Showing papers in "Electronics in 2016"

Electrolytic Gated Organic Field-Effect Transistors for Application in Biosensors—A Review

Abstract: Electrolyte-gated organic field-effect transistors have emerged in the field of biosensors over the last five years, due to their attractive simplicity and high sensitivity to interfacial changes, both on the gate/electrolyte and semiconductor/electrolyte interfaces, where a target-specific bioreceptor can be immobilized. This article reviews the recent literature concerning biosensing with such transistors, gives clues to understanding the basic principles under which electrolyte-gated organic field-effect transistors work, and details the transduction mechanisms that were investigated to convert a receptor/target association into a change in drain current.

Cyber-Physical System Security of a Power Grid: State-of-the-Art

Abstract: As part of the smart grid development, more and more technologies are developed and deployed on the power grid to enhance the system reliability. A primary purpose of the smart grid is to significantly increase the capability of computer-based remote control and automation. As a result, the level of connectivity has become much higher, and cyber security also becomes a potential threat to the cyber-physical systems (CPSs). In this paper, a survey of the state-of-the-art is conducted on the cyber security of the power grid concerning issues of: (1) the structure of CPSs in a smart grid; (2) cyber vulnerability assessment; (3) cyber protection systems; and (4) testbeds of a CPS. At Washington State University (WSU), the Smart City Testbed (SCT) has been developed to provide a platform to test, analyze and validate defense mechanisms against potential cyber intrusions. A test case is provided in this paper to demonstrate how a testbed helps the study of cyber security and the anomaly detection system (ADS) for substations.

A Comparative Review of Footwear-Based Wearable Systems

Abstract: Footwear is an integral part of daily life. Embedding sensors and electronics in footwear for various different applications started more than two decades ago. This review article summarizes the developments in the field of footwear-based wearable sensors and systems. The electronics, sensing technologies, data transmission, and data processing methodologies of such wearable systems are all principally dependent on the target application. Hence, the article describes key application scenarios utilizing footwear-based systems with critical discussion on their merits. The reviewed application scenarios include gait monitoring, plantar pressure measurement, posture and activity classification, body weight and energy expenditure estimation, biofeedback, navigation, and fall risk applications. In addition, energy harvesting from the footwear is also considered for review. The article also attempts to shed light on some of the most recent developments in the field along with the future work required to advance the field.

Graphene and Two-Dimensional Materials for Optoelectronic Applications

Abstract: This article reviews optoelectronic devices based on graphene and related two-dimensional (2D) materials. The review includes basic considerations of process technology, including demonstrations of 2D heterostructure growth, and comments on the scalability and manufacturability of the growth methods. We then assess the potential of graphene-based transparent conducting electrodes. A major part of the review describes photodetectors based on lateral graphene p-n junctions and Schottky diodes. Finally, the progress in vertical devices made from 2D/3D heterojunctions, as well as all-2D heterostructures is discussed.

3D Environment Mapping Using the Kinect V2 and Path Planning Based on RRT Algorithms

Abstract: This paper describes a 3D path planning system that is able to provide a solution trajectory for the automatic control of a robot. The proposed system uses a point cloud obtained from the robot workspace, with a Kinect V2 sensor to identify the interest regions and the obstacles of the environment. Our proposal includes a collision-free path planner based on the Rapidly-exploring Random Trees variant (RRT*), for a safe and optimal navigation of robots in 3D spaces. Results on RGB-D segmentation and recognition, point cloud processing, and comparisons between different RRT* algorithms, are presented.

Understanding the Performance of Low Power Raspberry Pi Cloud for Big Data

Abstract: Nowadays, Internet-of-Things (IoT) devices generate data at high speed and large volume. Often the data require real-time processing to support high system responsiveness which can be supported by localised Cloud and/or Fog computing paradigms. However, there are considerably large deployments of IoT such as sensor networks in remote areas where Internet connectivity is sparse, challenging the localised Cloud and/or Fog computing paradigms. With the advent of the Raspberry Pi, a credit card-sized single board computer, there is a great opportunity to construct low-cost, low-power portable cloud to support real-time data processing next to IoT deployments. In this paper, we extend our previous work on constructing Raspberry Pi Cloud to study its feasibility for real-time big data analytics under realistic application-level workload in both native and virtualised environments. We have extensively tested the performance of a single node Raspberry Pi 2 Model B with httperf and a cluster of 12 nodes with Apache Spark and HDFS (Hadoop Distributed File System). Our results have demonstrated that our portable cloud is useful for supporting real-time big data analytics. On the other hand, our results have also unveiled that overhead for CPU-bound workload in virtualised environment is surprisingly high, at 67.2%. We have found that, for big data applications, the virtualisation overhead is fractional for small jobs but becomes more significant for large jobs, up to 28.6%.

A Novel 12-Lead ECG T-Shirt with Active Electrodes

Abstract: We developed an ECG T-shirt with a portable recorder for unobtrusive and long-term multichannel ECG monitoring with active electrodes. A major drawback of conventional 12-lead ECGs is the use of adhesive gel electrodes, which are uncomfortable during long-term application and may even cause skin irritations and allergic reactions. Therefore, we integrated comfortable patches of conductive textile into the ECG T-shirt in order to replace the adhesive gel electrodes. In order to prevent signal deterioration, as reported for other textile ECG systems, we attached active circuits on the outside of the T-shirt to further improve the signal quality of the dry electrodes. Finally, we validated the ECG T-shirt against a commercial Holter ECG with healthy volunteers during phases of lying down, sitting, and walking. The 12-lead ECG was successfully recorded with a resulting mean relative error of the RR intervals of 0.96% and mean coverage of 96.6%. Furthermore, the ECG waves of the 12 leads were analyzed separately and showed high accordance. The P-wave had a correlation of 0.703 for walking subjects, while the T-wave demonstrated lower correlations for all three scenarios (lying: 0.817, sitting: 0.710, walking: 0.403). The other correlations for the P, Q, R, and S-waves were all higher than 0.9. This work demonstrates that our ECG T-shirt is suitable for 12-lead ECG recordings while providing a higher level of comfort compared with a commercial Holter ECG.

A Raspberry Pi Cluster Instrumented for Fine-Grained Power Measurement

Abstract: Power consumption has become an increasingly important metric when building large supercomputing clusters. One way to reduce power usage in large clusters is to use low-power embedded processors rather than the more typical high-end server CPUs (central processing units). We investigate various power-related metrics for seventeen different embedded ARM development boards in order to judge the appropriateness of using them in a computing cluster. We then build a custom cluster out of Raspberry Pi boards, which is specially designed for per-node detailed power measurement. In addition to serving as an embedded cluster testbed, our cluster’s power measurement, visualization and thermal features make it an excellent low-cost platform for education and experimentation.

A wearable system for the evaluation of the human-horse interaction: A preliminary study

Abstract: This study reports on a preliminary estimation of the human-horse interaction through the analysis of the heart rate variability (HRV) in both human and animal by using the dynamic time warping (DTW) algorithm. Here, we present a wearable system for HRV monitoring in horses. Specifically, we first present a validation of a wearable electrocardiographic (ECG) monitoring system for horses in terms of comfort and robustness, then we introduce a preliminary objective estimation of the human-horse interaction. The performance of the proposed wearable system for horses was compared with a standard system in terms of movement artifact (MA) percentage. Seven healthy horses were monitored without any movement constraints. As a result, the lower amount of MA% of the wearable system suggests that it could be profitably used for reliable measurement of physiological parameters related to the autonomic nervous system (ANS) activity in horses, such as the HRV. Human-horse interaction estimation was achieved through the analysis of their HRV time series. Specifically, DTW was applied to estimate dynamic coupling between human and horse in a group of fourteen human subjects and one horse. Moreover, a support vector machine (SVM) classifier was able to recognize the three classes of interaction with an accuracy greater than 78%. Preliminary significant results showed the discrimination of three distinct real human-animal interaction levels. These results open the measurement and characterization of the already empirically-proven relationship between human and horse.

A Comparative Reliability Study of Three Fundamental Multilevel Inverters Using Two Different Approaches

Abstract: The reliability of power electronic devices and components is very important to manufacturers. In recent years, many researchers have conducted reliability assessments of power electronic devices, yet the reliability of numerous circuits used widely has not been evaluated. This paper presents a comprehensive reliability evaluation of fundamental multilevel inverters. The reliability of the multilevel inverters is analyzed by calculating the mean time to failure for each component. The calculation was performed by two methods (approximate and exact) to achieve better comparisons. The approximate method is similar to the parts count method used in MIL-HDBK-217 reliability standard, and the exact method exhibits the parts stress method. In the exact method, due to the direct relationship between component failure and temperature, we used Matlab Simulink to determine power losses in diodes and switches taking into account the temperature factor. The results determined by the approximate method showed that the three-level cascade H-bridge was the most reliable of the inverters considered. Although the exact method validates those results, and shows that cascade H-bridge (CHB) had a longer lifespan, but the calculated values are different. Therefore, using different approaches for evaluating reliability results in different outcomes.

Automatic Measurement of Chew Count and Chewing Rate during Food Intake

Abstract: Research suggests that there might be a relationship between chew count as well as chewing rate and energy intake. Chewing has been used in wearable sensor systems for the automatic detection of food intake, but little work has been reported on the automatic measurement of chew count or chewing rate. This work presents a method for the automatic quantification of chewing episodes captured by a piezoelectric sensor system. The proposed method was tested on 120 meals from 30 participants using two approaches. In a semi-automatic approach, histogram-based peak detection was used to count the number of chews in manually annotated chewing segments, resulting in a mean absolute error of 10.40% ± 7.03%. In a fully automatic approach, automatic food intake recognition preceded the application of the chew counting algorithm. The sensor signal was divided into 5-s non-overlapping epochs. Leave-one-out cross-validation was used to train a artificial neural network (ANN) to classify epochs as "food intake" or "no intake" with an average F1 score of 91.09%. Chews were counted in epochs classified as food intake with a mean absolute error of 15.01% ± 11.06%. The proposed methods were compared with manual chew counts using an analysis of variance (ANOVA), which showed no statistically significant difference between the two methods. Results suggest that the proposed method can provide objective and automatic quantification of eating behavior in terms of chew counts and chewing rates.

Analysis of In-to-Out Wireless Body Area Network Systems: Towards QoS-Aware Health Internet of Things Applications

Abstract: In this paper, an analytical and accurate in-to-out (I2O) human body path loss (PL) model at 2.45 GHz is derived based on a 3D heterogeneous human body model under safety constraints. The bit error rate (BER) performance for this channel using multiple efficient modulation schemes is investigated and the link budget is analyzed based on a predetermined satisfactory BER of 10−3. In addition, an incremental relay-based cooperative quality of service-aware (QoS-aware) routing protocol for the proposed I2O WBAN is presented and compared with an existing scheme. Linear programming QoS metric expressions are derived and employed to maximize the network lifetime, throughput, minimizing delay. Results show that binary phase-shift keying (BPSK) outperforms other modulation techniques for the proposed I2O WBAN systems, enabling the support of a 30 Mbps data transmission rate up to 1.6 m and affording more reliable communication links when the transmitter power is increased. Moreover, the proposed incremental cooperative routing protocol outperforms the existing two-relay technique in terms of energy efficiency. Open issues and on-going research within the I2O WBAN area are presented and discussed as an inspiration towards developments in health IoT applications.

Raspberry Pi: An Effective Vehicle in Teaching the Internet of Things in Computer Science and Engineering

Abstract: The Raspberry Pi is being increasingly adopted as a suitable platform in both research and applications of the Internet of Things (IoT). This study presents a novel project-based teaching and learning approach devised in an Internet of Things course for undergraduate students in the computer science major, where the Raspberry Pi platform is used as an effective vehicle to greatly enhance students’ learning performance and experience. The devised course begins with learning simple hardware and moves to building a whole prototype system. This paper illustrates the outcome of the proposed approach by demonstrating the prototype IoT systems designed and developed by students at the end of one such IoT course. Furthermore, this study provides insights and lessons regarding how to facilitate the use of the Raspberry Pi platform to successfully achieve the goals of project-based teaching and learning in IoT.

On the Application of the Raspberry Pi as an Advanced Acoustic Sensor Network for Noise Monitoring

Abstract: The concept of Smart Cities and the monitoring of environmental parameters is an area of research that has attracted scientific attention during the last decade These environmental parameters are well-known as important factors in their affection towards people Massive monitoring of this kind of parameters in cities is an expensive and complex task Recent technologies of low-cost computing and low-power devices have opened researchers to a wide and more accessible research field, developing monitoring devices for deploying Wireless Sensor Networks Gathering information from them, improved urban plans could be carried out and the information could help citizens In this work, the prototyping of a low-cost acoustic sensor based on the Raspberry Pi platform for its use in the analysis of the sound field is described The device is also connected to the cloud to share results in real time The computation resources of the Raspberry Pi allow treating high quality audio for calculating acoustic parameters A pilot test was carried out with the installation of two acoustic devices in the refurbishment works of a neighbourhood In this deployment, the evaluation of these devices through long-term measurements was carried out, obtaining several acoustic parameters in real time for its broadcasting and study This test has shown the Raspberry Pi as a powerful and affordable computing core of a low-cost device, but also the pilot test has served as a query tool for the inhabitants of the neighbourhood to be more aware about the noise in their own place of residence

Robust and Accurate Algorithm for Wearable Stereoscopic Augmented Reality with Three Indistinguishable Markers

Abstract: In the context of surgical navigation systems based on augmented reality (AR), the key challenge is to ensure the highest degree of realism in merging computer-generated elements with live views of the surgical scene. This paper presents an algorithm suited for wearable stereoscopic augmented reality video see-through systems for use in a clinical scenario. A video-based tracking solution is proposed that relies on stereo localization of three monochromatic markers rigidly constrained to the scene. A PnP-based optimization step is introduced to refine separately the pose of the two cameras. Video-based tracking methods using monochromatic markers are robust to non-controllable and/or inconsistent lighting conditions. The two-stage camera pose estimation algorithm provides sub-pixel registration accuracy. From a technological and an ergonomic standpoint, the proposed approach represents an effective solution to the implementation of wearable AR-based surgical navigation systems wherever rigid anatomies are involved.

Gate Stability of GaN-Based HEMTs with P-Type Gate

Abstract: This paper reports on an extensive investigation of the gate stability of GaN-based High Electron Mobility Transistors with p-type gate submitted to forward gate stress. Based on combined electrical and electroluminescence measurements, we demonstrate the following results: (i) the catastrophic breakdown voltage of the gate diode is higher than 11 V at room temperature; (ii) in a step-stress experiment, the devices show a stable behavior up to VGS = 10 V, and a catastrophic failure happened for higher voltages; (iii) failure consists in the creation of shunt paths under the gate, of which the position can be identified by electroluminescence (EL) measurements; (iv) the EL spectra emitted by the devices consists of a broad emission band, centered around 500–550 nm, related to the yellow-luminescence of GaN; and (v) when submitted to a constant voltage stress tests, the p-GaN gate can show a time-dependent failure, and the time to failure follows a Weibull distribution.

Assessment of a Smart Sensing Shoe for Gait Phase Detection in Level Walking

Abstract: Gait analysis and more specifically ambulatory monitoring of temporal and spatial gait parameters may open relevant fields of applications in activity tracking, sports and also in the assessment and treatment of specific diseases. Wearable technology can boost this scenario by spreading the adoption of monitoring systems to a wide set of healthy users or patients. In this context, we assessed a recently developed commercial smart shoe—the FootMoov—for automatic gait phase detection in level walking. FootMoov has built-in force sensors and a triaxial accelerometer and is able to transmit the sensor data to the smartphone through a wireless connection. We developed a dedicated gait phase detection algorithm relying both on force and inertial information. We tested the smart shoe on ten healthy subjects in free level walking conditions and in a laboratory setting in comparison with an optical motion capture system. Results confirmed a reliable detection of the gait phases. The maximum error committed, on the order of 44.7 ms, is comparable with previous studies. Our results confirmed the possibility to exploit consumer wearable devices to extract relevant parameters to improve the subject health or to better manage his/her progressions.

Domain Specific and Model Based Systems Engineering in the Smart Grid as Prerequesite for Security by Design

Abstract: The development of Smart Grid systems has proven to be a challenging task. Besides the inherent technical complexity, the involvement of different stakeholders from different disciplines is a major challenge. In order to maintain the strict security requirements, holistic systems engineering concepts and reference architectures are required that enable the integration, maintenance and evaluation of Smart Grid security. In this paper, a conceptual approach is presented on how to enable the integration of security by design in the development of Smart Grid Systems. A major cornerstone of this approach is the development of a domain-specific and standards-based modelling language on basis of the M/490 Smart Grid Architecture Model (SGAM). Furthermore, this modelling approach is utilized to develop a reference architecture model on basis of the National Institute of Standards and Technology (NIST) Logical Reference Model (LRM) with its integrated security concepts. The availability of a standards-based reference architecture model enables the instantiation of particular solutions with a profound basis for security. Moreover, it is demonstrated how such architecture models can be utilized to gain insights into potential security implications and furthermore can serve as a basis for implementation.

Skin Admittance Measurement for Emotion Recognition: A Study over Frequency Sweep

Abstract: The electrodermal activity (EDA) is a reliable physiological signal for monitoring the sympathetic nervous system. Several studies have demonstrated that EDA can be a source of effective markers for the assessment of emotional states in humans. There are two main methods for measuring EDA: endosomatic (internal electrical source) and exosomatic (external electrical source). Even though the exosomatic approach is the most widely used, differences between alternating current (AC) and direct current (DC) methods and their implication in the emotional assessment field have not yet been deeply investigated. This paper aims at investigating how the admittance contribution of EDA, studied at different frequency sources, affects the EDA statistical power in inferring on the subject’s arousing level (neutral or aroused). To this extent, 40 healthy subjects underwent visual affective elicitations, including neutral and arousing levels, while EDA was gathered through DC and AC sources from 0 to 1 kHz. Results concern the accuracy of an automatic, EDA feature-based arousal recognition system for each frequency source. We show how the frequency of the external electrical source affects the accuracy of arousal recognition. This suggests a role of skin susceptance in the study of affective stimuli through electrodermal response.

Simulation of 50-nm Gate Graphene Nanoribbon Transistors

Abstract: An approach to simulate the steady-state and small-signal behavior of GNR MOSFETs (graphene nanoribbon metal-semiconductor-oxide field-effect transistor) is presented. GNR material parameters and a method to account for the density of states of one-dimensional systems like GNRs are implemented in a commercial device simulator. This modified tool is used to calculate the current-voltage characteristics as well the cutoff frequency fT and the maximum frequency of oscillation fmax of GNR MOSFETs. Exemplarily, we consider 50-nm gate GNR MOSFETs with N = 7 armchair GNR channels and examine two transistor configurations. The first configuration is a simplified MOSFET structure with a single GNR channel as usually studied by other groups. Furthermore, and for the first time in the literature, we study in detail a transistor structure with multiple parallel GNR channels and interribbon gates. It is shown that the calculated fT of GNR MOSFETs is significantly lower than that of GFETs (FET with gapless large-area graphene channel) with comparable gate length due to the mobility degradation in GNRs. On the other hand, GNR MOSFETs show much higher fmax compared to experimental GFETs due the semiconducting nature of the GNR channels and the resulting better saturation of the drain current. Finally, it is shown that the gate control in FETs with multiple parallel GNR channels is improved while the cutoff frequency is degraded compared to single-channel GNR MOSFETs due to parasitic capacitances of the interribbon gates.

Low Delay Video Streaming on the Internet of Things Using Raspberry Pi

Abstract: The Internet of Things is predicted to consist of over 50 billion devices aiming to solve problems in most areas of our digital society. A large part of the data communicated is expected to consist ...

A Fabric-Based Approach for Wearable Haptics

Abstract: In recent years, wearable haptic systems (WHS) have gained increasing attention as a novel and exciting paradigm for human–robot interaction (HRI). These systems can be worn by users, carried around, and integrated in their everyday lives, thus enabling a more natural manner to deliver tactile cues. At the same time, the design of these types of devices presents new issues: the challenge is the correct identification of design guidelines, with the two-fold goal of minimizing system encumbrance and increasing the effectiveness and naturalness of stimulus delivery. Fabrics can represent a viable solution to tackle these issues. They are specifically thought “to be worn”, and could be the key ingredient to develop wearable haptic interfaces conceived for a more natural HRI. In this paper, the author will review some examples of fabric-based WHS that can be applied to different body locations, and elicit different haptic perceptions for different application fields. Perspective and future developments of this approach will be discussed.

Wearable multimodal skin sensing for the diabetic foot

Abstract: Ulceration of the diabetic foot is currently difficult to detect reliably in a timely manner causing undue suffering and cost. Current best practice is for daily monitoring by those living with diabetes coupled to scheduled monitoring by the incumbent care provider. Although some metrics have proven useful in the detection or prediction of ulceration, no single metric can currently be relied upon for diagnosis. We have developed a prototype multivariate extensible sensor platform with which we demonstrate the ability to gather acceleration, rotation, galvanic skin response, environmental temperature, humidity, force, skin temperature and bioimpedance signals in real time, for later analysis, utilising low cost Raspberry Pi and Arduino devices. We demonstrate the utility of the Raspberry Pi computer in research which is of particular interest to this issue of electronics—Raspberry Pi edition. We conclude that the hardware presented shows potential as an adaptable research tool capable of gathering synchronous data over multiple sensor modalities. This research tool will be utilised to optimise sensor selection, placement and algorithm development prior to translation into a sock, insole or platform diagnostic device at a later date. The combination of a number of clinically relevant parameters is expected to provide greater understanding of tissue state in the foot but requires further volunteer testing and analysis beyond the scope of this paper which will be reported in due course.

Analysis and Design of a DSTATCOM Based on Sliding Mode Control Strategy for Improvement of Voltage Sag in Distribution Systems

Abstract: Voltage sag is considered to be the most serious problem of power quality. It is caused by faults in the power system or by the starting of large induction motors. Voltage sag causes about 80% of the power quality problems in power systems. One of the main reasons for voltage sag is short circuit fault, which can be compensated for by a distribution static compensator (DSTATCOM) as an efficient and economical flexible AC transmission system (FACTS) device. In this paper, compensation of this voltage sag using DSTATCOM is reviewed, in which a sliding mode control (SMC) technique is employed. The results of this control system are compared with a P+Resonant control system. It will be shown that this control system is able to compensate the voltage sag over a broader range compared to other common control systems. Simulation results are obtained using PSCAD/EMTDC software and compared to that of a similar method.

A Multi-Modal Sensing Glove for Human Manual-Interaction Studies

Abstract: We present an integrated sensing glove that combines two of the most visionary wearable sensing technologies to provide both hand posture sensing and tactile pressure sensing in a unique, lightweight, and stretchable device. Namely, hand posture reconstruction employs Knitted Piezoresistive Fabrics that allows us to measure bending. From only five of these sensors (one for each finger) the full hand pose of a 19 degrees of freedom (DOF) hand model is reconstructed leveraging optimal sensor placement and estimation techniques. To this end, we exploit a-priori information of synergistic coordination patterns in grasping tasks. Tactile sensing employs a piezoresistive fabric allowing us to measure normal forces in more than 50 taxels spread over the palmar surface of the glove. We describe both sensing technologies, report on the software integration of both modalities, and describe a preliminary evaluation experiment analyzing hand postures and force patterns during grasping. Results of the reconstruction are promising and encourage us to push further our approach with potential applications in neuroscience, virtual reality, robotics and tele-operation.

A Robust Automated Cataract Detection Algorithm Using Diagnostic Opinion Based Parameter Thresholding for Telemedicine Application

Abstract: This paper proposes and evaluates an algorithm to automatically detect the cataracts from color images in adult human subjects. Currently, methods available for cataract detection are based on the use of either fundus camera or Digital Single-Lens Reflex (DSLR) camera; both are very expensive. The main motive behind this work is to develop an inexpensive, robust and convenient algorithm which in conjugation with suitable devices will be able to diagnose the presence of cataract from the true color images of an eye. An algorithm is proposed for cataract screening based on texture features: uniformity, intensity and standard deviation. These features are first computed and mapped with diagnostic opinion by the eye expert to define the basic threshold of screening system and later tested on real subjects in an eye clinic. Finally, a tele-ophthamology model using our proposed system has been suggested, which confirms the telemedicine application of the proposed system.

Developing an affordable and portable control systems laboratory kit with a Raspberry Pi

Abstract: Instructional laboratories are common in engineering programs. Instructional laboratories should evolve with technology and support the changes in higher education, like the increased popularity of online courses. In this study, an affordable and portable laboratory kit was designed to replace the expensive on-campus equipment for two control systems courses. The complete kit costs under $135 and weighs under 0.68 kilograms. It is comprised of off-the-shelf components (e.g., Raspberry Pi, DC motor) and 3D printed parts. The kit has two different configurations. The first (base) configuration is a DC motor system with a position and speed sensor. The second configuration adds a Furuta inverted pendulum attachment with another position sensor. These configurations replicate most of the student learning outcomes for the two control systems courses for which they were designed.

A Compressive-Sensing Inspired Alternate Projection Algorithm for Sparse Array Synthesis

Abstract: In this paper, we propose a simple approach for sparse array synthesis. We employ a modified generalized alternate projection algorithm using l 1 -norm constrained minimization in order to achieve the excitation and the position of the elements of a sparse array. The proposed approach is very flexible, since it deals with power pattern masks and allows the inclusion of the effects of element pattern and mutual coupling. Its implementation is relatively simple, thanks to the possibility to use well-known convex programming techniques. The presented method is particularly suitable for the synthesis of patterns commonly employed in radar systems; the numerical results provided show good performances with respect to concurrent methods available in open literature.

On the Implementation of the IEC 61850 Standard: Will Different Manufacturer Devices Behave Similarly under Identical Conditions?

Abstract: Standardization in smart grid communications is necessary to facilitate complex operations of modern power system functions. However, the strong coupling between the cyber and physical domains of the contemporary grid exposes the system to vulnerabilities and thus places more burden on standards’ developers. As such, standards need to be continuously assessed for reliability and are expected to be implemented properly on field devices. However, the actual implementation of common standards varies between vendors, which may lead to different behaviors of the devices even if present under similar conditions. The work in this paper tested the implementation of the International Electro-technical Commission’s Generic Object Oriented Substation Event GOOSE (IEC 61850 GOOSE) messaging protocol on commercial Intelligent Electronic Devices (IEDs) and the open source libiec61850 library—also used in commercial devices—which showed different behaviors in identical situations. Based on the test results and analysis of some features of the IEC 61850 GOOSE protocol itself, this paper proposes guidelines and recommendations for proper implementation of the standard functionalities.

Photonic Structure-Integrated Two-Dimensional Material Optoelectronics

Abstract: The rapid development and unique properties of two-dimensional (2D) materials, such as graphene, phosphorene and transition metal dichalcogenides enable them to become intriguing candidates for future optoelectronic applications. To maximize the potential of 2D material-based optoelectronics, various photonic structures are integrated to form photonic structure/2D material hybrid systems so that the device performance can be manipulated in controllable ways. Here, we first introduce the photocurrent-generation mechanisms of 2D material-based optoelectronics and their performance. We then offer an overview and evaluation of the state-of-the-art of hybrid systems, where 2D material optoelectronics are integrated with photonic structures, especially plasmonic nanostructures, photonic waveguides and crystals. By combining with those photonic structures, the performance of 2D material optoelectronics can be further enhanced, and on the other side, a high-performance modulator can be achieved by electrostatically tuning 2D materials. Finally, 2D material-based photodetector can also become an efficient probe to learn the light-matter interactions of photonic structures. Those hybrid systems combine the advantages of 2D materials and photonic structures, providing further capacity for high-performance optoelectronics.