Miracle-dz/UniFAR-FTUs huggingface dataset:
Promoting the Learning Mobility of Future Workers: Experiments with Virtual Placements in University-Business Arrangements.

Summary Virtual placements are learning arrangements, which generate new possibilities for accumulating professional (work-based) knowledge. Virtual placements are beneficial in many ways; they merit increased training opportunities, exposure to not/never-thought-of occupations, integration of disadvantaged individuals, and preparation of, and blending with, physical placements. This paper reports about multi-country experiments with technologyenabled remote access to work, as a contribution to the work-based learning and professional mobility of students. The central question is: how may virtual placements be arranged so as to bring a contribution to the development of professional skills and competences? This paper first addresses the contribution of traditional placements, followed by the strengths and weaknesses of virtual ones. Next, real pilots with virtual (work-based) arrangements, are described. Regular universities experiment with virtual placements in oncampus courses and curricula, in frame of self-organised learning, whereas open universities experiment with virtual placements in off-campus courses and curricula, in frame of socialcollaborative and networked learning. Subsequently, the results of the different arrangements, their pros and cons, are described. Final conclusions from the study are drawn on the development of professional skills and competences in students, the implemented didactics and the technology applied.
Silicon photonic devices and integrated circuits

Abstract Silicon photonic devices and integrated circuits have undergone rapid and significant progresses during the last decade, transitioning from research topics in universities to product development in corporations. Silicon photonics is anticipated to be a disruptive optical technology for data communications, with applications such as intra-chip interconnects, short-reach communications in datacenters and supercomputers, and long-haul optical transmissions. Bell Labs, as the research organization of Alcatel-Lucent, a network system vendor, has an optimal position to identify the full potential of silicon photonics both in the applications and in its technical merits. Additionally it has demonstrated novel and improved high-performance optical devices, and implemented multi-function photonic integrated circuits to fulfill various communication applications. In this paper, we review our silicon photonic programs and main achievements during recent years. For devices, we review high-performance single-drive push-pull silicon Mach-Zehnder modulators, hybrid silicon/III-V lasers and silicon nitride-assisted polarization rotators. For photonic circuits, we review silicon/silicon nitride integration platforms to implement wavelength-division multiplexing receivers and transmitters. In addition, we show silicon photonic circuits are well suited for dual-polarization optical coherent transmitters and receivers, geared for advanced modulation formats. We also discuss various applications in the field of communication which may benefit from implementation in silicon photonics.
Optical correction capability of piezoelectric deformable mirror based on unimorph microactuator array

Piezoelectric DM based on unimorph microactuator array has advantages of large stroke with low voltage and high operating bandwidth. In this paper, we estimate the correction capability of this DM by fitting Zernike polynomials shapes. First, the influences of actuator arrangement, actuator number and coupling on correction capability were investigated to optimize the correction performance. Then low-order Zernike shapes were reproduced by a fabricated DM using measured influence function matrix. Experiment and simulation results show that the DM has a satisfying correction performance.
The Role of EOCs in Emergency Management: A Comparison of Canadian and American Experience

The literature on emergency management is full of praise for Emergency Operations Centers (EOCs), yet it contains little actual description of EOCs in operation. When Henry Quarantelli (1987) examined actual EOCs, he, too, found them valuable. But he also identified problems: the EOC is in the impact area, forcing it to relocate when disaster strikes; access to the EOC is so badly controlled it becomes cramped and crowded, which may lead to decisions being made by a small group separately; membership changes constantly, making it difficult to establish continuity in decision-making; it isn't clear, at many incidents, who was managing the EOC itself. Finally, when an EOC is established, it does not necessarily work as a unit. Quarantelli was using American research. This article uses 19 Canadian incidents to see whether disaster experience in another country would support Quarantelli. The article reports precisely the same problems. It also reports -- as did Quarantelli -- that EOCs are effective. Finally, it says their use in Canada is growing.
A Classification Approach for Heart Disease Diagnosis using Machine Learning

Heart Disease (HD)is a critical condition that many people suffer from and it is the expression which is used to characterize different types of heart conditions. Many people suffer with heart issues Heart disease remains the number one killer disease, especially in the United States. The main symptoms of heart disease are smoking, obesity, alcohol, high blood cholesterol level, hypertension etc. There are many algorithms that are used to improve the performance in health care system through information gathering in the form of datasets and it is used for various applications that are advanced in healthcare industry. In our paper, we used four machine learning classification techniques. Firstly, we included Support Vector Classifier (SVC). Is used to predict the model based on parameters considered. second one is the Logistic regression(LR). It is used to describe the classification problems based on the input parameters. Thirdly, Naive Bayes (NB) classifier and finally, the Decision tree (DT) Algorithm. We used different classifiers to boom the accuracy and overall performance. The principle intension of our proposal is to improve the accuracy rate and to identify heart disease by implementing the machine learning classifier techniques.
Preliminary Analytics of Video Cache Improvement using Random Linear Network Coding*

The demand of video streaming has become part of our modern daily life, especially under the threat of COVID-19. In order to promote the video quality, several video streaming techniques design and configure video cache along the transmission path. This paper investigates and studies how to improve video cache based on Random Linear Network Coding (RLNC). According to our initial experimental results on Peer-to-Peer (P2P), the proposed strategies can provide more flexible video distribution.
Skin Pathology Detection Using Artificial Intelligence

Skin Cancer is a disturbing disease in modern life. This disease should be detected as early as possible to reduce the impact of the disease as the growth of Melanoma cancer is rapid and it’s treatment cost is so high. The death rate caused by the Melanoma cancer is also so high. As the detection of the cancer cells manually take long time which causes delay in the treatment. This paper is proposed to detect the effected cancer cells by utilizing image processing. After segmentation process the features are extracted. Here CNN is arranged to extract the features.
Secure Accountable Dynamic Storage Integrity Verification

Integrity verification of cloud data is of great importance for secure and effective cloud storage since attackers can change the data even though it is encrypted. Traditional integrity verification schemes only let the client know the integrity status of the remote data. When the data is corrupted, the system cannot hold the server accountable. Besides, almost all existing schemes assume that the users are credible. Instead, especially in a dynamic operation environment, users can deny their behaviors, and let the server bear the penalty of data loss. To address the issues above, we propose an accountable dynamic storage integrity verification (ADS-IV) scheme which provides means to detect or eliminate misbehavior of all participants. In the meanwhile, we modify the Invertible Bloom Filter (IBF) to recover the corrupted data and use the Mahalanobis distance to calculate the degree of damage. We prove that our scheme is secure under Computational Diffie-Hellman (CDH) assumption and Discrete Logarithm (DL) assumption and that the audit process is privacy-preserving. The experimental results demonstrate that the computational complexity of the audit is constant; the storage overhead is $O(\sqrt n )$, which is only 1/400 of the size of the original data; and the whole communication overhead is O(1). As a result, the proposed scheme is not only suitable for large-scale cloud data storage systems, but also for systems with sensitive data, such as banking systems, medical systems, and so on.
Research on the use of AIoT and 5G in Mobile Commerce

With the continuous development of mobile communication technology, wireless Internet technology and the rapid growth of mobile phone users, mobile e-commerce has also been further developed. It can make people get the needed information at any time, pay all kinds of fees at any time, order goods at any time. At the same time, it is also people's "ID card", which is becoming an indispensable part of people's life. If the premise of interconnection of all things is mature 5G technology, then the catalyst of interconnection of all things is artificial intelligence. The combination of the two will change the whole mode of social production and improve social productivity. With the arrival of 5G network with characteristics of large bandwidth and low delay, more and more industries have the conditions to apply AI technology, so that all things can be realized and application scenarios can be enriched. The future of mobile e-commerce is bright, but the road is tortuous. The key is to see the development direction of mobile e-commerce. If the development direction is right, then mobile e-commerce will develop at an amazing speed. This paper takes mobile business under the background of AIoT combined with 5G technology as the object. Firstly, take a large number of literature search and collation, then it introduces the overall environment of China's mobile commerce through questionnaire survey and case study, states in detail the changes of mobile commerce under the influence of 5G and AIoT technology from the three perspectives of pre transaction, mid transaction and post transaction of mobile commerce, further analyzes the current situation and existing problems of China's mobile commerce development, and combines the research results obtained from the research methods to become mobile commerce. The development of mobile commerce gives reasonable suggestions, which provides a reference for the ultimate trend of mobile commerce.
Modeling in Water Losses Evaluation for Nonhomogeneous Furrow Set

Due to differences in infiltration characteristics across field, unifonnly delivered furrow irrigation streams advance at different rates. This "inter-row" nonuniformity is combined with the nonuniform distribution of irrigation water along the furrow length. Unlike studies based on data from one or two representative furrows, this analysis evaluates water losses in the presence of both lateral and longitudinal variation. A spatial mathe­ matical description of the nonuniform distribution of application depth over the whole field area is made in relative terms. Formulas for evaluation of water losses were derived by integrating both "downfield" and "inter­ row" deep percolation and runoff losses. The percentage losses calculated by these formulas were compared with those assessed from one and two representative furrows and differences up to twofold were found. An algorithm was developed for model application over a wide range of field conditions. The model was calibrated for irrigation on clay and silty clay loam soils and examples were given of its use.
Automatic Model Determination for Quaternion NMF

Nonnegative Matrix Factorization (NMF) is a well-known method for Blind Source Separation (BSS). Recently, BSS for polarized signals in spectropolarimetric data, containing both polarization and spectral information, was introduced. This information was encoded in 4-dimensional Stokes vectors represented by quaternion numbers. In the proposed Quaternion NMF (QNMF), the common challenge of determining the (usually) unknown number of quaternion signals remained unaddressed. Estimating the number of signals (aka model determination) is important, since an underestimation of this number results in poor source separation and omission of signals, while overestimation leads to extraction of noisy signals without physical meaning. Here, we introduce a method for determining the number of polarized signals in spectropolarimetric data, named QNMFk. QNMFk integrates: (a) Quaternion Alternating Direction Method of Multipliers (QADMM) implemented for QNMF, (b) random resampling of the initial quaternion data, and (c) custom clustering of sets of QADMM solutions with same number of sources, k, needed to estimate the stability of the solutions. The appropriate latent dimension is determined based on the stability of the solutions. We demonstrate that, without any prior information, QNMFk accurately extracts the correct number of signals used to generate synthetic quaternion datasets and a benchmark spectropolarimetric data.
Vibration attenuation by a combination of a piezoelectric stack and a permanent magnet

Thepresentworkproposesanon-contactvibrationattenuatormadeupofapermanentmagnetmountedonapiezoelectric stack. Two such actuators are made to work simultaneously in a 'twin-actuator' configuration. It is conceived that a controlled change in the gap between the actuator and the structure is capable of attenuation of vibration of the structure. This appropriate change in gap is achieved by controlled motion of the piezoelectric stacks. It is shown that the actuator works as an active damper when the extension and contraction of the actuators are made proportional to the velocity of the beam. The resolution of extension of a piezoelectric stack is in the order of nanometers. Thus in the proposed actuator the force of actuation can be applied with great precision. This actuator is also attractive for its simple constructional feature.
A comprehensive approach to identifying key stakeholders in complicated software ecosystems

Software stakeholders are critical to the success of software development projects, because they influence the strategic direction, the financial backing, and have specific knowledge – all of which sustains the software being developed. As the complexity of software environments increase, and expectations for cross-product integration heighten, there is more pressure on actors within software ecosystems (SECOs) to work in unison to produce reliably integrated software, efficiently. Recently collected empirical findings show that requirements managers working in SECO environments believe that all key stakeholders can be identified, but that it requires analysis, investigation and expert knowledge. Until now, the existing frameworks describing stakeholder identification do not take into account the level of dependencies that occur in SECOs nor the implications on SECO health. This research proposes that a structured comprehensive approach to identifying stakeholders in SECOs would provide practitioners the guidance they need to avoid the common pitfalls of poor stakeholder identification, including late requirements from critical stakeholders which can risk the software release schedule, software quality, and scope.
Interconnects and transitions in multilayer LTCC multichip modules for 24 GHz ISM-band applications

Multilayer LTCC substrates with screen printed conductors are considered as a key technology for coming RF wireless communication and automotive applications. Small but expensive MMICs should be integrated in a much cheaper LTCC environment to become a multichip module (MCM). Interconnects between the environmental waveguides and the integrated chips have been designed, optimized, fabricated and evaluated by the authors, which are partners in the European R&D project RAMP.
Comparison of Methods for Sensitivity Determination of Point-Contact Diodes at Submillimeter Wavelength

Three independent methods were used: 1) mixing of two HCN lasers; 2) mixing of the sixth harmonic of a klystron with an HCN laser; and 3) the incremental-loss method. The results are given. The most sensitive configuration was obtained using a corner reflector. The influence of local-oscillator (LO) power on the conversion losses of the diodes are investigated.
SUFI: A Simulation-based Fault Injection Tool for Safety Evaluation of Advanced Driver Assistance Systems Modelled in SUMO

Embedded electronic systems used in vehicles are becoming more exposed and thus vulnerable to different types of faults and cybersecurity attacks. Examples of these systems are advanced driver assistance systems (ADAS) used in vehicles with different levels of automation. Failures in these systems could have severe consequences, such as loss of lives and environmental damages. Therefore, these systems should be thoroughly evaluated during different stages of product development. An effective way of evaluating these systems is through the injection of faults and monitoring their impacts on these systems. In this paper, we present SUFI, a simulation-based fault injector that is capable of injecting faults into ADAS features simulated in SUMO (simulation of urban mobility) and analyse the impact of the injected faults on the entire traffic. Simulation-based fault injection is usually used at early stages of product development, especially when the target hardware is not yet available. Using SUFI we target car-following and lane-changing features of ADAS modelled in SUMO. The results of the fault injection experiments show the effectiveness of SUFI in revealing the weaknesses of these models when targeted by faults and attacks.
An Improved EEG-Based LRCN Emotion Recognition System Using Fuzzy Processing on ECG and PPG Features

In this paper, we proposed an improved 3 classes emotion classification system based on a Long-Term Recurrent Convolutional Network (LRCN) model using Electroencephalogram (EEG) signals, reinforced with a fuzzification process on extracted Electrocardiogram (ECG) and Photoplethysmogram (PPG) features. Although a good average accuracy can be achieved at 75%, the accuracy for some specific subjects remained very poor, mostly caused by a low correlation between EEG signal and emotion in a particular subject, or by a lowquality EEG signal recording. The fuzzification process on extra physiological signals was added for EEG-based LRCN to improve the total average accuracy by 8% and correct some low correlated EEG signals and emotions for certain subjects.
Monitoring the seagrass Posidonia oceanica to understand the effects of local disturbances in a marine protected area

Since the seagrass Posidonia oceanica is highly sensitive to environmental changes, a monitoring of the physiognomy, phenology and lepidochronology of the meadows was conducted during 2015-2020 at Tremiti Islands Marine Protected Area (Adriatic Sea). The meadow resulted stressed where anthropogenic disturbances occurred, while the implementation of proper management measures proved to trigger the recovery of the habitat. Our results underlined the importance of P. oceanica as a biological indicator to monitor human activities at local scale.
Calibration and basic motion of a micro hand module

A dexterous micro-manipulation system is developed for application in assembling micro-machine, manipulating cells, and micro-surgery. We have proposed a concept of a two finger micro-hand, and designed and built a hand module based on parallel mechanisms. The module has 6 degrees of freedom with piezoelectric devices as actuators. A calibration method based on least square error is proposed for 3-DOF translational motion in task coordinates fixed under a microscope. Coordinated motion is generated by both programming control and joystick teleoperation control. <<ETX>>
Two-level, multistate Markov model for satellite propagation channels

A new model to provide more states of the Markov model while limiting the size of the Markov transition matrix is proposed to save processing time and reduce memory requirements in predicting the fading statistics and error probability of land mobile satellite systems (LMSS) and satellite personal communication services (S-PCS). Propagation fading is treated as slow fading (or shadowing) and fast fading (or multipath fading). Both of these levels can be separated into several propagation states. Two Markov state transition matrices are introduced to simulate the variation in the strength of the received signal caused by shadowing and multipath fading. Fading statistics and error probability in typical mobile user environments are accurately predicted. The advantage of this new model over the traditional single Markov state transition model is that it can generate more accurate simulation results and help to predict performance. This simple and efficient model extends the application of the Markov process method to propagation channel modelling for LMSS and S-PCS.
A general physical model for short-channel double-gate SOI MOSFETS

Previous works on the modeling of short-channel double-gate devices in the above-threshold regime were based mainly on modifying the current expressions for bulk devices. These models would probably be of limited utility because they do not account for the central physical characteristic of the double-gate devices, namely the coupling of the two channels. In this paper, we present a general physical model which explicitly accounts for physical effects such as channel coupling and drain induced conductance enhancement (DICE). The model is a major extension of the single-gate SOI MOSFET model to the double-gate case.