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This work studies the performance of a Ge-based plasmonic detector with carrier mobility and lifetime variation. The performance is evaluated in terms of the detector's dark current, photocurrent, and detection bandwidth.

In the past years, individual electron spins confined in quantum dots have emerged as a promising candidate for realizing qubits, in view of their good scalability potential and relatively long decoherence times. Due to the recent advancements in qubit device technologies, the quantum system stack levels above the device level are becoming increasingly more relevant. However, quantum systems necessitate very specific requirements on the classical electronics that control and monitor the qubits, requiring good design tools for the co-design of the qubits with their associated electronics. We propose a circuit model for a spin qubit to facilitate this co-design. Our model includes readout via a resonator, single-qubit quantum gates based on electron spin resonance techniques and two-qubit quantum gates based on the spin exchange interaction. The model is also able to include qubit decoherence and handle the effects of nonideal control signals on the qubit. The spin qubit model can be completely simulated in Spectre®, thereby opening up possibilities for co-designing qubit-specific electronics in a commonly used simulation environment.

Computational efforts to simulate plasma processes have routinely faced challenges due to the multiscale, multispecies, and multidimensional nature of plasma behavior. Work towards predictive modeling of these processes spans from kinetic simulations that track particle-level interactions to fluid-based models for device scale phenomena. 1 , 2 Yet, the physics-based models remain challenging when the physics becomes more complex (cf. turbulence). Advancements in data-driven modeling and machine learning provide new opportunities for predictive modeling capabilities. The benefits of these approaches include the ability to use experimental data to solve the inverse problem and uncover the time histories of non-observed quantities that allows for real-time estimation of the plasma dynamics.

Passive balancing refers to the intentional deviations of market actors from their position in energy markets to support the real-time system balancing. Such a service is typically incentivized in a single imbalance pricing mechanism, where all imbalances are settled at a unique price. In this context, this paper presents a novel distributionally robust decision support tool, based on a bi-level model, for a market actor providing passive balancing services. The uncertainty related to the imbalance price is characterized by a Wasserstein metric-based ambiguity set, collecting all distributions in the neighborhoud of a central empirical one. In addition, the bi-level structure of the model allows capturing the interaction between the intentional imbalance position of the actor and the imbalance pricing mechanism. The proposed approach provides optimal passive balancing services in expectation over a worst-case imbalance price distribution, ensuring performance guarantees even if the probability distribution is not perfectly known. With a realistic case study using real-world market data from the Belgian power system, we validate and compare the proposed approach w.r.t. the performance of stochastic programming and robust optimization models.

This research enabled 38 homes in a rural village in Malaysia to have water supply. Many technologies for acquiring water supply have already been documented but it is often not modified sufficiently enough, leaving 14% of humanity with a severe lack of water. This paper describes a unique situation of solving the water scarcity for this village with technologies which may be adopted by villages. Examples of these are how to connect to the pumps over 120m, the type of pipes which are most suitable and methods to prime the pump and to prevent air locks. The final system is a 3 $\emptyset$, 4 HP pump placed near the river on two floats. This pump will push water up 120m horizontally and 9m vertically up to the Pump House located in the center of the village just behind the Community Hall. A smaller 3 $\emptyset$, 1 HP pump will pump water from the Pump House to the individual homes. Once water woes has been solved, various economic activities are introduced because it was noticed that a lack of water has demoralized the villagers, especially the youth in achieving their full human potential.

Despite all advantages proportionated by Blockchain, Smart Contracts and Distributed Applications technologies (trust, accuracy, security, savings, transparency, clear communication, storage & backup, etc.), we have experiencing in last years an increasing lack of qualified professionals having these technical skills, and this fact can be justified by high failure rates in STEM majors, and a reduced amount of technological practical activities in university classes. In such a way to mitigate such issues, we propose an extra-curricular training where undergraduate and graduate students can learn and practice such technologies, not usually presented in university programs. Such framework was experienced by students in three different universities in Bahia, Brazil, and the results found point out this training as an interesting and promising proposal.

The Internet of Things proposes a new paradigm of embedded systems in which every device in a network of computational objects has autonomy to communicate with other objects (things) or people, which allows its application in a wide range of domains, including the field of Education. This fact motivated the present work, developed from a community service learning project in which high school students (without advanced knowledge in electronics, programming and network protocols) participated in an experimentation aiming to enhance their logical reasoning skills from the construction of a “Smart Home” remotely controlled through the Internet. At the end of this practice, the students were motivated to develop new IoT projects to solve other problems of their daily lives. Being argued if they liked the course, they gave unanimous positive feedback, where 70% would be willing to take another course of this type and in this domain.

Quantum computers based on superconducting qubits have emerged as a leading candidate for a scalable quantum processor architecture. The core of a quantum processor consists of quantum devices that are manipulated using classical electronic circuits, which need to be co-designed for optimal performance and operation. As the principles governing the behavior of the classical circuits and the quantum devices are different, this presents a unique challenge in terms of the simulation, design and optimization of the joint system. A methodology is presented to transform the behavior of small-scale quantum processors to equivalent circuit models that are usable with classical circuits in a generic electrical simulator, enabling the detailed analysis of the impact of many important non-idealities. The methodology has specifically been employed to derive a circuit model of a superconducting qubit interacting with the quantized electromagnetic field of a superconducting resonator. Based on this technique, a comprehensive analysis of the qubit operation is performed, including the coherent control and readout of the qubit using electrical signals. Furthermore, the effect of several non-idealities in the system such as qubit relaxation, decoherence and leakage out of the computational subspace are captured, in contrast to previous works. As the presented method enables the co-simulation of the control electronics with the quantum system, it facilitates the design and optimization of near-term superconducting quantum processors.

This paper goes beyond the current state of the art related to Wasserstein distributionally robust optimal power flow problems, by adding dependence structure (correlation) and support information. In view of the space-time dependencies pertaining to the stochastic renewable power generation uncertainty, we apply a moment-metric-based distributionally robust optimization, which includes a constraint on the second-order moment of uncertainty. Aiming at further excluding unrealistic probability distributions from our proposed decision-making model, we enhance it by adding support information. We reformulate our proposed model, resulting in a semi-definite program, and show its satisfactory performance in terms of the operationalresults achieved and the computational time.

By using modular product structures, the external product variety required by customers can be realized with a minimum of internal variety of components and processes. Understanding the effects of this special product structuring strategy is essential in the early product planning phase to optimize the product structure for the entire value chain. For this purpose, an empirical study was conducted and is reported in this paper. Four real cases were analyzed to identify the effects of modular product structures considering effect occurrence and project-specific boundary conditions. The results are visualized in an extended impact model of modular product structures and traced back to possible measures of product structuring as well as essential target values in the company. These causal relationships serve product developers as decision support in planning and development of modular product structures.

In this work, fast stochastic surrogate models are derived for extracting RL parameters of wound inductors using the Finite Element method. To this end, the Representative Volume Element (RVE) technique is employed to convert the geometrical uncertainties (e.g. due to conductor positions in the winding window) into material uncertainties (complex permeability and conductivity). The dimensionality of the stochastic input space is in that way reduced, thereby allowing the use of the Polynomial Chaos Expansion (PCE) technique for building the stochastic surrogate.

Wireless interrogation of surface acoustic wave sensors can be accomplished either by inductive or electromagnetic (antenna) coupling. In order to optimize the coupling, we have performed finite element simulations of the entire coupled system. Both frequency dependent simulations and time dependent simulations have been performed. In the case of frequency dependent simulations, transformation into the time domain yields the envelope of the reflected signal. The results include guidance concerning the choice of matching components.

Unmanned Aerial Vehicles (UAVs) have been captivating audiences for over a decade now; from their military, mapping, photography, and even more recently cargo carrying abilities – UAVs continue to innovate in ways to remove human error from logistics and provide services never previously tenable. The USAID Global Health Supply Chain Program – Procurement and Supply Management project (GHSC-PSM) recently began delivering vital life-saving health services to remote locations in Africa via the use of UAVs. Through adaptation, these UAVs were embedded into the preexisting supply chain in Malawi to greatly improve health service delivery in several remote villages. The lessons learned from this activity have a larger impact on the use of UAVs and the potential benefits to society, especially related to health outcomes. With this activity, we hope to continue to innovate on UAV health service delivery and seek new avenues for which to improve the lives of people across the globe.

The 22FFL technology developed for operation to 3.3V is used to investigate process and design considerations required to extend technology capability to 12 V applications. A prototype chip was carefully designed in close consideration with the technology reliability requirements of the lower voltage components to demonstrate product-level reliability capabilities. The reliability of components such as transistors, well junctions, back-end dielectrics and MIMCAPs is thoroughly characterized and proven robust throughout a 10-year lifetime. The results demonstrate a reliable technology capability that is compliant with industrial standards to enable high-voltage design requirements.

This work presents silicon reliability characterization of Intel’s Foveros three-dimensional (3D) logic-on-logic stacking technology implemented on the 22FFL process node. Simulations and data demonstrate mechanical strain safe zones around Through Silicon Vias (TSVs). Evaluations of TSV impact on transistor, interconnect, and defect reliability are reported with a Si technology focus. TSV and bump architectures pass thermomechanical assessments on the final optimized process flow. Foveros 3D stacking technology is shown to exhibit robust silicon reliability.

This paper aims to present a platform to support the learning of high school students (without previous programming knowledge) for the development of technological solutions supported by the Internet of Things concept. This platform is designed from the integration of the following modules: A user-friendly visual programming environment for a specific microcontroller architecture; Web resource sharing tools assisting students in the tasks of communication and socialization of their projects (e.g., Wikis, Forums, Social Networks); A middleware, responsible for the communication between users (interfacing remotely with a teacher from a Web page) and sensors/actuators, present in an architecture remotely monitored by a teacher. With this proposal, it is expected that learners involved can be motivated and attracted by subjects related to the fields of Computer Science and (Electrical, Electronics, Mechatronics) Engineering. A scenario-based evaluation was performed to validate this platform.

Scratch has been shown as one of the main tools for teaching Computational Thinking through the concept of(block-based) programming. In the present research, two platforms based on/inspired by Scratch were considered for the analysis of their usability characteristics through the Cognitive Walkthrough method, for later use by engineering students at the beginning of their university courses for the development of their competences of logical thinking and abstraction of complex concepts: Snap4Arduino (used in the development of solutions for Internet of Things), and; App Inventor (used in the development of Android applications). The results show a positive evaluation of these tools, generating motivation for their use by new engineering students in their teaching-learning processes.

Blockchain introduces a new on-demand consensus paradigm where a set of P2P network nodes agrees on the order in which blocks of transactions are aggregated into a chain of blocks to provide a reliable, safe, scalable, immutable and distributed environment targeting the implementation and storage of transactions on the Internet. In such a way, the requirement of a credible party is eliminated, and a decentralized trust entity is created digitally. Through the use of electronic contracts, the relationships previously specified in documents and moderated by human beings can now be transformed into code and inserted into the blockchain, from the use of only driven-computer environments. This article presents a blockchain platform for innovation in the academic management, implementing a model composed of smart contracts to replace basic activities such as enrollment, school history and medical certifications verification, from a control of quality and safety previously unimaginable.