Miracle-dz/UniFAR-FTUs huggingface dataset:
Gravitational ensemble clustering

Data mining is one of the helpful and effective data analysis techniques that enable the extraction of interesting structures and knowledge from a large amount of data. Clustering is an important data mining task that refers to the process of categorizing data objects into cohesive groups called clusters. There are many clustering approaches proposed in the literature with different quality/complexity tradeoffs. It is well known that no clustering method can sufficiently handle all types of cluster structures and properties (e.g. shape, size, overlapping, and density). The idea of combining different clustering results (cluster ensemble or clustering aggregation) emerged as an approach to overcome the weakness of single algorithms and further improve their performances. In this paper, a novel consensus function based on the theory of gravity is presented which is called “Gravitational ensemble clustering (GEC)”. The proposed method combines “weak” clustering algorithms such as the K-means algorithm using gravitational clustering concepts. The proposed method is capable of the identification of true underlying clusters with arbitrary shapes, sizes and densities. Computational experiments were conducted to test the performance of the GEC approach using artificial and benchmark datasets. Undertaken experimental results illustrate the versatility and robustness of the proposed method, as compared to individual clusterings produced by well known clustering algorithms, and compared to other ensemble combination methods.
Aspectos da utilização do rastreamento ocular na pesquisa psicolinguística

O presente trabalho apresenta uma revisao critica da utilizacao da tecnica de rastreamento ocular na investigacao psicolinguistica do processamento online. Sao descritos alguns principios basicos de operacao de aparatos de rastreamento e a dinâmica elementar do comportamento oculomotor. De um ponto de vista teorico, discute-se a informatividade, para a pesquisa cognitiva, das medidas comportamentais obtidas por meio do rastreamento ocular, apresentando vantagens e desvantagens da utilizacao da tecnica e buscando demonstrar a relevância do rastreamento ocular para a compreensao do curso temporal dos processos envolvidos na compreensao da linguagem.
Improved Single Image Haze Removal by Multi Scale Fusion

The visibility of outdoor images can be degraded by the hazy weather conditions. A modified multi-scale fusion method is proposed in this paper to remove dense homogenous haze as well as fog present in an image. It is a fusion based strategy by deriving two hazy image inputs which is obtained by applying white balancing and a contrast enhancing procedure. Then filter their important features by applying weight maps which are luminance, chromaticity and saliency to preserve the important features of the derived inputs. These weight maps introduce artifacts in the images. To eliminate these artifacts we apply a multi scale fusion technique which is obtained by Gaussian and Laplacian pyramids. Then to eliminate the lightness of the image, we apply an image enhancement method. It is based on retinex theory and lightness decomposition method. The proposed method is then compared with the existing multi-scale fusion method. The results obtained shows that the new method enhances the image visibility in dense hazy regions.
Clinic Overbooking to Improve Patient Access and Increase Provider Productivity

The problem of patient no-shows (patients who do not arrive for scheduled appointments) is significant in many health care settings, where no-show rates can vary widely. No-shows reduce provider productivity and clinic efficiency, increase health care costs, and limit the ability of a clinic to serve its client population by reducing its effective capacity. In this article, we examine the problem of no-shows and propose appointment overbooking as one means of reducing the negative impact of no-shows. We find that patient access and provider productivity are significantly improved with overbooking, but that overbooking causes increases in both patient wait times and provider overtime. We develop a new clinic utility function to capture the trade-offs between these benefits and costs, and we show that the relative values that a clinic assigns to serving additional patients, minimizing patient waiting times, and minimizing clinic overtime will determine whether overbooking is warranted. From the results of a series of simulation experiments, we determine that overbooking provides greater utility when clinics serve larger numbers of patients, no-show rates are higher, and service variability is lower. Even with highly variable service times, many clinics will achieve positive net results with overbooking. Our analysis provides valuable guidance to clinic administrators about the use of appointment overbooking to improve patient access, provider productivity, and overall clinic performance.
Predictive analysis for detecting serializability violations through Trace Segmentation

We address the problem of detecting serializability violations in a concurrent program using predictive analysis, where a violation is detected either in an observed trace or in an alternate interleaving of events in that trace. Under the widely used notion of conflict-serializability, checking whether a given execution is serializable can be done in polynomial time. However, when all possible interleavings are considered, the problem becomes intractable. We address this in practice through a graph-based method, which for a given atomic block and trace, derives a smaller segment of the trace, referred to as the Trace Atomicity Segment (TAS), for further systematic exploration. We use the observed write-read pairs of events in the given trace to consider a set of events that guarantee feasibility, i.e., each interleaving of these events corresponds to some real execution of the program. We call this set of interleavings the almost view-preserving (AVP) interleavings. We show that the TAS is sufficient for finding serializability violations among all AVP interleavings. Further, the TAS enables a simple static check that can prove the absence of a violation. This check often succeeds in practice. If it fails, we perform a systematic exploration over events in the TAS, where we use dynamic partial order reduction with additional pruning to reduce the number of interleavings considered. Unlike previous efforts that are less precise, when our method reports a serializability violation, the reported interleaving is guaranteed to correspond to an actual execution of the program. We report experimental results that demonstrate the effectiveness of our method in detecting serializability violations for Java and C/C++ benchmark programs.
Operator attention based video surveillance

We introduce a surveillance video tractability adjustment system that employs a dynamic operator attention model. The tractability of the surveillance video is adjusted according to the instantaneous attention level of the operator (Fig.1). Our system has two novel major parts: (i) dynamic measurement of the operator attention levels and (ii) an online video tractability adjustment system that employs measured attention levels. We estimate the attention levels of the operators by measuring the blink rates and the saccade information of the eyes. Using well known theories from human psychology, we estimate the amount of video tractability that the operator can easily handle. We tested the proposed system on volunteer operators using both synthetic and real surveillance data. The results are very promising and we plan to extend the system with multiple operators and multiple video streams. Supplementary material is available at the project website.
Design of a Visually Guided 6 DOF Micromanipulator System for 3 D Assembly of Hybrid MEMS

The vastly different mechanics of manipulation at the microscale is a principle challenge of robotic microassembly and dictates the need for intelligent micromanipulation tools capable of compensating for these difficult to model mechanics. In this paper, we introduce a microassembly process that directly addresses this problem through an advanced six degrees-of-freedom (DOF) visual feedback mechanism and a complementary dexterous micromanipulation system. A CAD model based multi-microscope visual tracking system observes the 6 DOF motion of MEMS components in real-time (30 Hz). A 6 DOF micromanipulator was designed to complement the vision system. The novel, two-part design of the micromanipulator enables dexterous manipulation of MEMS components with large rotations (more than 90◦) and translations without occluding the microscope views. End-effector micro-tools and the distributed software architecture of the system are also introduced.
Different responses of soil respiration and its components to nitrogen addition among biomes: a meta‐analysis

Anthropogenic activities have increased nitrogen (N) deposition by threefold to fivefold over the last century, which may considerably affect soil respiration (Rs). Although numerous individual studies and a few meta‐analyses have been conducted, it remains controversial as to how N addition affects Rs and its components [i.e., autotrophic (Ra) and heterotrophic respiration (Rh)]. To reconcile the difference, we conducted a comprehensive meta‐analysis of 295 published studies to examine the responses of Rs and its components to N addition in terrestrial ecosystems. We also assessed variations in their responses in relation to ecosystem types, environmental conditions, and experimental duration (DUR). Our results show that N addition significantly increased Rs by 2.0% across all biomes but decreased by 1.44% in forests and increased by 7.84% and 12.4% in grasslands and croplands, respectively (P < 0.05). The differences may largely result from diverse responses of Ra to N addition among biomes with more stimulation of Ra in croplands and grasslands compared with no significant change in forests. Rh exhibited a similar negative response to N addition among biomes except that in croplands, tropical and boreal forests. Methods of partitioning Rs did not induce significant differences in the responses of Ra or Rh to N addition, except that Ra from root exclusion and component integration methods exhibited the opposite responses in temperate forests. The response ratios (RR) of Rs to N addition were positively correlated with mean annual temperature (MAT), with being more significant when MAT was less than 15 °C, but negatively with DUR. In addition, the responses of Rs and its components to N addition largely resulted from the changes in root and microbial biomass and soil C content as indicated by correlation analysis. The response patterns of Rs to N addition as revealed in this study can be benchmarks for future modeling and experimental studies.
Map-matching of GPS traces on high-resolution navigation networks using the Multiple Hypothesis Technique (MHT)

In recent years, data from GPS-based surveys has become increasingly important since transport modellers benefit from more accurate and reliable information about times, geographic locations, and routes. At the same time, participants’ burden is reduced substantially if the GPS data collection does not involve time-consuming questions to derive additional information. However, without respondent provided information, extensive data processing is required to derive results that can be used for analysis and model estimation. Since the first GPS survey (Wagner, 1997), one of the key postprocessing steps is the map-matching, i.e. the association of the GPS points to the links of a network, in order to establish the routes travelled by the survey participants. The algorithm proposed in this paper is an adaptation of the algorithm proposed by Marchal et al. (2005). Like the algorithm by Marchal et al. (2005), it is designed to match large-scale GPS data sets on a high-resolution navigation network in an acceptable computation time. This paper describes the implementation of the algorithm after a short overview of the existing literature. Afterwards, the performance of the algorithm is evaluated both in terms of accuracy and computational efficiency for about 36,000 car trips from 2,434 persons living in and around Zurich, Switzerland, which are mapped on the Swiss Navteq network, a high resolution navigation network covering all regions of Switzerland and containing 408,636 nodes and 882,120 unidirectional links.
Brains, Lifestyles and Cognition: Are There General Trends?

Comparative and experimental approaches to cognition in different animal taxa suggest some degree of convergent evolution. Similar cognitive trends associated with similar lifestyles (sociality, generalism, new habitats) are seen in taxa that are phylogenetically distant and possess remarkably different brains. Many cognitive measures show positive intercorrelations at the inter-individual and inter-taxon level, suggesting some degree of general intelligence. Ecological principles like the unpredictability of resources in space and time may drive different types of cognition (e.g., social and non-social) in the same direction. Taxa that rank high on comparative counts of cognition in the field are usually the ones that succeed well in experimental tests, with the exception of avian imitation. From apes to birds, fish and beetles, a few common principles appear to have influenced the evolution of brains and cognition in widely divergent taxa.
My Ever Changing Moods: Sentiment-Based Event Detection on the Cloud

Twitter is a globally used micro-blogging platformwith hundreds of millions of tweets sent every day. Manyresearchers have explored Twitter analytics across a wide rangeof areas such as topic modeling, sentiment analysis, eventdetection, as well as the application of Twitter for a variety ofdomain-specific application areas, e.g. disaster management. Onearea that has not been explored is how changes in sentiment canbe used to identify events. In this paper we present a scalableCloud-based platform for harvesting, processing, analyzing andvisualizing large-scale Twitter data. We focus especially on howchanges in sentiment can be used to identify events in givencontexts. What is novel is that the events that are detected are notdependent explicitly on the topic of any given tweet, but entirelyon the change in sentiment. This offers new capabilities for eventdetection that have hitherto not been explored. To illustrate theapproach, we present case studies related to sporting eventsidentified entirely through changing sentiment with specific focuson the 2014 FIFA World Cup of Soccer and the 2015 World Cupof Cricket.
Religious Orientation and Its Relationship to Suicidality: A Study in One of the Least Religious Countries

The relationship between religious orientation and suicidality can be more complex in samples of low religious rate. The present study was conducted in China, one of the least religious countries, with the purpose of exploring different aspects of religious orientation and their relationships to suicidality. Among a university sample of 2074 respondents, 122 respondents reported being religious and responded to our measures of religious orientation and suicidality. Extrinsic religious orientation, while being distinct from intrinsic religious orientation, could be subdivided into personally-oriented and socially-oriented dimensions to predict suicidality in our sample. Results from regression analysis showed that respondents with higher intrinsic religious orientation and lower personally-oriented extrinsic religious orientation are more likely to have lower suicidality. These findings support that intrinsic orientation is embodied with positive outcomes whereas extrinsic orientation is embodied with negative outcomes. It is noteworthy that socially-oriented extrinsic religious orientation did not predict suicidality in our sample, as it was speculated that the role of socially-oriented extrinsic religious orientation cannot function when there are few religious people to socialize with in the community.
Measuring Navigation Efficiency in the IDE

While coding, developers construct and maintain mental models of software systems to support the task at hand. Although source code is the main product of software development, the process involves navigating and inspecting entities beyond the ones that are edited by the end of a task. Developers use various user interfaces (UI) offered by the Integrated Development Environment (IDE) to navigate the complex, and often hidden, relationships between program entities. These UIs impose fixed navigation costs, in terms of the number of interactions that a developer is required to perform to reach an entity of interest. It is unclear to what extent the actual navigation effort differs from an ideal setting, and if there is any room for actual improvement. We present a preliminary empirical study, where we analyzed a corpus of IDE interaction data coming from 6 developers totaling more than 20 days of development activity. To measure the navigation efficiency, we compute a combination of different ideal settings and compare them against the observed navigation events. Our findings reveal that, on average, developers perform 1.5 to 19 times more navigation events than the ideal case. While different factors make the ideal setting unfeasible, we believe that this calls for novel approaches to support the navigation in integrated development environments.
Success breeds success or Pride goes before a fall ? 1 Teams and Individuals in Best-of-Three Contests

We study the impact of progress feedback in team-production contests, in which each team member is solely responsible for one part of the production task. Particularly, we employ a real-e¤ort laboratory experiment to examine how team members react to the feedback in team-based (best-ofthree) contests and whether it di¤ers from that of individual-based (best-ofthree) contests. Our data corroborate the theoretical prediction for teams: Neither a lead nor a lag in the rst period a¤ects a teams performance in the subsequent period. In individual contests, however, contrary to the theoretical prediction, we observe that leaders perform worse, but laggards perform better, after learning the outcome of the rst period. Our ndings o¤er new insights on team incentives in competition, and highlight the importance of incorporating contest structure into the design of feedback mechanisms in organizational management. JEL codes: D72; D74; C91
Global Grid Architecture Concept

Abstract : Military operations are becoming increasingly reliant on a communications and information infrastructure that provides seamless, interoperable connectivity between all forces, anytime and everywhere. This operational emphasis is changing the manner in which command and control (C2) systems are defined, developed and fielded. Communication systems can no longer be ,application-centric'. Instead, we must define a communications infrastructure to support a variety of applications and missions. In particular, communications systems must be interconnected to create a network accessible by all applications and users. This network-centric communications infrastructure has been coined the Global Grid. In many ways, the tremendous technology advances over the past ten years in the commercial world are making the Global Grid realizable.
Trust in a small package: minimized MRTM software implementation for mobile secure environments

In this paper we present a software-based implementation of a Mobile Remote Owner Trusted Module, using security extensions of contemporary System-On-Chip architectures. An explicit challenge are the constrained resources of such on-chip mechanisms. We expose a software architecture that minimizes the code and data size of the MRTM, applying some novel approaches proposed in recent research. Additionally, we explore alternatives within the specification to further optimize the size of MTMs. We present an analysis of specific new security issues induced by the architecture. Performance figures for an on-the-market mobile handset are provided. The results clearly indicate that a software-based MRTM is feasible on modern embedded hardware with legacy security environments.
Iterative MMSE Detection with Interference Cancellation for Up-Link HARQ Using Frequency-Domain Filtered SC-FDMA MIMO Multiplexing

SUMMARY In this paper, we propose an iterative minimum mean square error detection with interference cancellation (MMSED-IC) for frequency-domain filtered single carrier (SC)-frequency-division multipleaccess (FDMA) uplink transmission. The use of a square-root Nyquist transmit filter reduces the peak-to-average power ratio (PAPR) while increases the frequency-diversity gain. However, if carrier-frequency separation among multiple-access users is kept the same as the one used for the case of roll-off factor α=0 (i.e., brick-wall filter), then the adjacent users’ spectra will overlap and multi-user interference (MUI) occurs. The proposed MMSED-IC can sufficiently suppress the MUI from adjacent users while achieving the maximum frequency-diversity gain. We apply the proposed MMSED-IC to a packet access using filtered SC-FDMA, multi-input multi-output (MIMO) multiplexing, and hybrid automatic repeat request (HARQ). It is shown by computer simulation that filtered SC-FDMA with α = 1 can achieve higher throughput than orthogonal frequency division multiple access (OFDMA).
Enhancing the NI-9631 mobile robot abilities with multimodal communication skills

As it is well known, multimodality is a very common task in the human-robot communication. Human conversation is also considered usually multimodal, and a great amount of research is done worldwide to engine novel robotic systems embedding more and more intelligence for human gestures or speech recognition abilities enhancement. This paper presents a hardware configuration developed for multimodal communication skills implementation on the NI SbRIO-9631 prototype robot. The standard hardware structure of this mobile device has been gradually extended with voice recognition and real-time image processing units. By using the LabView graphical software toolkit, these modules integrates through specific software drivers various sensor modality including vision and speech signals analyzing. The robot endowed with the mentioned capabilities becomes a very flexible and powerful development tool for human-robot multimodal communication research and implementation. In addition to this, is also suitable for a large amount of voice signals and image processing algorithms testing, through that the robot displays intelligence and cooperativeness in its behavior.
Small Station EME at 10 and 24 GHz : GPS Locking , Doppler Correction , and JT 4

GPS frequency locking and automatic Doppler correction, together with a recently improved JT4 decoder make it possible for small portable stations (40 W and 80 cm dishes) to work the larger (3 meter dish) home stations on 10 GHz EME, even with libration spreading in excess of 100 Hz. While 24 GHz JT4F EME signals from a home station (100 W, 2.4 m dish) have been received and decoded using a 47 cm dish, a two way QSO is still a challenge.
Emotion-enhanced Mobile Chat – Conveying Emotions in Mobile Text Chat

Great part of human communication is carried out nonverbally. All this information is lost in mobile text messaging. This work describes an attempt to augment text chatting in mobile phones by adding automatically detected facial expression reactions, such as a smile, to conversations. These expressions are detected using known image processing techniques. Known related work, concerning the investigation of non-verbal communication through text messaging are considered and distinguished from the present solution. The conception and implementation of a mobile phone application with the debated feature is described and user studies are narrated. Finally, context of application, conclusions and future works are also discussed.