Miracle-dz/UniFAR-FTUs huggingface dataset:
EncounteredLimbs: A Room-scale Encountered-type Haptic Presentation using Wearable Robotic Arms

Haptic information significantly improves human awareness of objects in virtual reality. One way of presenting this information is via encountered-type haptic feedback. An advantage of encounter type feedback is that it enables physical interaction with virtual environments without the need for specialized haptic devices on the hand. Additionally, encountered-type haptics are known for being able to provide high quality contact feedback to the user. However, such systems are typically designed to be grounded (i.e., fixed to the floor). As such, they typically have bounded workspace and a limited range of possible applications. In this work, we present a novel, wearable approach to presenting a user with encountered-type haptic feedback. We realize this feedback using a wearable robotic limb that holds a plate where the user might interact with their environment. An appropriate location for the plate is determined by a novel haptic solver while control of the arm is made possible using motion trackers. The system was designed to be stable, for presenting consistent haptic feedback, while also being safe and lightweight for wearability. By making the feedback system wearable, we enable the presentation of stiff feedback while maintaining the spatial freedom and unbounded workspace of natural hand interaction. Herein, we present the design of the novel system, mechanical and safety considerations when designing a wearable encountered-type system, and an evaluation of the system. A technical evaluation of the implemented system showed that the system provides a stiffness over 25 N/m and slant angle errors under 3°. Three user studies show the limitations of haptic slant perception in humans and the quantitative and qualitative effectiveness of the current prototype system. We conclude the paper by discussing various potentialapplications and possible improvements that could be made to the system.
A review on the comparison of conventional and corona resistant nanofilled enamels

The low voltage rotating electrical machines, typically based on Type I random/wound windings, are normally controlled by power electronic drives. The power supply voltage waveforms are characterized by fast rise and fall time fronts and in case of resonance and reflection phenomena, overvoltage could appear at the connection terminals of the machine. These overvoltages can incept the partial discharges in the electrical insulation, leading to the total breakdown of the machine. The nanocomposite material used as enamel on the winding wires can lead to increase the performances of the insulating system. In recent years, new class of corona resistant materials based upon nano particles have been characterized. In this work, an overview of the research studies performed by the CMTEST laboratory staff of the University of Genova is presented to summarize the results obtained comparing the behavior of conventional and nano-filled enamels.
Thermal Analysis of GaN/SiC-on-Si Assemblies: Effect of Bump Pitch and Thickness of SiC Layer

The ever-increasing requirements for high device performance and compact size drive the communications industry to lookfor new materials, technologies, and integration concepts. This simulation-based study investigates the thermal properties of a compact, heterogeneously integrated gallium nitride on silicon carbide (GaN-on-SiC) and silicon (Si) assembly. Thermal simulations and parametric studies are used to determine how the heat spreading and temperature levels in the lateral and vertical directions are affected by the thickness of the SiC layer and the distribution of the thermal interconnects. Results show that a SiC layer thinned down to 100 µm shows more pronounced differences in its thermal characteristics compared to thicker ones, especially in terms of its backside heating. Aspects related to practical implementations are also considered.
Automated Shopping and Convenient Wi-Fi Based Indoor Navigation

The essential motivation behind this cross-stage application is to ease the process of shopping during and after the pandemic. The proposed application allows users to enter their location and provides the layout of the store-an indoor navigation system to suggest the least time consuming routes to people based on the human traffic through live mapping. The users can then scan the items bought using the inbuilt barcode scanner on the app. This methodology would give us better understanding of customer choices and avoid long queues.
Calculating the Supplied Energy for Physical Human-Robot Interaction

As the safety of robotics is highly demanded, injury criteria are widely investigated and employed in control strategies because of their guiding roles, in which the energy (density) tolerances are of priority owing to unification of other physical variables for injury criteria. However, the calculation method for the supplied energy of the physical Human-Robot Interaction (pHRI) is not addressed by considering the viscoelasticity of the human soft tissue. This paper presents four collision modes for classifying the pHRI and proposes a generic method for calculating the supplied energy of each collision mode. Consequently, specific calculation instances are given by treating the human soft tissue as a three-element Maxwell model with maximum/allowable compressive displacement. The feasibility and precision of the proposed calculation method are verified by comparing the computational and simulation results. This calculation method is intended to provide a way of directly determining or indirectly converting the allowable velocity or mass of an approaching robot.
Power and Traffic Nexus: From Perspective of Power Transmission Network and Electrified Highway Network

The increasing prevalence of electric vehicles (EVs) and emerging dynamic wireless charging techniques have increased the interdependence between the power and transportation systems. This article investigates a new nexus scenario—the electrified highway network (EHN) and power transmission network (PTN). The independent but interrelated operation of the two networks is analyzed. On the EHN side, a combined charging–driving navigation (CCDN) model, which rigorously considers EV travel speed and charge/discharge behaviors, is proposed and formulated as an irregular dynamic programming problem. A chronological search algorithm is designed to derive the optimal charging–driving decision sequences. The economic operation of the PTN is formulated as a direct current optimal power flow problem. Hourly location marginal prices (LMPs) and charge/discharge demands are exchanged between the two networks. The abovementioned LMP-based interaction forms a Nash-type game, in which both networks aim to minimize their own operation costs. A best-response decomposition algorithm combined with a continuous LMP method is developed to identify the equilibrium state. Numerical results demonstrate the effectiveness of the CCDN model in modeling EV charging–driving behaviors in the EHN. Moreover, the results show that, under certain conditions, mobility of EVs along the EHN can economically relieve the transmission congestion and reduce the operation costs of both networks.
Image Classification of Rice Leaf Diseases Using Random Forest Algorithm

The problem of rice diseases around the world make to damage and fall into a large number of rice. Caused by many of types, such as; fungi, Bakteri and Viruses. which are the main causes of rice disease affected to farmers. The classification of rice can be classified into several methods. In this research, image classification is used to classify the data set of rice leaf diseases, such as; Brown Spot Rice disease (BSR), Brown Spot Rice disease (BSR), Bacterial Leaf Blight disease (BLB), which is the rice leaf disease with severe outbreaks around Thailand. Moreover, image processing technology in the classification types of rice leaf disease, such as; Random forest classification algorithm, Decision tree classification algorithm, Gradient Boosting classification algorithm and Naïve-Baye classification algorithm, which is measured by the accuracy, precision and recall of each algorithms. The best result of performance in the image classification of rice leaf diseases is random forest algorithm equal to 69.44 percent.
Isolation Bandwidth Enhancement of Electrical Balance Duplexers

In In-Band Full Duplex (IBFD) transceivers, newly suggested Electrical Balance Duplexer (EBD) technique works by coupling transmitter, receiver, antenna, and balancing impedance using a hybrid junction where the balancing impedance needs to be equal to the antenna impedance to achieve a high Transmit-Receive (TX-RX) isolation. This isolation implements a form of self-interference (SI) cancellation to facilitates simultaneous transmission and reception from single antenna. Variations in antenna impedance with respect to frequency significantly reduces the isolation bandwidth and is dominant factor in limiting the isolation. A frequency independent antenna with a core structure of equiangular Archimedean spiral is designed by authors with high impedance stability in ultra-wideband (UWB) frequency domain of 1.5GHz to 3.5GHz while the antenna impedance is smoothened using some electromagnetic techniques. In comparison with the literature, using this antenna in the EBD stage along with a simpler balancing impedance is resulted to six times wider isolation bandwidth in the EBD stage.
Wireless Communications for IoT: Energy Efficiency Survey

Internet of Things concept has brought us many sensors application possibilities that aim to make our lives better. The IoT concept entail the use of low-power, low-cost, long-range sensors that can collect data from the environment and send it to the user application using wireless link, for maximum mobility. In this paper we evaluate and compare a couple of the market available LPWAN solutions, trough the energy efficiency perspective. Although LPWAN implies low-power devices, some of the modules used in the experimental setup need a high current burst, making them inefficient if the power supply is not properly sized. Thus, the main contribution of this paper is the energy efficiency analysis of the main existing IoT technologies like LoRa or SigFox. From the obtained results one may conclude that some modules can transmit using high current peaks for short period of time while others can transmit low current peaks for long period of time, being useful only for specific monitoring applications.
Conversation Analysis of Robot-Assisted Recreation for Older Adults with Dementia

Social commitment robots have been used in aged care facilities as a group activity to enhance social wellness in older adults with dementia. This preliminary study examined the effectiveness of a scenario-type Robot-Assisted Recreation (RAR) program by analyzing participants' conversations. The RAR program was designed to provide participants with ongoing enjoyment and to take into account the cognitive conditions with dementia. The effects of activating communication between the participants were tested in field works of four RAR activities. Speech data recorded during recreation and pre-recreation and post-recreation interviews were analyzed for transcriptions, the number of utterances, response speech duration, and fundamental frequency of speech data. Results revealed that participants' QoL improved in terms of their willingness to participate in recreation, their positive feelings about the future, and their interest in interacting with others.
Anti-patterns in Modern Code Review: Symptoms and Prevalence

Modern code review (MCR) is now broadly adopted as an established and effective software quality assurance practice, with an increasing number of open-source as well as commercial software projects identifying code review as a crucial practice. During the MCR process, developers review, provide constructive feedback, and/or critique each others’ patches before a code change is merged into the codebase. Nevertheless, code review is basically a human task that involves technical, personal and social aspects. Existing literature hint the existence of poor reviewing practices i.e., anti-patterns, that may contribute to a tense reviewing culture, degradation of software quality, slow down integration, and may affect the overall sustainability of the project. To better understand these practices, we present in this paper the concept of Modern Code Review Anti-patterns (MCRA) and take a first step to define a catalog that enumerates common poor code review practices. In detail we explore and characterize MCRA symptoms, causes, and impacts. We also conduct a series of preliminary experiments to investigate the prevalence and co-occurrences of such anti-patterns on a random sample of 100 code reviews from various OpenStack projects.
Thermal Characterisation and Failure Analysis of MMIC Components by Thermo-Reflectance Imaging

Thermo-reflectance (TR) imaging for thermographic purposes in thermal characterisation and failure analysis is becoming a technique with increasing performance, relevance and fields of application despite the small scale of the effect and the consequently compulsory requirements for lock-in amplification. Whereas a classical benchmark case for TR imaging are structures in the range between the spatial resolution limit of optical and infrared (IR) wavelength devices (as e.g. HEMT-structures), there is a lot of potential to use it for failure analytical purposes with more relaxed requirements on absolute measurement values. We show, based on a simple TR setup, the performance and limits of the technique, apply it to typical terminal metals used in electronics for calibration and benchmark the method on some typical use cases and also against IR-based thermographic methods where meaningful.
Micromagnetic simulation of finite and infinite-size Fe nanowire arrays

The article presents some results of ICPE-CA research for the development of new permanent magnets based on nano ferromagnetic wires without rare earths or other expensive raw materials. The paper presents the results of the modeling of some spatial arrangements of the iron nanowires. Several ratios between the base area and the length of the wire are considered. Hysteresis loops show how the properties of the entire configuration are influenced depending on the geometry of the nanowires and their arrangement. The micromagnetism model started from the definition of the types of energies that compete with each other and that define the magnetic properties. The simulations show that for nanowires with aspect ratio $L/\ell \ge$10 they can be treated as infinitely long nanowires. Study of finite and infinite-size arrays of nanowires shows that the hysteresis loops converge to an oblique shaped loop with coercive field larger than 100 kA/m.
Study of Anomalous Hot-Carrier Degradation of NMOS Transistor with 3D-NAND Hydrogen-Rich Process

Hot Carrier Injection (HCI) behavior of 3.3V NMOS with 3D-NAND hydrogen-rich process has been studied, and an anomalous HCI degradation is observed. To explain this anomalous degradation, the interface trap evaluation has been studied by TCAD and a novel model for current (IDS and IDL) degradation is proposed for the first time.
A New High Gain Active Switched Network-Based Boost Converter for DC Microgrid Application

This paper deals with an active switched inductor network-based high gain boost converter. By using less number of components in circuit topology, a higher gain in voltage can be attained at a small duty cycle value by using the proposed converter, which helps in reducing the switch voltage stress and conduction loss. In addition, it draws continuous input current, has lower diode voltage stress, and lower passive component voltage ratings. The operating principles and key waveforms in Continuous Conduction Mode (CCM) and Discontinuous Conduction Mode (DCM) are presented. Parameter design, power loss calculation, characteristics, and comparative study with other non-isolated converters have been presented. Finally, a 200W hardware prototype is constructed and the viability of the proposed converter is verified through the experimentally obtained results.
Counter-Misdirection in Behavior-based Multi-robot Teams **Research supported by the National Science Foundation under CNS EAGER grant #1848653.

When teams of mobile robots are tasked with different goals in a competitive environment, misdirection and counter-misdirection can provide significant advantages. Researchers have studied different misdirection methods but the number of approaches on counter-misdirection for multi-robot systems is still limited. In this work, a novel counter-misdirection approach for behavior-based multi-robot teams is developed by deploying a new type of agent: counter-misdirection agents (CMAs). These agents can detect the misdirection process and “push back” the misdirected agents collaboratively to stop the misdirection process. This approach has been implemented not only in simulation for various conditions, but also on a physical robotic testbed to study its effectiveness. It shows that this approach can stop the misdirection process effectively with a sufficient number of CMAs. This novel counter-misdirection approach can potentially be applied to different competitive scenarios such as military and sports applications.
Real Time Emotion Based Music Player Using CNN Architectures

Emotion detection is the process of detecting a human being's emotions based on various facial cues and visual information. This field has gained much traction since the popularity of deep learning. Emotion detection has also given rise to many applications that had not been thought of before. One of the areas that are heavily associated with emotions is music. Music can invoke particular emotions of the listener, and a person feeling a certain emotion would look for a similar song. We use our emotion detection model to associate these emotions with a music player that plays music that accompanies user experiences. The model we designed includes two convolutional neural networks (CNN) models: a five-layer model and a global average pooling (GAP) model. We combined these CNN models with transfer-learning models. For our transfer-learning models, we used three pre-trained models: ResNet50; SeNet50; VGG16. Our results are comparable with the state-of-the-art models; however, our models are more efficient in performance.
Vocational Education Digital Enterprise Architecture Framework (VEDEAF)

The purpose of this research was follows: 1) synthesis of components of enterprise architecture and 2) to develop a vocational education digital enterprise architecture framework (VEDEAF) 3) evaluate of VEDEAF. Which have been studied from theories, documents and researches related to enterprise architecture, high performance organization, digital organization and operating process within Vocational Education College. The results of the research showed that components of VEDEAF consist of six component which are 1) Business Architecture, 2) Data Architecture, 3) Application Architecture, 4) Infrastructure Architecture, 5) Security Architecture and 6) Human Capital Architecture. Each components also divided into sub-module as follows; Business Architecture divided into 2 submodules which are Mission and Core Processes; Data Architecture divided into 2 sub-modules which are Core Process Data and Supporting Process data; Application Architecture divided into 3 sub-modules which are Instructional Application, Process Application and Integration Application; Infrastructure Architecture divided into 5 sub-modules which are Communication Platform, Operating System, Hardware Platform, Network and Data Communication Platform and Server Platform; Human Capital Architecture divided into 4 sub-modules which are Executive, Teacher, Student and Administration. To evaluation results of VEDEAF, the result found that the appropriate is at very high levels.
Recording, Visualising and Understanding Developer Programming Behaviour

To understand how developers solve programming tasks, it is necessary to observe what they are doing, i.e., what specific actions they perform, which strategies they apply and how they make use of possibly present, but not yet known or otherwise not yet available information that is needed to solve a task. To do so, we implemented a plug-in for the Eclipse IDE which captures nearly every interaction with the IDE a developer performs when working on a programming task. This enables us to comprehensively track a developer’s behaviour, e.g., whether and when a code edit needed for solving a given task was performed, and even more interesting, what were the preceding steps that led the developer to do so. In a first experiment conducted with the new plug-in, we were able to observe action patterns and program comprehension stages that confirm results of previous studies as well as were partly only suspected until now by recent literature, but never truly observed before.Screencast of the tool: https://youtu.be/GeZI-vCdgfoClosed caption version: https://youtu.be/mgt6Q-t7U00
Current Sensorless Control for WRSM Using Model-Free Adaptive Control

Sensorless control theory is considered as one of the most important keys to reduce the cost of manufacturing and maintenance in automotive applications. This article presents a current sensorless control algorithm of a wound rotor synchronous machine using a model-free-adaptive control (MFAC). The only controlled variable in this method is the rotor speed, and no observation or estimation will be performed on the phase currents. The presented controller is also compared with a current sensorless control method that uses a Lyapunov-based observation of phase currents in the control algorithm. The developed control algorithm is first tested in simulation under several operating conditions, such as starting, tracking, parameter variation, and load step. Then, experimental tests validated the effective performance of MFAC in a current sensorless control algorithm. According to these results, the control of phase currents is guaranteed with a small error but without using any current sensors.
Investigation Of Transformer Health Prediction Through Accelerated Aging Studies of the Natural Ester/Paper Complex

The life duration of cellulosic insulation is an essential aspect in the design of power transformer. Mineral oils have been largely used as liquid dielectrics to extend the service life of transformers. However the environmental and health aspects led to the seeking of alternative liquid dielectrics. Many authors have claimed that the use of bio-based liquids, especially natural esters can slow down the aging process of dielectric paper. The use of natural esters can therefore extend the actual operating life of transformers. Many vegetable oils have been elaborated. In this paper, we focus on palm kernel and castor oils, two non-edible vegetable oils largely present in Central Africa. We show the results of a study of thermal aging of dielectric paper immersed in palm kernel and castor oils. We start by presenting the elaboration and performance analysis processes of methyl esters of palm kernel and castor oils. Next, we develop the aging procedure; the paper was aged at 110°C during 100 hours, samples of oils and insulating paper were taken for analyses. The various tests performed included the determination of the total acid number, the UV-visible spectroscopy and the physical changes of the insulating paper. The results obtained with natural esters are compared to those obtained with mineral oil, which was used as a benchmark. The results obtained with palm kernel and castor oils confirms the excellent dielectric and cooling properties observed with other natural esters.