Miracle-dz/UniFAR-FTUs huggingface dataset:
Multi-Objective Scheduling of CHP-Based Microgrids with Cooperation of Thermal and Electrical Storage Units in Restructured Environment

Renewable energy sources are counted as dominant elements of the future distribution grids. The integration of renewable resources such as wind, solar along with the volatility of instantaneous demand features uncertainty in the operation of these grids. By increasing in the pervasiveness of demand-side distributed generation along with utility-scale energy storage technologies, the concept of microgrid has grown bold more than ever. The optimal operation of microgrid has vital importance to exploit the resources efficiently and optimally. The energy management system of the microgrid must regard electric loads and thermal loads at the same time while scheduling for the microgrid. The commitment of thermal units and integration of renewable sources highly depends on how the operator deals with these uncertain units and also depends on its adopted supportive policies to increase their penetration. In this study, a microgrid scheme is designed where combined heat and power (CHP) unit, wind unit, solar unit, thermal storage facility, micro-turbine, and fuel cell unit supply the loads. The scheduling is conducted for a 24-hour period. The correlation between electricity and heat in CHP unit is supposed to be polygonal that is the most comprehensive paradigm in the modeling of these units so far. The scheduling problem is classified as a mixed-integer non-linear programming (MINLP) type. The non-linearity of the problem is caused due to the fitness function of the CHP unit. In order to solve and optimize the problem, the Crow search algorithm (CSA) is employed which is simulated by MATLAB software.
Exploring the Capabilities of Harmony for Upper-Limb Stroke Therapy

Harmony is a bimanual upper-limb exoskeleton designed for post-stroke rehabilitation. It moves the subject’s shoulders and arms through their entire ranges of motion while maintaining natural coordination, is capable of force/torque control of each joint, and is equipped with sensors to measure motions and interaction forces. With these capabilities Harmony has the potential to assess motor function and create individualized therapy regimens. As a first step, five stroke survivors underwent rehabilitation sessions practicing multijoint movements with the device. Each participant performed a total of 1130 motions over seven hours of therapy with no adverse effects reported by participants or the attending therapist, supporting the suitability of Harmony for use in a clinical setting. Donning and doffing time averaged 3.5 minutes and decreased with therapist experience. Reported levels of stress, anxiety, and pain indicate that the Harmony safely assisted in the completion of the trained movements and has great potential to motivate and engage patients. We developed a novel methodology for assessing coordination capability and results from the study indicate that Harmony can enable therapists to identify neuromuscular weakness and maladaptive coordination patterns and develop targeted interventions to address these aspects of upper-limb function. The results suggest Harmony’s feasibility and show promising improvements, motivating future study to gain statistical support.
Aggressive Driving Detection Using Deep Learning-based Time Series Classification

Driver aggressiveness is a major cause of traffic accidents. Aggressive driving detection is an important application in the field of intelligent transportation systems (ITS). Developing systems capable of automatically detecting aggressive driving behavior should help improve traffic safety. In this paper we propose a novel solution to the problem of drivers' behavior classification based on a Long Short Term Memory Fully Convolutional Network (LTSM-FCN) to detect if a driving session involves aggressive behavior. We formulate the problem as a time series classification and test the validity of our approach on the UAH-DriveSet, a public dataset that provides a large amount of naturalistic driving data obtained from smartphones via a driving monitoring application. The proposed solution is compared to other deep learning and classical machine learning models for different processing time window sizes. It is shown that the proposed system outperforms the other methods in terms of the F-measure score, which reaches 95.88% for a 5 minutes window length.
Bio-inspired design and validation of the Efficient Lockable Spring Ankle (ELSA) prosthesis

Over the last decade, active lower-limb prostheses demonstrated their ability to restore a physiological gait for transfemoral amputees by supplying the required positive energy balance during daily life locomotion activities. However, the added-value of such devices is significantly impacted by their limited energetic autonomy, excessive weight and cost, thus preventing their full appropriation by the users. There is thus a strong incentive to produce active yet affordable, lightweight and energy efficient devices. To address these issues, we developed the ELSA (Efficient Lockable Spring Ankle) prosthesis embedding both a lockable parallel spring and a series elastic actuator, tailored to the walking dynamics of a sound ankle. The first contribution of this paper concerns the developement of a bio-inspired, lightweight and stiffness-adjustable parallel spring, comprising an energy efficient ratchet and pawl mechanism with servo actuation. The second contribution is the addition of a complementary rope-driven series elastic actuator to generate the active push-off. The system produces a sound ankle torque pattern during flat ground walking. Up to 50% of the peak torque is generated passively at a negligible energetic cost (0.1 J/stride). By design, the total system is lightweight (1.2kg) and low cost.
Dynamic Time Warping: Itakura vs Sakoe-Chiba

In the domain of time-series classification, one simple but persistently successful method is the 1-nearest neighbour (1NN) classifier coupled with an elastic distance measure such as Dynamic Time Warping (DTW). In this paper we evaluate the performance of DTW when constrained using the Itakura parallelogram, and compare it with the more commonly used Sakoe-Chiba band, as well as with the unconstrained DTW. Results show that although the Itakura parallelogram is generally inferior to the Sakoe-Chiba band, it is still superior to unconstrained DTW. Furthermore, on individual data sets the Itakura parallelogram can produce superior results, warranting further investigation into the merits of its use with DTW and other elastic distance measures for time-series classification.
Indoor Position Algorithm Based on the Fusion of Wifi and Image

In this paper, an image and WiFi multi-mode fusion localization method is proposed. WiFi fingerprint 10-calization is one of the most commonly used methods at present, but WiFi fingerprint localization has the phenomena of multipath and non-line-of-sight, signal fluctuation, scattering and so on, which leads to the unstable positioning effect. In addition, the image uses feature matching to determine the user’s location, which is less affected by the environment, more stable and lower cost. Taking advantage of the advantages of the two algorithms, a new fusion location estimation algorithm is proposed. In the offline phase, WiFi fingerprint and image are collected, fingerprint database is established, and the collected images are split and matched using AlexNet to determine the overall range. In the online stage, fingerprint location matching is carried out in the area through the fusion WiFi. After experiments, the results show that our method can effectively reduce the fluctuation of WiFi fingerprint positioning and improve the positioning accuracy; it can be widely used to provide indoor positioning services for people.
Step-Function Approach for E-Learning Personalization

Personalization is an alternative to improve the learning process for an e-Learning environment. It is a useful strategy to adjust the student' needs based on their characteristics to make learning more effectively. In this study, we propose the step-function approach for personalization in e-learning. It provides the students with adopting the knowledge-ability factor (Novice, Average, or Good category) that matches with their learning materials levels (Level1, Level2, or Level3). The approach implemented into an e-learning which called SCELE-PDE and used as the experimental group in two stages with different scenarios. In the first, without a step-function approach, but the SCELE-PDE can identify an initial of student's ability to knowledge category. The second stage has used the approach to providing students with personalization in e-Learning to adapt learning material based on a knowledge category. As a result, the step-function approach has successfully to improve the student performance in the learning process during the course. Thus, the approach has shown an increase in the level of students’ knowledge. So, it can be used as a guide when designing an e-learning personalization for students to enhance learning and achievement.
Training teachers for English Medium Instruction: lessons from research on second language listening comprehension

CLIL (Content and Language Integrated Learning) and EMI (English Medium Instruction) practices have outpaced theory and teacher training. There is a need to provide answers to some of the key issues such as the language requirements. This paper aims to show that knowledge from English for Specific Purposes and English for Academic Purposes, fields which have provided effective teaching practices and materials, could now be used in CLIL/EMI. The paper focuses on two of these. First, the issues related to second language academic listening comprehension and, secondly, the findings from research on it and their implications for student / lecturer training and materials design. These implications and suggestions are summarized. The paper concludes providing some language learning resources originally targeted to students but which could become tools for (self) training of those teachers who need to update their language skills for CLIL.
Natural Myocontrol in a Realistic Setting: a Comparison Between Static and Dynamic Data Acquisition

Natural myocontrol employs pattern recognition to allow users to control a robotic limb intuitively using their own voluntary muscular activations. The reliability of myocontrol strongly depends on the signals initially collected from the users, which must appropriately capture the variability encountered later on during operation. Since myoelectric signals can vary based on the position and orientation of the limb, it has become best practice to gather data in multiple body postures. We hereby concentrate on this acquisition protocol and investigate the relative merits of collecting data either statically or dynamically. In the static case, data for a desired hand configuration is collected while the users keep their hand still in certain positions, whereas in the dynamic case, data is collected while users move their limbs, passing through the required positions with a roughly constant velocity.Fourteen able-bodied subjects were asked to naturally control two dexterous hand prostheses mounted on splints, performing a set of complex, realistic bimanual activities of daily living. We could not find any significant difference between the protocols in terms of the total execution times, although the dynamic data acquisition was faster and less tiring. This would indicate that dynamic data acquisition should be preferred over the static one.
Reliable, Fast and Reusable Interfacing of High-Frequency Signals to Disposable Lab-on-a-Chip Devices

This work presents a novel manner of interconnecting high-frequency signals from laboratory instruments to a disposable lab-on-a-chip chip with an interconnect box (ICB). The ICB can connect with a standard coaxial connector to microwave lab equipment and uses a spring levered interface with elastomer conductive pins to connect to the disposable chip. With the spring-system, a new microwave-microfluidic chip can be mounted reliably on the setup in a couple of seconds. The high-frequency interface within the ICB is protected from the environment by an enclosure having a single slit for mounting the chip. The gold-on-quartz technology and casting of polydimethylsiloxane was used to develop an interdigital capacitor (IDC) for microwave sensing and heating for continuous flow microfluidics. Different isopropyl alcohol-water mixtures were flushed through the channel over the IDC and sensed based on the measured reflection coefficient measurements of the interconnected IDC on quartz. Using calibration techniques, the dielectric properties were extracted and good agreement with values in literature was obtained. At last, a deionized water sample of $2\mu \mathbf{L}$ was heated with heating rates of 50° C/s.
A Neuromuscular-Model Based Control Strategy to Minimize Muscle Effort in Assistive Exoskeletons

In literature, much attention has been devoted to the design of control strategies of exoskeletons for assistive purposes. While several control schemes were presented, their performance still has limitations in minimizing muscle effort. According to this principle, we propose a novel approach to solve the problem of generating an assistive torque that minimizes muscle activation under stability guarantees. First, we perform a linear observability and controllability analysis of the human neuromuscular dynamic system. Based on the states that can be regulated with the available measurements and taking advantage of knowledge of the muscle model, we then solve an LQR problem in which a weighted sum of muscle activation and actuation torque is minimized to systematically synthesize a controller for an assistive exoskeleton.We evaluate the performance of the developed controller with a realistic non-linear human neuromusculoskeletal model. Simulation results show better performance in comparison with a well known controller in the literature, in the sense of closed loop system stability and regulation to zero of muscle effort.
User-centered Design and Evaluation of Physical Interfaces for an Exoskeleton for Paraplegic Users

Over the last decade, the use of wearable exoskeletons for human locomotion assistance has become more feasible. The VariLeg powered lower limb robotic exoskeleton is an example of such systems, potentially enabling paraplegic users to perform upright activities of daily living. The acceptance of this type of robotic assistive technologies is often still affected by limited usability, in particular regarding the physical interface between the exoskeleton and the user (here referred to as pilot). In this study, we proposed and evaluated a novel pilot attachment system (PAS), which was designed based on user-centered design with experienced paraplegic exoskeleton users. Subjective assessments to compare usability aspects of the initial and the redesigned physical interfaces were conducted with two paraplegic and five healthy pilots. The redesigned PAS showed a 45% increase in the system usability scale (SUS), normalized to the PAS of a commercial exoskeleton assessed in the same manner. Pain rating scales assessed with healthy pilots indicated an increased comfort using the redesigned PAS while performing several activities of daily living. Overall, an improvement in usability relative to the initial PAS was achieved through intensified user evaluation and individual needs assessments. Hence, a user-centered design of physical body-machine interfaces has the potential to positively influence the usability and acceptance of lower limb exoskeletons for paraplegic users.
Techno-Economic Feasibility Analysis of Grid-Tied PV-Wind Hybrid System to Meet a Typical Household Demand: Case Study - Amman, Jordan

In an attempt to hinder the advancement in climate change impacts, concerned people are motivated to invest in renewable energy systems. Follows, the proliferation in energy demand, especially in residential sector, is another concern because fossil-fuel sources are depleting as time progresses. Fortunately, renewable energy resources in some countries are available in abundance and can cover a large portion of residential sector's energy demand. Jordan, like many other parts of the world, enjoys a great potential of renewable energy resources. To tackle the aforementioned issues, in this study we aim at conducting a techno-economic feasibility assessment for an on-grid PV-Wind hybrid system in order to cover a typical household annual energy demand in Amman, Jordan. The analysis show that there is a great potential of supplying the household energy demand in most of the months annually and the system is able to generate excess energy that can be exported to the national grid, which generates significant project revenues. Furthermore, the hybrid system provides a price of energy (LCOE) lower than the national grid tariff. Consequently, this study contributes greatly to the country plans of reducing the reliance on imported fossil fuels for meeting its domestic energy demands.
A systematic literature review to identify human related challenges in globally distributed agile software development: towards a hypothetical model for scaling agile methodologies

Currently, software organizations are implementing agile methodologies in global software development (GSD) because of low development cost, schedule and high quality product. However, GSD project is complex undertaken because of it distributed dimensions especially when the agile methodologies are concerned. The objective of this study is to identify the human related factors that can negatively influence agile practices in GSD organizations, and proposed a hypothetical model of the identified challenges related to the scaling agile methodologies. A Systematic Literature Review (SLR) method was used to identify the challenges. In the findings, a total of eleven challenges were identified using SLR. This study also reported the Critical Challenges (CChs) for scaling agile methodologies using a criterion of the challenges having a frequency $\ge 50$%. Findings reported the six out of eleven challenges as critical challenges in scaling agile methods. Based on the identified challenges, a hypothetical model was presented that is highlighted a relationship between identified challenges and the implementation of agile methodologies in GSD environment.
Real time computation of Centroidal Momentum while human walking in the lower limbs rehabilitation exoskeleton: Preliminary trials

In EU-funded BALANCE project, developing a stability index which can be employed to estimate actual state of balance of both healthy and neurologically impaired humans’ walking in exoskeleton was one of scientific tasks. In the task, Centroidal Momentum (CM), referring to linear and angular momenta at Center of Mass (CoM), has raised as a potential index for such purpose. While our past studies have presented analysis results of CM in offline and online (real time) manners for walking of healthy human and stroke patients, in this study, we present real time computation of CM in exoskeleton-supported walking, specifically with healthy subjects. Experimental setup consists of LOPES II, a treadmill-based robotic gait training exoskeleton for lower limbs rehabilitation developed by Twente University, and commercially available IMUs (Inertial Measurement Units)-based full body motion capture suits from Xsens. CM was computed and demonstrated in two walking conditions: unperturbed walking and walking with unexpected pelvic perturbations in lateral direction. While electromagnetic fields (EMF) from LOPES II exoskeleton affected signals of IMUs in the motion capture suit, the results show the potential applicability of the CM as a sort of stability index for human walking in the exoskeleton.
Reliable Image Notifications for Smart Home Security with MQTT

Internet of Things (IoT) applications utilize low-powered battery operated devices and reliable event notifications depend on low-power messages from the sensors node to the server and vice versa over bandwidth constrained unreliable channels. Publish/subscribe communications protocols play an important part in such low-powered device communications with MQTT protocol being most prevalent for such deployments. These protocols have enabled IoT applications such as smart home, fleet management, oil pipelines and space exploration that heavily depend on reliable communications. This paper investigates utilization of MQTT protocol for a smart home security system. A Raspberry Pi implementation detects an intrusion event using a passive infrared sensor triggering an image capture which is then communicated to the subscribed client for countermeasures. Results for power consumption and data transfer are provided that help understand the behaviour with different service qualities.
Awareness and source of AIDS-related prevention knowledge among medical university students of Guizhou province, China

Objective: To clarify the awareness and source of AIDS knowledge among college students of medical university of Guizhou province, China, so as to provide some basic evidences for implementing education of AIDS control and prevention . Methods: A stratified cluster sampling survey was conducted. Self-designed questionnaires were used to investigate university students, Epidata 3.0 and SPSS 8.0 were used to analyze data.Results: The awareness rate of AIDS through blood transmission and mother-to-child transmission was over 90%, the awareness rate of sexual transmission was just about 80%, and the awareness rate of non- transmission route “mosquito bites will not spread AIDS” was only 53.3%. The awareness rate of AIDS transmission and treatment among medical students was higher than that of non-medical students. The Internet, propaganda materials, newspapers and magazines, and school classes were the main ways for university students to acquire AIDS knowledge. Some students hope to acquire knowledge from classmates and friends, it was found that the proportion of medical students receiving AIDS knowledge from school classes was significantly higher than that of non-medical students (80.8% vs 73.1%, p = .007). Conclusion: Though the awareness rate of AIDS knowledge among medical students is better than that of non-medical students, they had incomplete knowledge of AIDS, especially the sexual transmission. Moreover, school classes may be an effective way to propagandize AIDS-related knowledge, so schools can consider publicizing the AIDS education through classes, so as to improve students’ abilities of AIDS control and prevention.
A Framework for Optimization of Software Test Cases Generation using Cuckoo Search Algorithm

Software testing is the most important phase of the software development lifecycle in the software industry. It is done to make sure that developed software is defect free; behavior of the software is same as expected and includes the generation of test data that satisfies some adequacy criteria like statement coverage, branch coverage, path coverage etc. This task is costly and time-consuming so there is an urge for automation of this process. In recent years various meta-heuristic based nature-inspired algorithms are applied in various fields of software engineering. This article proposes a framework for the generation of an optimal set of test cases using a meta-heuristic based optimization algorithm called Cuckoo Search Algorithm as well as an overall algorithm for the same.