Miracle-dz/UniFAR-FTUs huggingface dataset:
Mock juror perceptions of police shootings: the effects of victim race and shooting justifiability

Recent police shootings of African Americans have led citizens to question police officers’ use of force. Thus, it is important to determine whether mock jurors can distinguish between justifiable and unjustifiable police shootings—and whether their judgements depend on victim race. Media attention could lead jurors to be more punitive in cases in which an officer shoots an African American (compared to Caucasian) victim. A punitive verdict would reflect society’s opposition to such shootings, as suggested by the bandwagon effect. In a 2 (Shooting: Justified/Unjustified) x 2 (Victim’s race: African American/ Caucasian) experiment, mock jurors read a trial summary involving a fatal police shooting and indicated verdicts. Unjustifiable shootings resulted in less positive perceptions of the officer and perceptions that the shooting was less justified. When the victim was African American, participants had more positive perceptions of the victim, were more certain in a guilty verdict, and perceived the shooting as less justified. The interaction indicated that victim race affected verdicts, but only when the shooting was unjustified. Results suggest there is bias against officers who unjustifiably shoot African Americans, supporting the bandwagon effect. Implications for the role of media effects, psychology, and the legal system are discussed.
Software Repository Mining Analytics to Estimate Software Component Reliability

Encontrar e corrigir bugs em Software tem um grande custo e impacto no esforco em desenvolver Software. Os repositorios escondem informacao preditiva sobre o historico de Software que pode ser explorada recorrendo a tecnicas de analise e de machine learning. A investigacao atual de Mining Software Repositories (MSR) e capaz de classificar e listar componentes defeituosos com a granularidade ao nivel do ficheiro. Os nossos objetivos sao prever defeitos em Software com a granularidade ate ao metodo, ao minar repositorios, e melhorar as tecnicas de localizacao de falhas atuais com os resultados da previsao de defeitos. Foi implementada uma ferramenta denominada de Schwa, disponivel livremente no Github, que e capaz de analisar repositorios Git. Para Java e outras linguagens conseguimos chegar a granularidade ao nivel do metodo e ficheiro, respectivamente. Metricas como as revisoes, correccoes de bugs e autores sao analisadas e usadas para alimentar o modelo de previsao com relevância temporal. Esta tese faz as seguintes contribuicoes: um metodo para interpretar e representar diffs de patches com a granularidade ao metodo; um modelo para calcular probabilidades de defeito; uma framework para minar repositorios de Software; uma tecnica para aprender a importância das metricas analisadas; um metodo para avaliar o ganho de usar as probabilidade de defeito em localizacao de falhas.
Analysing UTAUT with trust toward mobile banking adoption in China and Pakistan: extending with the effect of power distance and uncertainty avoidance

Banking technology supports financial systems through emerging a solid connection between local population and financial intuitions. Technology acceptance studies with innovative models are considering the key research in Asian countries specifically China and Pakistan. The current study used unified theory of acceptance and use of technology (UTAUT) model with trust factor by moderating two cultural dimensions namely power distance and uncertainty avoidance. In addition, novel ideas were incorporated in determinants to investigate the national cultural effects on individuals' behavioural intentions toward mobile banking adoption in China and Pakistan. Empirical study was performed to test the proposed cross-cultural model using the data obtained from both countries. The model was analysed through multiple and moderated regression analyses using IBM SPSS software. Results proved that performance expectancy, effort expectancy, social influence and trust were important predictors of behavioural intentions to adopt m-banking in Pakistan. On the other hand, performance expectancy and trust have significant effect on individual's behavioural intentions to adopt m-banking in China. Moreover, power distance and uncertainty avoidance were significant moderators in analysing the behavioural intention to use m-banking.
Online Community College Student-Researchers Explore Mental Health Stigmas: Deeper Learning Implied

ABSTRACT The purpose of this study was to assess learning through the integration of student-research within a community college online Abnormal Psychology course, contained in a one-semester behavioral health certificate program. Seven abnormal psychology students became researchers with IRB approval, and they conducted a qualitative study about mental health stigmas interviewing participants (N = 14). The students varied – first college experience to a senior attending a four-year institution and each located hundreds of miles apart in rural Rocky Mountain communities. To develop themes, student-researchers shared literature and participants’ quotes within online discussion boards using a hermeneutic design. Findings clarified that mental health stigmas differed when considering participants’ ages, education, and family history. Among student-researchers, deeper learning was evidenced as a majority of students described a most important part of their learning as their research experience, and they applied their learning about mental health stigmas to their personal lives and career aspirations.
A Correlation between Students’ Anxiety Levels and Oral Presentation Performance in EFL Speaking Class

ABSTRACTThis research was aimed to find out whether there is a correlation between students’ anxiety level and oral presentation’s performance in EFL speaking class. The population of this research was the 4th semester students in English Education Study Program of Bengkulu University class A, B and C with 51 students randomly chosen as the sample. The design of this research was descriptive quantitative with questionnaire and presentation test as the instruments. The questionnaire of this research was FLCAS (Foreign Language Classroom Anxiety Scales) by Horwitz (1986) meanwhile the presentation test was a presentation test rubric evaluated by two raters in order to find the reliability of the test. The result of this research showed that there was a significant negative correlation between students’ anxiety level and oral presentation test score from rater 1 and rater 2. Based on the result, the strength of this correlation was moderate. On the other hand, both of the results were in negative directions. The finding also showed that most of the students had “Mildly Anxious” level of anxiety and “Basic” category from presentation test score. It can be concluded that anxiety can influenced the students’ speaking skill especially while performing a presentation in front of the class. Some factors as like fear of making mistakes, being seen by a lot of people, or being interrupted by the lecturers can increase the students’ anxiety. Keywords : Anxiety Levels, Oral Presentation, Speaking.
EURECOM participation in TrecVid VTT 2018

This paper describes the submissions of the EURECOM team to the TrecVid 2018 VTT task. We participated in the Sentence Matching subtask. Our approach is to project both descriptive texts and videos in the same vector space through a deep neural network, and to compare them using a cosine similarity. In particular, we compare several variants of sentence embeddings
Millimeter-wave frequency selective surfaces for reconfigurable antenna applications.

In this thesis, I have proposed two new types of millimeter-wave frequency selective surfaces, for shielding and reconfigurable antennas. A novel wideband FSS and a new class of reconfigurable FSS are introduced for shielding as well as mutual coupling reduction in antenna systems and beam-switching applications, respectively. Two beam-switching antennas using cantilever enabled reconfigurable FSS are designed and implemented at the 30 GHz millimeter-wave frequency band. Initially, a wideband FSS for millimeter-wave applications at the 60 GHz band is investigated. The simulated results of the wideband FSS are validated by the free-space measurement of a fabricated FSS panel. Furthermore, the proposed wideband FSS is applied as a mutual-coupling reducing wall in a MIMO system of DRAs. As a second objective, a new class of cantilever enabled FSS with frequency reconfigurability is designed. The method of fabrication and measurement of the FSS are described. For the validation of the cantilever-enabled FSS, panels of the proposed FSS are fabricated and measured. Further, these FSS panels are integrated with a conventional monopole source, to provide a beam-switching antenna in the 30 GHz frequency band. The beam-switching in the azimuth plane of the center source antenna is controlled by the switching of the FSS panels arranged around the antenna. Another antenna using a similar kind of cantilever enabled FSS is demonstrated for dualplane beam-switching application in the millimeter-wave frequency bands. The FSS panels arranged around the conventional DRA are divided both horizontally and vertically to obtain the concept of dual-plane beam-switching.Further, the prototypes of both single and dual-plane beam-switching antennas at 30 GHz are fabricated and measured to obtain the beam-switching radiation patterns.
A non-cooperative vehicle-to-vehicle trajectory-planning algorithm with consideration of driver’s characteristics

This paper presents a non-cooperative vehicle-to-vehicle trajectory-planning algorithm with consideration of the characteristics of different drivers. The driver–vehicle model considering vehicle dynamics and characteristics of the drivers is used to formulate a vehicle-to-vehicle encountering system. A non-cooperative control algorithm considering each of the driver–vehicle system as a player is employed to plan collision-free trajectories for the encountering vehicles with respective initial driving intentions. The non-cooperative problem is solved with the theory of Nash equilibrium and is ultimately converted to a standard nonlinear Model Predictive Control problem. Simulations are conducted in the scenarios of the lane-exchanging and overtaking with different initial vehicle speeds to verify the effectiveness of the proposed algorithm. Results show that the algorithm can accomplish the trajectory-planning task with consideration of both the safety requirement and the characteristics of drivers. The simulation results also show that the proposed algorithm has effectiveness for trajectory planning in different vehicle-to-vehicle encountering scenarios.
An Optimised Latent Fingerprint Matching System Using Cuckoo Search

: Biometrics is a scientific automation based on behavioural and physiological human traits to identify a person uniquely. Fingerprints are one of the eminent human psychological cues with an admiral potential for person identification. It has been widely adopted by many law enforcement agencies, forensics for criminal investigation. Amongst the three categories of fingerprints, latent fingerprints are the most intricate prints found in crime scenes and functions as dominant evidence in forensic investigations. The development of an accurate and reliable automatic latent fingerprint system is one of the pivotal issues for fingerprint researchers. This paper seeks the development of an optimal system for accurate latent fingerprint matching. The proposed system includes pre-processing of latent fingerprint image to remove noisy or unwanted information followed by minutiae extraction. The final step of proposed system includes the employment of swarm intelligence based cuckoo search algorithm to acquire optimal matching results. The performance of the system is evaluated on NIST Special Database 27 in terms of similarity score and identification rate. For the three categories of NIST dataset good, bad & ugly, the proposed system has achieved similarity score value of 94.50%, 86.22% & 84.78% and identification rates of 97.72%, 87.05% & 83.52% respectively. The proposed system outperformed in comparison with other considered concept of latent fingerprint matching techniques.
Empathy and Moral Disengagement as Predictors of Bystander Roles in School Bullying

Objective - The aims of this study were to explore bystander roles based on the Participant Role Questionnaire (PRQ) and to determine the contribution of affective empathy and moral disengagement in explaining bystander roles in bullying. Methods - The sample included 325 elementary school students aged 11-16 years old. Students’ involvement in different bystander roles was assessed by subscales adapted from the PRQ, and their individual characteristics were measured by the Emotional Empathy Scale and the adapted version of the Moral Disengagement Scale. Results - The factor analysis revealed a five-factor structure of bystander role scales (assistant, reinforcer, defender, aggressive defender and outsider). The Outsider scale did not show satisfactory reliability. Boys had significantly higher scores on assisting the bully, whereas girls had significantly higher scores on defending the victim. Reinforcing the bully increased with students’ age, while defending the victim decreased with age. Hierarchical regression analyses revealed that, after controlling for the effects of bystanders’ gender and age, emotional empathy had significant positive effects on defender and aggressive defender roles, and a significant negative effect on the reinforcer role. Moral disengagement was a significant positive predictor of assistant, reinforcer and aggressive defender roles, and a negative predictor of the defender role. Conclusion - Bystanders’ affective empathy and moral disengagement are important determinants of their behaviour in bullying situations. The validity of differentiating between the roles of assertive and aggressive defenders is confirmed.
Spectrum Allocation and Power Optimization for Demand-Side Cooperative and Cognitive Communications in Smart Grid

In this paper, we optimize power and spectrum allocation simultaneously to improve the demand-side communication quality in smart grid, to further reduce the cost of utility companies. The electricity cost is first modeled based on regulation errors caused by direct load control in the smart grid. Then the subbands are allocated to different data aggregator units according to the band confidence levels and the utility company's maximum cost. An algorithm is designed to optimize transmission power of the relay and refine the spectrum allocation to reduce the cost of utility companies. Simulation results demonstrate that the packet loss rate and cost of utility companies can be significantly reduced.
Information avoidance, selective exposure, and fake(?) news: A green market experiment

We investigate if people exploit moral wiggle room in green markets when revelation is stochastic and the revealed information is potentially erroneous. In our laboratory experiment, subjects purchase products associated with co-benefits represented as a contribution to carbon o? sets purchased by the experimenters. Information on the size of this contribution is unobservable at first, but can be actively revealed by the consumer. In seven treatments, we alter the information structure as well as the perceived revelation costs. We find strong evidence of self-serving information avoidance in treatments with simple stochastic revelation and reduced reliability of the information, representing potentially 'fake' news. The propensity to avoid information increases with the introduction of nominal information costs, which are in fact not payo? -relevant. We conclude that, generally, self-serving information avoidance can arise in green market situations if specific situational excuses are present, which could explain the demand for products associated with 'greenwashing'.
An improved matching method base on SURF

An improved matching method base on Speed Up Robert Feature(SURF) is proposed to solve the problem of of false matching in image. Firstly, the SURF keypoints and SURF feature vector are extracted. Then, the coarse matching is performed based on the traditional method of Euclidean distance. Finally, adaptive threshold of Spearman correlation coefficient is used to obtain the final matching points set. The experiments show that the proposed algorithm based on SURF and Spearman correlation coefficient can reduce false matching rate compared with original algorithm in translation, zooming, rotation, varying illumination and noise jamming.
A systems based interpretative framework for approaching exaptation and bricolage in decision making and value co-creation

Purpose – The increasing variety and variability of social and economic dynamics is pushing both researchers and practitioners in developing approaches, models, and tools for supporting decision makers in observing, interpreting, understanding and managing emergent dynamics. For contributing to the ongoing debate, the paper aims at discussing possible paths for facing the challenges of the increasing complexity through flexible decisional and behavioral approaches. Methodology/approach – The paper adopts a qualitative approach for systematizing and refreshing the interpretative role of existing literature within managerial and organizational fields. Through the interpretative contributions provided by the systems thinking, a multi-disciplinarity literature review is conducted for identifying possible constructs through which addressing the development of flexible managerial and organizational models. Findings – Managerial and organizational fields are enriched through the concepts of exaptation and bricolage as explicative domains able to provide useful indications to decision makers interested in building more flexible decisional and behavioral approaches. A possible path for managing the increasing social and economic complexity is depicting in the light of systems perspective, and a system based interpretative framework is defined for explaining actors’ reciprocal adaptation as a way for supporting value co-creation. Research implications – The paper provides possible pillars on which acting to build managerial and organizational approaches able to enhance actors’ contributions through the definition of shared processes. The concepts of exaptation and bricolage enrich previous managerial and organizational literature promoting research on value co-creation as a driver for ensuring systems’ viability in dynamic ecosystems. Practical implications – The paper calls the attention of decision makers on the need for the systems’ flexibility trough the enhancement of actors’ contributions for facing the challenges of increasing social and economic complexity. Acting on exaptation and bricolage, a possible model is provided for clarifying managerial and organizational paths for increasing the systems’ flexibility and for supporting practitioners in defining approaches able to support actors’ collaboration as a required condition for value co-creation. Originality/value – Adopting a multi-disciplinary perspective the paper enriches previous managerial and organizational literature trough the definition of concepts, processes, and approaches able to support both researchers and practitioners for better understanding and managing increasing social and economic complexity by acting on exaptation and bricolage. Thanks to the interpretative lens provided by the systems studies, a conceptual model for addressing systems’ decisions and behaviors in the light of value co-creation is proposed.
Exploring The Relationship Between Self-Regulated Learning Strategies And Computer Programming Achievement In Higher Education

This paper aims to report and discuss the findings of a research project exploring the relationship between self-regulated learning (SRL) strategies and computer programming achievement in higher education. In the project, data were collected from 66 undergraduate students who enrolled in a 13-week introductory computer programming course offered by a Hong Kong university during the academic year 2018/19. Participants were asked to complete the Motivated Strategies for Learning Questionnaire (MSLQ) to measure their use of SRL strategies. Their computer programming achievement was assessed by continuous exercises and the end-of-course examination as part of the course assessment. A quantitative correlational analysis on the questionnaire and assessment scores was conducted to explore the relationship between use of SRL strategies and computer programming achievement. The results of the project indicate that higher-order cognitive strategies, metacognitive control strategies, time and study environment strategies as well as help-seeking strategieswere positively associated with computer programming achievement. The findings suggest that students could be trained to use certain SRL strategies in order to effectively participate in computer programming activities.
ROS-based 2-D Mapping Using Non-holonomic Differential Mobile Robot

This research proposes a 2-D mapping method by a mobile robot using LIDAR sensor. The mobile robot used is a non-holonomic type with a differential driver designed to operate in an indoor area. The robot applies an occupancy grid map method that uses a probability rule to handle the uncertainties of the sensor. The quality of 2-D occupied map relies on the accuracy of distance measurements by the LIDAR sensor and the accuracy of position estimation. Position estimation is obtained by using the 2-D LIDAR odometry which is based on the laser scan matching technique. This research uses simulation model which has characteristics like real nature. All the robotic software operations are managed by the Robot Operating System (ROS) as one of the most popular software frameworks currently used by robot researchers. The experimental results show that the robot can arrange a 2-D map well which is indicated by the similarity between the reference ground truth and the resulting 2-D map.
Soft Information for Localization-of-Things

Location awareness is vital for emerging Internet-of-Things applications and opens a new era for Localization-of-Things. This paper first reviews the classical localization techniques based on single-value metrics, such as range and angle estimates, and on fixed measurement models, such as Gaussian distributions with mean equal to the true value of the metric. Then, it presents a new localization approach based on soft information (SI) extracted from intra- and inter-node measurements, as well as from contextual data. In particular, efficient techniques for learning and fusing different kinds of SI are described. Case studies are presented for two scenarios in which sensing measurements are based on: 1) noisy features and non-line-of-sight detector outputs and 2) IEEE 802.15. 4a standard. The results show that SI-based localization is highly efficient, can significantly outperform classical techniques, and provides robustness to harsh propagation conditions.