Miracle-dz/UniFAR-FTUs huggingface dataset:
Direct Instruction and Its Extension with a Community of Inquiry: A Comparison of Mental Workload, Performance and Efficiency

This paper investigates the efficiency of two instructional design conditions: a traditional design based on the direct instruction approach to learning and its extension with a collaborative activity based upon the community of inquiry approach to learning. This activity was built upon a set of textual trigger questions to elicit cognitive abilities and support knowledge formation. A total of 115 students participated in the experiments and a number of third-level computer science classes where divided in two groups. A control group of learners received the former instructional design while an experimental group also received the latter design. Subsequently, learners of each group individually answered a multiple-choice questionnaire, from which a performance measure was extracted for the evaluation of the acquired factual, conceptual and procedural knowledge. Two measures of mental workload were acquired through self-reporting questionnaires: one unidimensional and one multidimensional. These, in conjunction with the performance measure, contributed to the definition of a measure of efficiency. Evidence showed the positive impact of the added collaborative activity on efficiency.
MultiMagNet: A Non-deterministic Approach based on the Formation of Ensembles for Defending Against Adversarial Images

Deep Neural Networks have been increasingly used in decision support systems, mainly because they are the state-of-the-art algorithms for solving challenging tasks, such as image recognition and classification. However, recent studies have shown these learning models are vulnerable to adversarial attacks, i.e. attacks conducted with images maliciously modified by an algorithm to induce misclassification. Several works have proposed methods for defending against adversarial images, however these defenses have shown to be inefficient, since they have facilitated the understanding of their internal operation by attackers. Thus, this paper proposes a defense called MultiMagNet, which randomly incorporates at runtime multiple defense components, in an attempt to introduce an expanded form of non-deterministic behavior so as to hinder evasions by adversarial attacks. Experiments performed on MNIST and CIFAR-10 datasets prove that MultiMagNet can protect classification models from adversarial images generated by the main existing attacks algorithms.
A Systematic Review on the Use of Educational Technologies for Medical Education

Educational technologies have been increasingly used in medical education to promote innovative pedagogical strategies in classroom. However, the medical scientific community still lacks a comprehensive understanding on how educational technologies are used in medical education. The objective of this work is to explore what types of technologies are employed in medical education, aiming to identify in which domains they have been applied and the reported evidence of using educational technologies in medical education. We conducted a Systematic Literature Review (SLR) to identify the primary studies on the use of educational technologies in medical education, following a pre-defined review protocol. One hundred sixty-eight papers were selected, covering nine types of education technologies, which were applied in more than 40 medical domains. Moreover, our SLR results also show that most of the papers included in this SLR reported positive evidence about the benefits of using these technologies in medical domain.
Cadenza: The Evolution of a Digital Music Education Tool

This paper describes the evolution of Cadenza, a digital music tool designed to inspire and assist students with practising between music lessons. Cadenza was developed using an evidence-based research and design model, supported by funding for both the research and software design. The focus of the present case study is on how Cadenza has continued to thrive after the research funding period ended, through a community-based not-for-profit organizational structure housed within the auspices of the host research institution. In an era where technology transfer has become a goal for many post-secondary institutions, this case study illuminates both the advantages and pitfalls of creating a start-up enterprise under the umbrella of an established university.
Gradual Machine Learning for Aspect-level Sentiment Analysis

The state-of-the-art solutions for Aspect-Level Sentiment Analysis (ALSA) were built on a variety of deep neural networks (DNN), whose efficacy depends on large amounts of accurately labeled training data. Unfortunately, high-quality labeled training data usually require expensive manual work, and may thus not be readily available in real scenarios. In this paper, we propose a novel solution for ALSA based on the recently proposed paradigm of gradual machine learning, which can enable effective machine labeling without the requirement for manual labeling effort. It begins with some easy instances in an ALSA task, which can be automatically labeled by the machine with high accuracy, and then gradually labels the more challenging instances by iterative factor graph inference. In the process of gradual machine learning, the hard instances are gradually labeled in small stages based on the estimated evidential certainty provided by the labeled easier instances. Our extensive experiments on the benchmark datasets have shown that the performance of the proposed solution is considerably better than its unsupervised alternatives, and also highly competitive compared to the state-of-the-art supervised DNN techniques.
Healthy, Active and Connected: towards Designing an Age-Friendly Digital Neighborhood Platform

Due to declining fertility rates and rising life expectancy, the world’s population is ageing at an unprecedented pace. This demographic change is expected to exert pressure on social security as well as healthcare systems and poses the risk of social exclusion of the elderly. As urban areas are home to the majority of the global elderly population, they are disproportionately affected by this development. Cities have begun responding with strategies ranging from policy and regulation reform to investments in innovative healthcare technologies with the goal of becoming “age-friendly”. Enabling the elderly to live a socially active, healthy and self-determined lifestyle past retirement are among the prime objectives for alleviating the challenges of an ageing society. With increasing urbanization, human, technological and infrastructural resources of urban contexts or neighborhoods have presented themselves as important determinants of elderly well-being. We propose that an age-friendly digital neighborhood platform can activate and leverage these resources to the benefit of the elderly population, contributing to the mitigation of the challenges of an ageing society. Following a design science research approach, we develop design principles for such an age-friendly digital neighborhood platform and evaluate a prototypical instantiation in two case neighborhoods in a German metropolitan area.
Omnidirectional Sensing for Escaping Local Minimum on Potential Field Mobile Robot Path Planning in Corridors Environment

Mobile robot path planning using artificial potential field approach is popular for its computational simplicity. However, the conventional artificial field potential approach possesses weakness when the robot is deployed into corridors environment. The approach makes the robot easily trapped in local minimum caused by long obstacles presence, thus makes the robot unable to get to the goal point. In this paper, a method for escaping local minimum in corridors scenario is proposed. The proposed method utilizes the omnidirectional sensor, which has the ability to sense 360 degrees field of view, to get information on obstacles which are surrounding the robot. This information is used for the robot to put a feasible temporary goal to guide the robot to detour the trap. Numerical experiment verified that the proposed method successfully generates a safe path and is able to escape the local minimum trap in corridors environment.
Clinical Workflows based on OpenEHR using BPM

The integration of clinical workflows in electronic health records systems has been problematic due to the complex nature of clinical processes. For that reason, many health institutions have opted to maintain a few clinical workflows on paper, which has been compromising the quality and efficiency of several provided services. The purpose of this study is to investigate if the OpenEHR model can be applied in the configuration and management of clinical workflows using Business Process Modelling (BPM), with the focus on clinical forms based on OpenEHR archetypes and having has background the institution Centro Hospitalar do Porto (CHP). The need to review the workflows is pertinent due to the lack of integration of clinical workflows on their Electronic Health Records system. To analyse this possibility, a prototype was created containing: i) a BPM tool to configure and manage the clinical workflows; and ii) a web application to execute them and call the external clinical forms. The obtained results proved that the use of a BPM tool to configure clinical workflows allows the interoperability and flexibility of the prototype, which helps to improve the quality and efficiency of the clinical practice.
Fabrication and Comparison of Guided Two-Beam and Four-Beam Piezoelectric Energy Harvester For Low-Frequency Operation

This paper deals with design, fabrication, characterization, and testing of Piezoelectric Vibration Energy Harvester (P-VEH) based on guided two-beam and four-beam-structures proposed for the applications in the low-frequency domain. Each cantilever beam has been deposited with a <inline-formula> <tex-math notation="LaTeX">$2.5~\mu \text{m}$ </tex-math></inline-formula> thick c-axis oriented ZnO film with a passivation layer of <inline-formula> <tex-math notation="LaTeX">$0.5~\mu \text{m}$ </tex-math></inline-formula> thick PECVD SiO<sub>2</sub> on both the sides to avoid the environmental deterioration of ZnO. Al electrodes (top one, as a split electrode) on both sides of the ZnO/SiO<sub>2</sub> structure have been incorporated to capture the electric potentials generated. The displacement and stress for both the designs have been analyzed and reported. A heavy pyramidal shaped seismic mass has been carved out of single crystal Si substrate at the free ends of the cantilevers, thereby providing a higher electric potential. The beam thickness is well controlled by an optimized beam thinning process done through deep reactive ion etching (DRIE). The resonance frequencies using Laser Doppler Vibrometer (LDV), have been measured at 466 Hz and 515 Hz for two-beam and four-beam devices, respectively. In the low-frequency domain (10–1000 Hz), sensitivity analysis has been done experimentally. The two-beam and four-beam devices exhibit net sensitivities of 2.2784 mV/m/s<sup>2</sup> and 4.09272 mV/m/s<sup>2</sup>, respectively. [2019-0022]
Time-Varying Formation Control For Second-Order Discrete-Time Multi- Agent Systems With Switching Topologies and Nonuniform Communication Delays

Time-varying formation control and velocity tracking problems for second-order discrete-time multi-agent systems with switching jointly-connected topologies and nonuniform communication delays are investigated. A local information-based distributed protocol is designed by utilizing the instantaneous states of the agent itself and the delayed states of its neighbors. Through model transformation and stability analysis, an explicit mathematical description of a feasible time-varying formation set is proposed. Necessary and sufficient conditions for the systems with switching topologies and nonuniform communication delays to achieve the feasible time-varying formation are obtained. The coupling constraints on the gain parameters and sampling period are proposed, so as to guide the design of parameters in the protocol. We include the effects of velocity tracking error damping gain in the protocol and derive milder conditions which allow for not only bounded nonuniform communication delays but also for dynamically switching directed graphs that are jointly connected. The numerical examples are further presented to illustrate the validity and effectiveness of the obtained results.
A Picture is Worth More than a Thousand Purchases: Designing an Image-based Fashion Curation System

Online retailing has been experiencing explosive growth for years and is dramatically reshaping the way people shop. Given the lack of personal interactions fashion retailers have to establish compelling service and information offerings to sustain this growth trajectory. A recent manifestation of this is the emergence of shopping curation as a service. For this purpose, experts manually craft individual outfits based on customer information from questionnaires. For the retailers as well as for the customers, this process entails severe weaknesses, particularly with regard to immediateness, scalability, and perceived financial risks. To overcome these limitations, we present an artificial fashion curation system for individual outfit recommendations that leverages deep learning techniques and unstructured data from social media and fashion blogs. Here, we lay out the artifact design and provide a comprehensive evaluation strategy to assess the system’s utility.
A field Experiment for Understanding the Unintended Impact of Internet Monitoring on Employees: Policy Satisfaction, Organizational Citizenship behaviour and Work Motivation

Internet monitoring is widely deployed in organizations as an attempt to regulate employees’ cyberloafing behaviour, which is defined as employees’ usage of Internet for non-work-related purposes during work. Although previous studies have examined the effectiveness of Internet monitoring in regulating employees’ cyberloafing, the impact of Internet monitoring on employees’ perceptions or behaviours other than cyberloafing has not been investigated. As the first step to address this research gap, we conduct a field experiment to study the impact of Internet monitoring on employees’ policy satisfaction, organizational citizenship behaviour (OCB) and work motivation. We found that Internet monitoring decreased employees’ policy satisfaction and OCB. We also found that Internet monitoring decreased employees’ intrinsic work motivation, although it slightly increased employees’ extrinsic work motivation. Our study contributes to the literature by examining the unintended impact of Internet monitoring on employees. It also has implications for organizations to make appropriate decisions regarding whether to implement Internet monitoring.
Aging Investigation of Digital Circuit using In-Situ Monitor

Handling process, voltage, temperature and aging variations have become an important challenge for advanced technology nodes to guarantee good performance. It is important to capture PVTA variations very accurately, in that context in-situ monitor captures both local and global variations accurately as they are placed inside the design at the end of critical paths. This paper presents the experimental results and analysis of aging with the help of in-situ monitor across different dies. Critical path ranking and slack modification due to aging effect and different supply voltage are analyzed. Compensation of aging through body-bias applied on PMOS and NMOS is discussed.
Optimization of Gaps Resolution Strategy in Implementation of ERP Systems

Enterprise Resources Planning (ERP) systems are packaged applications developed by their vendors. Their functionality is not specifically tailored to particular companies implementing these systems. Differences between provided functionality and company’s needs are identified using fit-gap analysis. The paper develops a novel optimization model for fit-gap analysis. The model yields an optimal gaps resolution strategy, which defines type and timing of customizations made to resolve the gaps and decisions are made with respect to the vendor’s software evolution roadmap. Thus, the model highlights trade-offs between inhouse customization and adoption of standard features yet to be released. The optimization results are analysed depending on the company’s customization preferences and an application example is also provided. The model allows for understanding and evaluation of relationships between the company implementing the ERP system and the vendor of the ERP system.
Facilitating Entrepreneurial Experiences through a Software Engineering Project Course

Skills and competencies in entrepreneurship, such as the ability to generate innovative ideas and the courage to engage with stakeholders and society, have gained importance in engineering curricula. In this case study paper, we report on how we have integrated entrepreneurial experiences into a software engineering project course and made the creation of value and reflection on the application of a structured process the heart and soul of the course. Based on current research on entrepreneurship education as well as the definition of entrepreneurial competencies used by the European Union, we show how the learning objectives, the teaching moments, the integration of external stakeholders, and the assessment work together to create an entrepreneurial environment in which students are encouraged and rewarded to work in an entrepreneurial way. Based on data from reflection reports, course evaluations, and interviews we discuss the pros and cons of our approach and how the student perception and expectations often run counter to the motivations of the course design. We thus contribute guidance for other teachers based on our own experiences in relation to the findings of our peers.
Towards Sampling and Simulation-Based Analysis of Featured Weighted Automata

We consider the problem of model checking Variability-Intensive Systems (VIS) against non-functional requirements. These requirements are typically expressed as an optimization problem over quality attributes of interest, whose value is determined by the executions of the system. Identifying the optimal variant can be hard due to the state-explosion problem inherent to model checking the exponentially growing number of variants in large VIS. In this paper, we lay the foundations for the application of smart sampling and statistical model checking to solve this problem faster. We design a simple method that samples variants and executions in a uniform manner from a featured weighted automaton and that assesses which of the sampled variants/executions are optimal. We implemented our approach on top of ProVeLines, a tool suite for model-checking VIS and carried out a preliminary evaluation on an industrial embedded system design case study. Our results show that sampling-based approaches indeed holds the potential to improve scalability but should be supported by better heuristics to be competitive.
Wideband Low-Profile Differential-Fed Patch Antennas With an Embedded SIW Cavity Under Dual-Mode Resonance

In this communication, a single-layer differentially fed microstrip patch antenna (MPA) with wide bandwidth and low profile is proposed. The proposed antenna is composed of a patch radiator and a substrate integrated waveguide (SIW) cavity. In this work, a square SIW cavity is concentrically embedded within a square patch radiator. Here, the two dominant resonant modes in the radiative patch resonator and nonradiative SIW cavity, namely, TM10 and TE21, are both employed to achieve a wide impedance bandwidth under dual resonances. At first, the resonant properties of these two modes are investigated based on the cavity model theory. Then, their resonant frequencies are extensively discussed, aiming at reallocation of these two modes in proximity to each other by properly selecting the geometrical dimensions of the square patch resonator and SIW cavity. After that, the spacing between adjacent metallic pins of the SIW cavity is studied to reveal its influence on both radiation and bandwidth properties. As such, proper spacing is selected toward stable radiation gain over the whole band of operation. Finally, the feeding positions of the MPA are studied to determine the input impedance of the antenna toward wide impedance matching in a wideband. To verify the predicted results, a prototype antenna is fabricated and measured. The simulated and measured results are found in good agreement with each other and both of them illustrate that the proposed antenna achieves a wide bandwidth of about 11.43% at a center frequency of 3.5 GHz and a stable gain in the range of 8.09 to 9.04 dBi within the whole band. Moreover, this antenna is a low-profile structure with a height of 0.037 free-space wavelength.
The Influence of Social Media filter bubbles and echo Chambers on IT Identity Construction

Social media sites are extending social structures from physical to virtual environments. The leading social media platforms use customized algorithms to improve their users experience online. The filter algorithms analyze restricted to individuals online habits. Thus, ignoring more subjective personality traits. Moreover, social media technological features allow individuals to receive constant feedback loops that influence their self-concept and reflects on their identity construction while online. The understanding of how a dynamic Information Technology (IT) artifact — created and continuously modified by interpersonal relationships — influence individuals identity, demands a multidisciplinary approach. Based on a broad bibliographic review, this research-in-progress paper proposes a conceptual model encompassing the cognitive and motivational processes involved during the use of social media to investigate the influence of filter bubbles and echo chambers on Information Technology (IT) Identity construction. In the next phase of research, we intend — throughout a mixmethods approach — investigate empirically the relations presented in the conceptual model. Given the interconnected and embedded nature of social media in today’s world, we believe that findings from this research will be of interest to Information System(IS) researchers and practitioners engaged in the study of the relationship between social media and identity.
How to Nudge Pro-Environmental behaviour: an Experimental Study

Last year, human mankind exhausted the planet’s resources for the year as early as never before by consuming food, water, or clean air beyond the nature’s sustainable means. To prevent further environmental damages, understanding and promoting individual pro-environmental behaviour (PEB) is crucial. However, motivating individual PEB is considered difficult as it is often costlier and more burdensome than non-eco-friendly behaviour. One promising recent approach is the concept of ‘digital nudging’, which examines the effectiveness of user-interface elements to guide people’s behaviour in digital choice environments. Prior research has focused on nudging PEB through anchoring and adjustment, overlooking the import nudging mechanisms of priming and status quo bias. To test nudges’ direct and interaction effects on motivating individual PEB, we conducted a randomized, laboratory experiment with 120 participants. We find that groups nudged with a status quo bias acted more pro-environmentally. Surprisingly, we find no differences in PEB between groups nudged with priming and the control group, indicating priming’s ineffectiveness in motivating PEB. Our study contributes to research on Green IS and digital nudging and offers directions for future research.