance, performativity, and the performative.
ACP approach based intelligent quality management system for manufacturing processes

With the rapid progress of information and electronic technology, traditional industrial processes are becoming more and more complex. It is very important for manufacturing enterprises to manage and control the product quality under the circumstance of big data. Based on artificial systems, computational experiments, and parallel execution approach, modeling methods by mechanism, data, heuristic rules, etc. are proposed to construct intelligent management and control system for complex manufacturing processes. The presented system is helpful to visualize production processes, to earlier detect potential problems, to quantitatively analyze various risks, to verify management strategies by computational experiments, to optimize decisions by parallel execution.
UM-PRS: An implementation of the procedural reasoning system for multirobot applications

The Procedural Reasoning System (PRS) is used in applications where predetermined situations might arise. The UM-PRS provides a reasoning system that represents robotic applications even in unpredictable domains, such as the robotic reconnaissance task domain outlined here. UM-PRS incorporates a changing context, rather than relying solely on a prearranged plan. The UM-PRS here provides representation important in the reasoning and interface between a mission plan and the executable map of an outdoor vehicle that changes its behavior based on what it comes in contact with in its environment. PRS is thus used in the dynamic control of such a vehicle, providing the basis for coordinating the joint task of multiple robotic vehicles by the their individual observations and representation.
Classi cation for High-Dimension Small-Sample data Sets Based on Kullback-Leibler Information Measure

In classifying samples by Gaussian classi er, the covariance matrix estimated with a small number sample set becomes unstable, which leads to degrading the classi cation accuracy. In this paper, we discuss the covariance matrix estimation problem for small number samples with high dimension setting based on Kullback-Leibler Information Measure. A new covariance matrix estimator is developed, and a fast, rough estimating regularization parameter formula is derived. Experiments are performed to investigate the classi cation accuracy with developed covariance matrix estimator and higher classi cation accuracy results are obtained.
Integron Gene Cassettes: A Repository of Novel Protein Folds with Distinct Interaction Sites

Mobile gene cassettes captured within integron arrays encompass a vast and diverse pool of genetic novelty. In most cases, functional annotation of gene cassettes directly recovered by cassette-PCR is obscured by their characteristically high sequence novelty. This inhibits identification of those specific functions or biological features that might constitute preferential factors for lateral gene transfer via the integron system. A structural genomics approach incorporating x-ray crystallography has been utilised on a selection of cassettes to investigate evolutionary relationships hidden at the sequence level. Gene cassettes were accessed from marine sediments (pristine and contaminated sites), as well as a range of Vibrio spp. We present six crystal structures, a remarkably high proportion of our survey of soluble proteins, which were found to possess novel folds. These entirely new structures are diverse, encompassing all-α, α+β and α/β fold classes, and many contain clear binding pocket features for small molecule substrates. The new structures emphasise the large repertoire of protein families encoded within the integron cassette metagenome and which remain to be characterised. Oligomeric association is a notable recurring property common to these new integron-derived proteins. In some cases, the protein–protein contact sites utilised in homomeric assembly could instead form suitable contact points for heterogeneous regulator/activator proteins or domains. Such functional features are ideal for a flexible molecular componentry needed to ensure responsive and adaptive bacterial functions.
The Role of Blood Pressure Variability in the Development of Nephropathy in Type 1 Diabetes

OBJECTIVE Increases in blood pressure and visit-to-visit variability have both been found to independently increase the likelihood of cardiovascular events in nondiabetic individuals. This study has investigated whether each may also influence the development of microvascular complications in type 1 diabetes by examining data from the Diabetes Control and Complications Trial (DCCT). RESEARCH DESIGN AND METHODS Using binary longitudinal multiple logistic regression, mean systolic (SBP) and diastolic (DBP) blood pressure as well as annual visit-to-visit variability (SD.SBP and SD.DBP, respectively) was related to the risk of the development/progression of nephropathy and retinopathy in initially normotensive subjects who did not become pregnant during the DCCT. RESULTS Mean SBP and SD.SBP were independently predictive of albuminuria (odds ratio 1.005 [95% CI 1.002–1.008], P < 0.001 and 1.093 [1.069–1.117], P < 0.001, respectively, for 1 mmHg change), although SBP variability did not add to mean SBP in predicting retinopathy (0.999 [0.985–1.013], P = 0.93). DBP variability was also independently predictive of nephropathy (1.102 [1.068–1.137], P < 0.001) and not of retinopathy (0.991 [0.971–1.010], P = 0.37). Mean SBP was poorly related to SD.SBP (r2 < 0.01) as was mean DBP with SD. DBP (r2 < 0.01). CONCLUSIONS Visit-to-visit variability in blood pressure consistently independently added to mean blood pressure in predicting the risk of nephropathy, but not retinopathy, in the DCCT. This observation could have implications for the management and treatment of blood pressure in patients with type 1 diabetes.
Text clustering on authorship attribution based on the features of punctuations usage

This paper proposes a method of extracting writing characteristics of various authors based on their usage of punctuation marks. Comparative analysis has been done between the text clustering effects of the proposed method and character Bigram method using 200 articles of five well-known modern writers. The analysis also covers the performance of Euclidean distance, cosine distance and KLD (Kullback—Leibler) distance used in the text clustering. In conclusion, the analysis results show that: (1) The method proposed in this paper not only features low dimension, but also is superior to Bigram, (2) KLD has obvious advantages compared to Euclidean distance and cosine distance, and F1 value using the Ward hierarchical clustering of KLD distance can reach 96%∼99%.
Filler models for Automatic Speech Recognition created from Hidden Markov Models using the K-Means algorithm

In Automatic Speech Recognition (ASR), the presence of Out Of Vocabulary (OOV) words or sounds, within the speech signal, can have a detrimental effect on recognition performance. One common method of solving this problem is to use filler models to absorb the unwanted OOV utterances. A balance between accepting In Vocabulary (IV) words and rejecting OOV words can be achieved by manipulating the values of Word Insertion Penalty and Filler Insertion Penalty. This paper investigates the ability of three different classes of HMM filler models, K-Means, Mean and Baum-Welch, to discriminate between IV and OOV words. The results show that using the Baum-Welch trained HMMs 97.0% accuracy is possible for keyword IV acceptance and OOV rejection. The K-Means filler models provide the highest IV acceptance score of 97.3% but lower overall accuracy. However, the computational complexity of the K-Means algorithm is significantly lower and requires no additional speech training data.
Flexible XML‐based configuration of physical simulations

The extensible markup language XML can be used to support the integration of several component programming environments to create a flexible physical simulation system. Data exchange via open‐standard‐based plain text files allows system components to be loosely‐coupled, rather than combined into an integrated development environment, so that the most appropriate tools can be used for each component and the system can be extended with minimal disruption. This paper details an example application using this technology to configure a simulation of robotic manipulation. Those parts of the system that require real‐time data exchange use simple UNIX socket‐based interactions, which are configured using shared XML setup files. The approach provides a reusable template for other, similar projects. Copyright © 2004 John Wiley & Sons, Ltd.
Mining mobile application sequential patterns for usage prediction

In recent years, researches on smart phone services have received a lot of attention in both of the industry and academia due to a wide range of potential applications. Among them, one of popular topics is the mining and prediction of mobile application usage behaviors. In this paper, we propose a location-based approach to predict the mobile application usage behaviors. In this approach, we first discover the stay locations of the GPS movement data to obtain the mobile application usage database. Then, we consider both of the physical location moving paths and virtual application usage paths of users to mine the Mobile Application Sequential Patterns (MASPs) by the Mobile Application Sequential Pattern Mine (MASP-Mine) algorithm. Furthermore, a prediction strategy is designed to predict the next mobile application usage behaviors based on the MASPs. To our best knowledge, this is the first work on mining and prediction of mobile application usage behaviors with considerations of physical location moving paths and virtual application usage paths simultaneously. Through experimental evaluation under various condition settings by a real mobile application usage data, the proposed approach is shown to deliver excellent performance in terms of precision and recall.
IMF effect on the polar cap contraction and expansion during a period of substorms

Abstract. The polar cap boundary (PCB) location and motion in the nightside ionosphere has been studied by using measurements from the EISCAT radars and the MIRACLE magnetometers during a period of four substorms on 18 February 2004. The OMNI database has been used for observations of the solar wind and the Geotail satellite for magnetospheric measurements. In addition, the event was modelled by the GUMICS-4 MHD simulation. The simulation of the PCB location was in a rather good agreement with the experimental estimates at the EISCAT longitude. During the first three substorm expansion phases, neither the local observations nor the global simulation showed any poleward motions of the PCB, even though the electrojets intensified. Rapid poleward motions of the PCB took place only in the early recovery phases of the substorms. Hence, in these cases the nightside reconnection rate was locally higher in the recovery phase than in the expansion phase. In addition, we suggest that the IMF Bz component correlated with the nightside tail inclination angle and the PCB location with about a 17-min delay from the bow shock. By taking the delay into account, the IMF northward turnings were associated with dipolarizations of the magnetotail and poleward motions of the PCB in the recovery phase. The mechanism behind this effect should be studied further.
Feature vector classification based speech emotion recognition for service robots

This paper proposes an efficient feature vector classification for Speech Emotion Recognition (SER) in service robots. Since service robots interact with diverse users who are in various emotional states, two important issues should be addressed: acoustically similar characteristics between emotions and variable speaker characteristics due to different user speaking styles. Each of these issues may cause a substantial amount of overlap between emotion models in feature vector space, thus decreasing SER accuracy. In order to reduce the effects caused by such overlaps, this paper proposes an efficient feature vector classification for SER. The conventional feature vector classification applied to speaker identification categorizes feature vectors as overlapped and non-overlapped. Because this method discards all of the overlapped vectors in model reconstruction, it has limitations in constructing robust models when the number of overlapped vectors is significantly increased such as in emotion recognition. The method proposed herein classifies overlapped vectors in a more sophisticated manner, selecting discriminative vectors among overlapped vectors, and adds those vectors in model reconstruction. On SER experiments using an emotional speech corpus, the proposed classification approach exhibited superior performance to conventional methods, and displayed an almost human-level performance. In particular, we achieved commercially applicable performance for two-class (negative vs. non-negative) emotion recognition.
Understanding public relation practices in Chinese organisations: multiple logics and identities

In response to growing awareness of the inherent Western assumptions and biases in the dominant normative theories, we introduce key concepts of institutional logics and identities to the realm of PR study. Specifically, we highlight the primacy of logics and identities in discursive practice by exploring how a wide range of stakeholders conceptualise and understand PR in Chinese cultural contexts. We employed forty semi-structured interviews with PR agency consultants, in-house PR practitioners, media journalists and industry regulators. We have found that each group of stakeholders tend to interpret Chinese PR in relation to their identities. The established cultural contexts also serve as a “repertoire” for stakeholders to draw institutional logics and legitimise their interpretation of PR practice in China.
Recent Advances in Unification for the EL Family

Unification in Description Logics (DLs) has been proposed as an inference service that can, for example, be used to detect redundancies in ontologies. For the DL EL, which is used to define several large biomedical ontologies, unification is NP-complete. Several algorithms that solve unification in EL have previously been presented. In this paper, we summarize recent extensions of these algorithms that can deal with general concept inclusion axioms (GCIs), role hierarchies (H), and transitive roles (R). For the algorithms to be complete, however, the ontology consisting of the GCIs and role axioms needs to satisfy a certain cycle restriction.
Integrating the User in the Social Group Dynamics of Agents ∗

This paper introduces the Virtual Beergarden as a virtual meeting place for agents and users. The agents behavior is controlled by a behavior control component, which allows testing diﬀerent theories of social group dynamics. Agents interact via natural language that is generated by a statistical language component and takes into account the social interaction categories and the social relationships between agents. The user can freely navigate and interact with the other agents relying on the above mentioned components. An evaluation shows if the user can really be integrated in the agents’ social group
Face Detection Using Mixtures of Linear Subspaces Paper Number : 73

We present two methods using mixtures of linear subspaces for face detection in gray level images. One method uses a mixture of factor analyzers to concurrently perform clustering and, within each cluster, perform local dimensionality reduction. The parameters of the mixture model are estimated using an EM algorithm. A face is detected if the probability of an input sample is above a predefined threshold. The other mixture of subspaces method uses Kohonen’s self-organizing map for clustering and Fisher Linear Discriminant to find the optimal projection for pattern classification, and a Gaussian distribution to model th class-conditional density function of the projected sampl es for each class. The parameters of the class-conditional den sity functions are maximum likelihood estimates and the decision rule is also based on maximum likelihood. A wide range of face images including ones in different poses, with different expressions and under different lighting condit ions are used as the training set to capture the variations of human faces. Our methods have been tested on three sets of 225 images which contain 871 faces. Experimental results on the first two datasets show that our methods perform as well as the best methods in the literature, yet have fewer false detects.
Human action concentric video retrieval system using features weight updating method as relevance feedback

Retrieving videos based on its contents is becoming an increasingly popular area of research, because of enormous growth in the availability of multimedia information on public databases like Google and YouTube. Usually videos contain large variety of data but majority of online videos contain human as a subject of interest. In this paper, a human action based video retrieval system is presented which can be used to retrieve videos based on the contents of the query. The proposed system can search videos containing particular action on large databases efficiently. Furthermore, it is also shown that by using features weight updating approach as a Relevance feedback (RF), it is possible to involve user concepts interactively so that complex human action queries can be searched quickly to achieve useful results. Three popular Human action datasets namely Weizmann, KTH and UCF (sports) have been utilized in order to validate the performance of the proposed system. Experimental results and simulations show the efficacy of the proposed system. Even with number of visual challenges proposed approach will manage to get better accuracy as compare to other existing methods.
Comparing Two Variants of Calvo-Type Wage Stickiness

We compare two ways of modeling Calvo-type wage stickiness. One in which each household is the monopolistic supplier of a differentiated type of labor input (as in Erceg, et al., 2000) and one in which households supply a homogenous labor input that is transformed by monopolistically competitive labor unions into a differentiated labor input (as in Schmitt-Grohe and Uribe, 2006a,b). We show that up to a log-linear approximation the two variants yield identical equilibrium dynamics, provided the wage stickiness parameter is in each case calibrated to be consistent with empirical estimates of the wage Phillips curve. It follows that econometric estimates of New Keynesian models that rely on log-linearizations of the equilibrium dynamics are mute about which type of wage stickiness fits the data better. In the context of a medium-scale macroeconomic model, we show that the two variants of the sticky-wage formulation give rise to the same Ramsey-optimal dynamics, which call for low volatility of price inflation. Furthermore, under both specifications the optimized operational interest-rate feedback rule features a large coefficient on price inflation and a mute response to wage inflation and output.
Digraphs structures corresponding to realisation of multi-order fractional electrical circuits

This paper presents a method of the determination of a minimal stable realisation of the fractional continuous-time linear system with different fractional orders. For the proposed method, a digraph-based algorithm was constructed. In this paper, we have shown how we can perform the transfer matrix using electrical circuits consisting of resistances, inductances, capacitances and source voltages. The proposed method was discussed and illustrated with some numerical examples.
Families Facing the Opioid Crisis: Content and Frame Analysis of YouTube Videos

Opioid abuse has become a national crisis due to overprescribing, misuse, and misinformation. Data were collected from N = 125 YouTube videos, with n = 33 videos fitting the inclusion criteria for the analysis, which sought to understand the lived experiences of parents and families impacted by the opioid crisis. YouTube was utilized to research the opioid crisis due to the availability of up-to-date content and the large, diverse user base. Researchers used frame analysis and thematic content analysis, yielding two frames: (1) severe and urgent and (2) systemic, and four themes: (1) benefits and barriers to receiving counseling and supportive services, (2) multigenerational impact, (3) the importance of prevention and intervention, and (4) disbelief. Implications for counselors working with families affected by the opioid crisis and policy are discussed.
Framework and Items for Measuring End-User Computing Competency with a Case Study

—The end-user computing capability is necessitated for efficiently performing his or her given tasks and improving his or her business performance in an computing environment. A measurement framework and items of an end-user computing competency is extracted from the major components of a general computing competency. Through a survey measurement of 287 respondents, this study performed factor and reliability analyses, and proposed a 15-item framework that can examine an end-user computing competency in an organizational computing environment. The application of the measure is confirmed by applying it to measuring the computing competency of the end-users in a firm computing environment and by presenting the measurement results for them.