Miracle-dz/UniFAR-FTUs huggingface dataset:
An auto-scaling VM game approach for multi-tier application with Particle swarm optimization algorithm in Cloud computing

Cloud computing allows customers to scale their application to their needs. However, the problem of determining the amount of resources to be leased while still ensuring the quality of services and low cost is a big challenge. In this study, we focused on modeling the problem of auto-scaling virtual machines for multi-tier applications based on game theory. The strategy for auto-scaling resources is based on the Nash equilibrium and QoS parameter of the virtual machines. In the cloud computing environment, there is a need for scalability and high user responsiveness, so we design the algorithm - PSOVM to solve this problem based on PSO algorithm. Metaheuristic algorithms can find the near-optimal results in acceptable time.
An Empirical Study on Teleworking Among Slovakia's Office-Based Academics

Teleworking has become fairly popular in recent years, mostly outside the academic setting. The evolution of the information age offers the flexibility to perform work-related tasks anywhere at any time. However, very little research has been done on teleworking practices within the higher-education environment. Generally, the concept of teleworking or telecommuting is less common in Slovakia than in other countries. The introduction of teleworking in many different organisations, including universities, could provide great advantages. The success rate of the implementation of teleworking in universities is very high because of the great number of researchers. A study was conducted to explore the potential of introducing teleworking at universities in Slovakia. Drawing on existing literature related to teleworking and the outcome of an empirical study, this paper presents enlightening findings on teleworking at these organisations in Slovakia. The paper investigates the attitudes and viewpoints of potential teleworkers toward the possibility of introducing teleworking in universities. The research reveals high levels of support for teleworking practices, which are associated with high levels of work productivity and satisfaction (student satisfaction), lower levels of emotional and physical fatigue, reduced work stress, absence, frustration and overload. Overall, this critique presents insightful findings on telecommuting practices within an academic setting, which clearly signal the potential for a shift in the office culture at higher-education institutions that provide distance tuition. The study makes a significant contribution to a limited collection of empirical research on telecommuting practices at universities and also guides institutions in refining and/or redefining future teleworking strategies or programmes.
Using Intel SGX to Enforce Auditing of Running Software in Insecure Environments

In this work we propose a strategy using Intel SGX processors to guarantee the use of audited applications in insecure environments. A cloud-based toolchain allows auditors to assess if the user's application meets specifications and standards, to generate the final binaries, and to cryptographically sign them. It also generates a manifesto containing information to verify the authenticity of the audited software binaries. A SGX-based binary loader (inserted by the cloud-based toolchain during the applications building process) writes down auditing data that is encrypted and sealed by SGX functions to form reliable proofs that the original audited software is the one running. As a proof-of-concept, a Linux kernel was modified in order to cryptographically measure all processes being executed and send these results to a SGX application. An analysis was carried out to measure the performance of the altered system. On average, a system consistently running the audit increased the execution time of each process by 20 to 30%.
Extending ISO/IEC 29110 Basic Profile with Privacy-by-Design Approach: A Case Study in the Health Care Sector

Privacy related elements have become an essential part of any information system. Previous studies reveal a scarcity of research on privacy in software processes, few engineering practices and a lack of methodological support to address privacy requirements in software systems. Introducing Privacy-by-Design (PbD) into software developments is an advantageous solution to tackle privacy related concerns. This paper presents an integration of PbD goals into the ISO/IEC 29110 Basic profile for small software development organizations. The most frequently encountered privacy goals as well as privacy addressing practices from previous methodological proposals were taken into account and included in the form of tasks, work products and roles. As a practical example, we describe a real life project development of a health care system that motivated the creation of the ISO/IEC 29110 PbD extension.
Kinematic Analysis and Performance of a Planar 3RRR Parallel Robot with Kinematic Redundancy using Screw Theory

In this paper, a complete kinematic analysis of a planar 3-RRR parallel robot is presented. The position through the direct and inverse kinematics, velocities, jacobians and accelerations were developed using Screw Theory. Likewise, the workspace and singularities analysis is performed to find the smallest set of active joints for which the planar 3-RRR parallel robot remains equilibrated with respect to dexterous workspace, when failure occurs for one arbitrary active joint in a safe region. In order to accomplish this, sensitivity analysis for a classic trajectory and performance indexes for redundant planar 3-RRR parallel robot were obtained and compared with the same generation of non-redundant one, to validate the dexterity and manipulability of the mechanism. The simulation results show the maps of the dexterous workspace which the End-Effector can reach when there is redundant or non-redundant kinematics in the robot.
Intelligent Execution of Behaviors in a NAO Robot Exposed to Audiovisual Stimulus

Emotions and their intimate relationship with how humans interact with each other are currently studied as an alternative to stimulate what is called as Human-Robot Interaction (HRI). Different strategies that use emotions in robots as a central element have been developed to fulfil this goal, which has allowed the improvement of the interaction quality between a robot and a human. In this paper, different models and APIs are discussed and integrated for the processing of visual and audio stimulus in order to deliver the evoked emotions to a deterministic system and finally get the intelligent execution of behaviors in a NAO robot. The tests carried out with different case studies validated that the system responds according to the characteristics of each audiovisual stimulus and this does not have a bias towards a particular case.
Impact of Learner-Centric Discussion Forums on Learner Engagement in Skill Development MOOC

Discussion forum is an important component of Massive Open Online Courses (MOOCs). Many MOOC researchers have reported that learners do not use the discussion forum to its fullest potential. As MOOCs are evolving from being instructor-centric to learner-centric, the role played by discussion forums in driving learner engagement and completion rate is becoming evident. The Learner-Centric MOOC (LCM) model has been developed to increase learner centricity in MOOCs. Learner Experience Interaction (LxI) is one such element of the LCM model, which leverages peer learning via focused discussions. In this research, we have analyzed the impact of LxIs on a skill development MOOC, particularly the discussion forum participation, and compared it with the non-LxI version of the same MOOC. Results indicate that by adding the LxI element to a MOOC, peer learning can be leveraged for effective engagement.
IoT-based Versatile Platform for Precision Farming

This paper presents the use of IoT (Internet of Things) in agriculture such as smart or precision farming. The versatile controller is developed to monitor and control temperature and relative humidity in different ways to serve different types of use. Control methods including timer, hysteresis control, condition control, can be arranged in different sequences and periods of time. Eight multifunction output ports are available for actuators or loads. Results from real implementation are shown. Temperature and humidity in a greenhouse can be controlled in predefined ranges to suit with planting processes. Data on the cloud can be monitored in real-time on PC or mobile application.
Gain-Scheduling PID Low-Level Control for Robotic Sailboats

The sea imposes a set of restrictions that substantially influences the development of control systems for robotic sailboats. Nonlinearities produced by events such such as currents and waves are introduced that makes it more difficulty to develop effective systems to work in such environment. Towards solving the navigation problems that appear, we propose a new methodology for the control of an autonomous sailboat, which differs from others in the literature by applying a suitable PID parameters at each different maneuvering. Our methodology consists of identifying the best control (i.e. control parameters) for a given mission through simulations of the mathematical model of the sailboat. To this end, we came up with a controller, called Proportional and Integrative Gain-Scheduling control, or GS-PI, which basically consists of a table with a set of proportional and integrative parameters that best suits the control requirements of a given wind speed/direction. Results of various experiments in simulation show an improvement in the sailboat performance using the GS-PI strategy, mainly in narrow environments, when compared to classical PID approaches using a single set of control parameters during the entire navigation.
Pinset: A DSL for Extracting Datasets from Models for Data Mining-Based Quality Analysis

Data mining techniques have been successfully applied to software quality analysis and assurance, including quality of modeling artefacts. Before such techniques can be used, though, data under analysis commonly need to be formatted into two-dimensional tables. This constraint is imposed by data mining algorithms, which typically require a collection of records as input for their computations. The process of extracting data from the corresponding sources and formatting them properly can become error-prone and cumbersome. In the case of models, this process is mostly carried out through scripts written in a model management language, such as EOL or ATL. To improve this situation, we present Pinset, a domain-specific language devised for the extraction of tabular datasets from software models. Pinset offers a tailored syntax and built-in facilities for common activities in dataset extraction. For evaluation, Pinset has been used on UML class diagrams to calculate metrics that can be employed as input for several fault-prediction algorithms. The use of Pinset for this calculations led to more compact and high-level specifications when compared to equivalent scripts written in generic model management languages.
Extracting Photoplethysmographic Waveform from Bulbar Conjunctiva Video

Recently the conjunctival vascularity measurement based on image analysis has shown great potential in physiological monitoring and biometrics. However, the motion artifacts in the conjunctiva videos cause both large displacement and distinct illumination variety. In this paper, a novel approach is proposed to extract photoplethysmographic waveform from conjunctiva video. Which consists of video stabilization and dual-channel extraction to eliminate the two facets of the motion artifacts respectively. The heart rate measuring results have shown a good agreement between our method and the fingertip oximeter.
High Performance MEMS Disk Gyroscope with Force-to-Rebalance Operation Mode

A fully symmetric and high quality factor MEMS disk gyroscope is presented. The gyroscope is fabricated in a single crystal silicon $< 100 >$ SOl process with a quality factor of ~100,000. A precision digital control processing circuit is implemented on a FPGA with a force-to-rebalance (FTR) readout scheme to increase the detection bandwidth of the gyroscope. The quadrature error is suppressed using a closed-loop compensation circuits, which increases gyroscope bias stability. The in-phase error caused by damping difference is also researched and compensated. The measured gyroscope achieves a 0.18 deg/h bias stability $(1 \sigma)$ and a bandwidth of 90 Hz.
The Incidence of Psychosocial Risks in Musculoskeletal Symptoms in Workers in the Bus Manufacturing Industry: Preliminary Study

The activities related to buses assembly involve a high margin of ergonomic and psychosocial risks in the work environment that can cause pain symptoms and even generate muscle skeletal disorders (MSD) in workers. The preliminary study developed for this industrial activity aims to describe these variables and how they are associated in the generation of this issue. The investigation was carried out through the use of the Psychosocial Factors questionnaire (F-PSICO) which determined nine dimensions in the psychosocial risk factor, the musculoskeletal pain symptomatology was established with the Nordic questionnaire, while the degree of relationship between variables was made with chi-square and Odd Ratio (OR) statistical tests with a confidence level of 95%. The results show that the nine analyzed psychosocial dimensions have a very high risk among the seventeen workers involved in the study with incidence rates greater than 50%. The symptomatology of pain found in the population corresponds to discomfort in the neck, shoulders and back in lapses up to thirty days with a perception that ranges from mild to severe. Regarding to the degree of relationship of variables, there is significance $(\mathbf{p} < \mathbf{0.05})$ with the $\chi^{2}$ statistic in all dimensions, while O.R is significant in work autonomy and participation in work. The musculoskeletal symptomatology is manifested in a large percentage by ergonomic risks of work, however, psychosocial factors can accentuate this condition.
INCA: Infrastructure for Content Analysis

We present INCA (short for INfrastructure for Content Analysis), a Python module for collecting, storing, processing, and analyzing a wide variety of media content, including but not limited to news, political debates, social media, forums, and customer reviews. Using Elasticsearch as a database backend and Celery for task management, it makes automated content analysis scalable. INCA's main objective is to enable and promote an integrated workflow. INCA focuses on re-usability of data, processors, and analyses; making all steps of automated content analysis (ACA) accessible to social scientists, without requiring advanced programming skills. Here, we present the aim, implementation, and recommended workflow for INCA.
A Dark Target Method for Himawari-8/AHI Aerosol Retrieval: Application and Validation

Himawari-8 (H8), as a geostationary satellite, observing the full disk image of the earth per 10 min, is a very powerful tool to investigate atmospheric aerosol temporal variations. The advanced himawari imager (AHI) onboard H8 has several spectral bands similar with those of Moderate Resolution Imaging Spectroradiometer (MODIS). Aerosol optical depth (AOD) is thus possible to be retrieved from AHI data using the dark target (DT) method of MODIS. Based on a statistics study of infrared bands of these two satellite instruments, we found that the difference of shortwave infrared bands between AHI (<inline-formula> <tex-math notation="LaTeX">$2.3~\mu \text{m}$ </tex-math></inline-formula>) and MODIS (<inline-formula> <tex-math notation="LaTeX">$2.12~\mu \text{m}$ </tex-math></inline-formula>) in DT area can be ignored for our purpose. Meanwhile, for AHI sensor, the normalized difference vegetation index (NDVI) calculated from <inline-formula> <tex-math notation="LaTeX">$0.86~\mu \text{m}$ </tex-math></inline-formula> (instead of traditional <inline-formula> <tex-math notation="LaTeX">$1.24~\mu \text{m}$ </tex-math></inline-formula>) and <inline-formula> <tex-math notation="LaTeX">$2.3~\mu \text{m}$ </tex-math></inline-formula> can also be a good indicator of surface spectral reflectance. Therefore, first, a new NDVI of AHI sensor is proposed in this paper to improve the estimation of surface reflectance based on DT retrieval method. Then, AOD over DT area was retrieved using a lookup table strategy and tested based on AHI observation over China region from August 2015 to July 2016. All retrieved results are validated against ground-based measurements of the aerosol robotic network and the sun–sky radiometer observation network. The coincident AOD results between AHI retrieval- and ground-based network measurements show good agreements with <inline-formula> <tex-math notation="LaTeX">$R^{2}$ </tex-math></inline-formula> of 0.81. The intercomparison between AHI and MODIS DT AOD products also shows a good agreement with <inline-formula> <tex-math notation="LaTeX">$R^{2}$ </tex-math></inline-formula> of 0.92.
WiSpy: Through-Wall Movement Sensing and Person Counting Using Commodity WiFi Signals

In current era, the world is becoming more and more tetherless. A wide range of applications relies on wireless signals. In this paper, we demonstrate a system that senses movement of person behind a wall and predicts number of moving persons without instrumenting the body of target using wireless signals. This system relies on commercial off-the-shelf components and commodity WiFi signals for sensing and prediction of moving targets. In particular, we use channel state information that can incur effects induced by movement of persons. We evaluate the performance of system for a challenging scenario like 13-inch thick brick wall and our results show that system can predict up to three persons moving in a closed environment with maximum average accuracy of 96.97%.
Challenges in Building an Open-Source Flow from RTL to Bundled-Data Design

Bundled-data designs can mitigate many of the ill effects of process, voltage, and temperature (PVT) variations. This paper describes an open-source CAD flow to synthesize BD designs from RTL specifications, using perl and TCL scripts that drive commercial tools. The flow called Edge has been developed using experiences from both an open-source CPU called Plasma and a Qualcomm Technologies, Inc. industrial design.
Intrinsic Image Recovery From Remote Sensing Hyperspectral Images

In this paper, a novel reflectance model is proposed to recover intrinsic images from remote sensing hyperspectral images (HSIs). Intrinsic image recovery is a well-known challenging and underconstrained problem in computer vision, and it becomes even more severely illposed for HSIs. To reduce the uncertainties and improve the recovery accuracy, two kinds of priors are introduced: 1) shading prior which describes the geometric relation between illuminate and object surface and 2) reflectance prior based on L1-graph coding, which describes the relation between pigment density with reflectance. These priors can effectively eliminate the reflectance inhomogeneity caused by surface normal changes or pigment density variations other than material changes. Then, a noniterative optimization method is proposed to combine the shading prior and reflectance prior, with which closed-form solutions can be derived and thus avoided falling into local optimums. The experimental results demonstrate that the proposed method can efficiently improve the spectral reflectance homogeneity within a class while preserving the image boundaries; it also produces a competitive performance with the state of the art when utilizing the extracted intrinsic hyperspectral reflectance feature in the task of HSI classification.
Blockchain Privacy-Preservation in Intelligent Transportation Systems

Blockchain technology, on which digital currencies are based, is poised to be the most important disruption business innovation since the Internet. Today researchers and renowned companies have proposed the use of this technology in other areas such as voting, identity management, smart city, and others. Regarding smart city, car navigation systems is one of the main research directions that aims to streamline traffic and calculate travel routes. Existing applications such as Google Traffic or Waze are often used, but for users worried about their personal data, these systems are something of a black box. Using blockchain technology, in this paper we describe the architecture of a car navigation system in which personal data protection is a major concern.
Towards Commoditizing Simulations of System Models Using Recurrent Neural Networks

System modeling and simulation plays a crucial role in the engineering of large and complex systems from various fields, such as industrial automation or power systems. In this paper, we propose a method that can be used to easily deploy high fidelity simulations at scale, onto various target platforms. Out method is to approximate the behavior of the modeled system using a recurrent neural network. We use artificial neural networks as they easily lend themselves to high performance execution, thus avoiding the need to (manually) translate system models (typically a system of differential equations) to specialized hardware architectures. Moreover, this approach is generic in the sense that it is decoupled from typical modeling and simulation tools, such as Matlab Simulink or Dymola. This paper presents a proof-of-concept neural network architecture including the methodology for training that we used to approximate the behavior of different example systems originating from the electrical power systems domain. We present our evaluation results mainly regarding accuracy and to a certain extent performance on a GPU-based testbed. Furthermore, we detail limitations of the used approach and outline potential directions for research regarding the general applicability of our method.
An Approach towards Text to Emoticon Conversion and Vice-Versa Using NLTK and WordNet

Sentiment analysis on instant messaging and social media, is a significant and well covered area of research in Natural Language Processing. Emoticons are most popularly used in text based communication. This paper presents a new and simple approach towards text to emoticon conversion and vice-versa using input text processing with WordNet®. Proposed work is an attempt to recognize emotion from sms (short messaging service) and social media text consisting with, or, without emoticon.
TenDSuR: Tensor-Based 4D Sub-Nyquist Radar

We propose tensor-based four-dimensional sub-Nyquist radar that samples in spectral, spatial, Doppler, and temporal domains at sub-Nyquist rates while simultaneously recovering the target's direction, Doppler velocity, and range without loss of native resolutions. We formulate the radar signal model wherein the received echo samples are represented by a partial third-order tensor. We then apply compressed sensing in the tensor domain and use our tensor-orthogonal matching pursuit (OMP) and tensor completion algorithms for signal recovery. Our numerical experiments demonstrate joint estimation of all three target parameters at the same native resolutions as a conventional radar but with reduced measurements. Furthermore, tensor completion methods show enhanced performance in off-grid target recovery with respect to tensor-OMP.