Miracle-dz/UniFAR-FTUs huggingface dataset:
Compact K-Band Lange Coupler Based 2-Bit RF MEMS Reflection-Type Phase Shifter

Lange Coupler and low-loss shunt DC contact Microelectromechanical System (MEMS) switches have been implemented which in turn reduces the loss of the reflection-type MEMS phase shifter (RTPS) at K-band. ON-OFF mechanism of respective switches in both arms, changes the length of the short-ended stubs which introduces the respective phase changes double of the phase given by the path length. Simulated work of this 2-bit (135°) RTPS shows an average insertion loss of less than 1.1 dB with return loss better than 13.5 dB from 15 to 25 GHZ. The designed phase shifter occupies small area of 1.76 mm × 2.45 mm. The measured maximum phase error between 135° and 90° phase states is 1.15° about 20 GHz frequency.
On the Impact of Device Characteristics on Opportunistic Network Performance

With smartphones gaining relevance in everyone's regular day more than ever, the application of opportunistic networks on those devices has become a popular field of research, as it enables smartphones to connect locally with high bandwidth and to provide networked applications for regional use. Conventional Delay Tolerant Networks and opportunistic network methods and techniques however cannot be directly applied on smartphones. Challenges are brought up by missing ad-hoc communication possibilities and system architecture constraints. Through tethering hotspot-based communication it is possible to create opportunistic networks for smartphones, although with specific network characteristics. We conduct a survey on the impact of device characteristics and network transmission properties on the overall network performance. Using the ONE simulator, we deploy a tethering hotspot-based connection strategy and, as the main contribution of this paper, asses the influence of single device properties onto the global opportunistic network performance. By applying a Linear Regression, we conclude a device's radio transmission range as the most significant factor one should consider when designing algorithms for smartphone-based opportunistic networks.
State Encoding with Stochastic Numbers for Transient Fault Tolerant Linear Finite State Machines

Stochastic computing (SC) has attractive characteristics, compared with deterministic (or general binary) computing, such as smaller area of the implemented circuits, higher fault tolerance and so on. This study focuses on the transient fault tolerance of SC circuits with linear finite state machines (linear FSMs). To improve the transient fault tolerability of linear-FSM-based SC circuits, we propose a scheme for encoding the states of the FSM with stochastic numbers (SNs). Moreover, we discuss approximating state transition of the FSM so as to reduce the area overhead. The proposed SC circuits are modeled as Markov processes to clarify their behaviors when any transient fault occurs. Experimental results clarify the improvement in the fault tolerability of the SC circuits based on the proposed state encoding with SNs.
A Robust Modified Harmony Search Evolutionary Technique for Transient Stability Enhancement in a Two Machine System Through STATCOM

Nowadays the increasing complexity and dimensionality of modern power systems have given rise to low frequency electromechanical oscillations (LFOs). These oscillations pose a major threat to the stability of power system and cause unnecessary limitations to its smooth operation. For the fast damping of system and successful mitigation of oscillations, Flexible AC Transmission System (FACTS) devices are utilized. Static Synchronous Compensator (STATCOM) is one such versatile shunt connected FACTS device that controls the bus voltage influencing the power flow and enhancing the transient stability of the system very fast because no moving parts are involved. However the PID controller of STATCOM is a linear controller that cannot respond effectively to non linear power system. Hence taking non linearities into account, the PID controller of STATCOM is tuned dynamically with a very robust and powerful meta heuristic optimization technique called harmony search inspired from improvisation process of jazz musician. It is a relatively recent technique that is considered superior because of its easy execution and reduced modifiable parameters. However it also has some noticeable defects like less convergence speed and premature convergence. To overcome the shortcomings of HS, a Modified Harmony Search (M-HS) is proposed in this paper to obtain much better transient as well as dynamic stability results. To justify and validate the effectiveness of M-HS optimized PID in reducing oscillations it is compared and contrasted with HS optimized PID and conventional PID of STATCOM using MATLAB/SIMULINK environment. Furthermore the THD calculation in each case is carried out. The results depict the efficacy and potential of M-HS techniques over HS and conventional PID controller in damping out oscillations and restoring system stability.
Disturbance-Observer-Based Tracking Control for A Two-Link Robotic Manipulators with External Disturbances

In this paper, two tracking control laws are designed for two-link robotic manipulators with external disturbances. A new nonlinear disturbance observer (NDO) is studied, and the global asymptotic stability of the given disturbance observer is guaranteed by appropriate assumptions on the system parameters and the physical structure. By utilizing the NDO, a nonlinear tracking controller is presented in the present of dissipation force and friction force. The tracking errors converge to zero by tuning the designed parameters. In addition, the sliding-mode-based tracking controller is also discussed. A simulation example is given to show the validity of the control algorithms.
A Novel Axial-Flux-Complementary Doubly Salient Machine With Boosted PM Utilization for Cost-Effective Direct-Drive Applications

This paper proposes a novel axial-flux-complementary doubly salient machine (AFC-DSM) for cost-effective direct-drive applications. The key is to coordinate two complementary rotors with inset stator permanent magnets (PMs) circumferentially magnetized to construct an axially complementary flux return path in machine. Different from the traditional stator-PM machines, the excitation flux is transferred between the complementary rotors, hence switched smoothly without been shorted or opened in the air gaps. As a result, the PM utilization in the proposed machine can be doubled compared to that in traditional stator PM machine. In addition, the proposed machine also contributes to reduced cogging torque, higher winding utilization factor and neglectable mutual inductance, which helps to improve its torque performance as well as fault-tolerant capability. The electromagnetic performance is evaluated by 3-D finite element analysis, and the simulation results verify the effectiveness of the proposed machine.
Control of wind power smoothing with battery energy storage system and thermostatically controlled loads

Due to inherent variability and intermittency of renewable energy, high penetration of renewable energy in the current electricity market could be difficult to achieve. Use of energy storage units and controllable loads are some of the feasible solutions to regulate renewable energy. The basic idea is to store/consume part of the generated renewable energy so that the actual power dispatched to the utility grid can meet the ramp rate requirements. In this paper, we propose a wind power smoothing strategy with the coordination of a battery energy storage system (BESS) and thermostatically controlled loads (TCLs). We considered a group of cooling TCLs, and the unsmoothed wind power will be regulated by them to minimize its fluctuation first, followed using a dynamic programming-based algorithm to determine a set of BESS actions that adjust the actual power delivered to the grid and reduce the operational cost of BESS. The rolling horizon approach is utilized with predicted wind power and ambient temperature data updated at each control step. The strategy is tested with practical data.
Phase-amplitude coupling between mu- and gamma-waves to carry motor commands

The development of brain computer interfaces, especially the ones related to controlling exoskeletons and neurorehabilitation of stroke patients, strongly relies on our understanding of motor system and its neuronal mechanism. Motor imagery (MI) has turned out to be one of the most popular experimental regimes to study this system. Kinesthetic imagery (KI) is a kind of MI which shares a large portion of its neuronal pathway with real movements, except for having an additional inhibitory mechanism to prevent movement execution. Our magnetoencephalographic (MEG) experiments with ten untrained subjects revealed that this inhibitory control implied local neuronal desynchronization. We found that the motor-related communication between the inferior parietal cortex and the prefrontal cortex was carried out using the mu-frequency range. Additionally, three gamma frequencies were also pinpointed that encode the motor command specifics. Using artificial neural networks (ANNs) we classified left- and right-hand MI which reached maximal accuracy when we included these three gamma frequencies in the input signal for ANN. We suggest that mu-activity acts as a carrier of gamma-activity between inferior and parietal areas utilising phase-amplitude coupling.
+16 dBm High Power and High Linearity Integrated Photoreceiver for W-band Fiber Wireless Communication Applications

We designed and fabricated an 80-GHz range high-power integrated photoreceiver that is operated using a zero-bias operational broadband uni-traveling carrier photodetector and a high-gain narrow-band amplifier. The results showed that by applying a single power supply to the amplifier, the integrated photoreceiver could exhibit a higher power output at 1-dB power compression, i.e., over +16 dBm, and a 3-dB bandwidth of 6.5 GHz at 83 GHz.
Learning-Based Instantaneous Drowsiness Detection Using Wired and Wireless Electroencephalography

Instantaneous drowsiness (<italic>i.e.,</italic> lapse or micro-sleep) during various activities such as driving or construction causes enormous socioeconomic losses. Thus, a virtuous cycle system that monitors a subject’s drowsiness can improve work efficiency and safety. We propose a novel framework to detect instantaneous drowsiness with only a two-second length of electroencephalography (EEG). To achieve reliable performance, we use multitaper power spectral density for feature extraction along with extreme gradient boosting as a machine learning classifier. In addition, we introduce a novel phenotype labeling of instantaneous drowsiness by combining both task dependent and independent measures of alertness (psychomotor vigilance task and electrooculography technique, respectively). The results show that our techniques outperform others used in previous studies. We also identified which spectral components (<inline-formula> <tex-math notation="LaTeX">$\theta $ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">$\alpha $ </tex-math></inline-formula>, and <inline-formula> <tex-math notation="LaTeX">$\gamma $ </tex-math></inline-formula>) and channels (Fp1, Fp2, T3, T4, O1, O2, and electrocardiogram) play important roles in our drowsiness detection framework. To verify the applicability for a mobile environment, we implemented our framework on a wireless EEG, as well as on a wired EEG. We hereby present our successful results.
A Filtering Based Recursive Extended Least Squares Identification Algorithm

Based on the standard recursive generalized extended least squares (RGELS) algorithm and the filtering based recursive least squares (F-RLS) algorithm, a new type of filtering based algorithm is presented for ARARMAX model in this paper. The core idea is to transform the ARARMAX model into an ARMAX model by introducing a filter for the input and output data. With such a treatment, the system can be decomposed into two subsystems. Then, a recursive identification algorithm is constructed by replacing immeasurable terms in information vectors with their estimates respectively. A numerical simulation example is employed to show the effectiveness of the proposed algorithm.
Optimization of Data Fitting Algorithm for Tissue Dielectric Properties in THz-band using Genetic Algorithm

The non-linear least squares method (NLLS) is often used to extract the double Debye parameters. However, to solve NLLS, the traditional numerical iteration method depends heavily on the initial values. This paper provides a method to optimize the algorithm, using genetic algorithm (GA) to acquire suitable initial values for the numerical iteration method. Computer simulations show that the optimized algorithm extracts more accurate double Debye parameters and fits the data better.
In vitro culture and isoenzyme analysis of giardia lamblia.

Giardia lamblia, an enteric protozoan parasite, infects a large number of individuals worldwide. In South Africa prevalences ranging between 4 and 63% are documented, however, the impact of giardiasis is underreseached in this country. Giardia infections vary from asymptomatic carriage or a self-limiting acute symptomatic illness to chronic, debilitating malabsorption syndrome. The factors responsible for development of symptomatic versus asymptomatic infection are poorly understood. It is believed by some that host factors determine the clinical outcome of infection. On the other hand, the possibility of the existence of pathogenic and non-pathogenic strains (a situation akin to Entamoeba spp.) remains to be explored. One requirement for investigation of the potential contribution of strain differences to pathogenecity of infection is establishment of laboratory cultures of different strains isolated from symptomatic and asymptomatic patients. The present study was undertaken to develop and modify existing methods for: (i) establishment of laboratory cultures of Giardia trophozoites from excystation of faecal cysts, (ii) long-term maintenance and cryopreservation of the cultures and (iii) preliminary characterisation methodology. One thousand and twenty-three stool specimens were collected from day care centres, hospital wards and Hlabisa hospital laboratory. A further 6246 were retrieved from the Microbiology Laboratory at King Edward VIII Hospital and screened by direct wet preparation. Giardia was detected by light microscopy following formol-ether concentration (127 of 1023 samples) or direct examination of wet preparations (78 of 6246 samples). Cysts were purified from
Optimization Design for Structure Parameters of Six Degree-of-Freedom (DOF) Positioner of Secondary Mirror in a Space Optical Remote Sensor Based on ADAMS

In space optical remote sensor, the relative position and orientation of primary mirror and secondary mirror have important influence on high quality imaging. Adjusting the secondary mirror pose is one of the means to improve the imaging quality of space camera. In order to meet the requirements of secondary mirror pose adjustment and improve the performance and economy of the mechanism, the Stewart platform, a typical kind of 6-DOF parallel mechanism, is optimized. Firstly, a parametric model of the Stewart platform is established in ADAMS. Secondly, the optimal objective function of the Stewart platform is established. Thirdly, According to the actual constraint conditions, the constraint function is set up. Finally, the ADAMS simulation software is used to add objective function and constraint functions to optimize the structure parameters and optimized structural parameters are obtained. After parameter checking, all indexes of the optimized secondary mirror positioner meet the requirements.
Sewing Bioprobe

Referring to the conventional sewing mechanism using a sewing needle and thread, here we propose a flexible ‘thread’ bioprobe device, which is sewn to the biological tissue by guiding tungsten-microneedle. The thread bioprobe was fabricated by parylene-based MEMS process. The fabricated bioprobe was sewn to the mouse's muscle and platinum (Pt)-microelectrodes in the bioprobe device detected electromyography (EMG) signals. Similar to sewing the device to the muscle, the flexible bioprobe also penetrated through the mouse's brain tissue and detected light evoked neuronal activity. Compared to conventional rigid microelectrode (e.g., silicon needle), the proposed sewing bioprobe device offers i) minimization of tissue damage due to the device flexibility, ii) device (microelectrode) placement at precise position in the tissue, and iii) attachment of the device to the tissue for both acute and chronic applications.
An Approach for Detecting Power Peaks During Testing and Breaking Systematic Pathological Behavior

The verification and validation process of embedded critical systems requires providing evidence of their functional correctness and also that their non-functional behavior stays within limits. In this work, we focus on power peaks, which may cause voltage droops and thus, challenge performance to preserve correct operation upon droops. In this line, the use of complex software and hardware in critical embedded systems jeopardizes the confidence that can be placed on the tests carried out during the campaigns performed at analysis. This is so because it is unknown whether tests have triggered the highest power peaks that can occur during operation and whether any such peak can occur systematically. In this paper we propose the use of randomization, already used for timing analysis of real-time systems, as an enabler to guarantee that (1) tests expose those peaks that can arise during operation and (2) peaks cannot occur systematically inadvertently.
Le traitement de l'hépatite chronique C est-il aussi efficace dans la population générale que dans les essais randomisés ?

Objectif-Etudier les modalites et les resultats du traitement de l'hepatite C dans une population generale. Methode - Ce travail a ete realise a partir de toutes les nouvelles serologies positives d'hepatite C recenses par le registre des hepatites virales entre 1994 et 1999 chez des personnes residant en Cote-d'Or et dans le Doubs (1 005 817 habitants). Resultats - L'etude a porte sur 1 251 des 1 508 cas recenses; 262 d'entre eux ont ete traites. Le resultat du traitement etait connu dans 238 cas (157 monotherapies interferon et 81 bitherapies interferonribavirine). Une reponse virologique prolongee etait observee dans 18,0 % apres monotherapie, et dans 46,9 % apres bitherapie. En analyse multivariee, l'âge < 40 ans et la bitherapie etaient positivement associes a la reponse virologique durable. Le taux de reponse virologique durable etait abaisse par un arret premature du traitement; il etait independant du sexe et du degre de fibrose. Cinquante-six malades ont eu une bitherapie apres echec d'une monotherapie: une reponse virologique durable a ete observee chez 33,3% des repondeurs-rechuteurs et 23,7% des non-repondeurs a la monotherapie. Conclusions - Cette etude indique que si une faible proportion des cas diagnostiques beneficie d'un traitement dans une population generale, les resultats de ce traitement sont tout a fait comparables a ceux des etudes hospitalieres chez des malades tres selectionnes. Cela justifie les efforts des poles et reseaux pour ameliorer l'acces aux soins des malades atteints d'hepatite C.
A Survey on Android Malware and their Detection Techniques

The usage of Smartphones is increasing very fast. All the private and confidential information is stored in smartphones. The popularity of Android is also increased massively. Android offers a large number of applications free of cost to be downloaded and used. Statistics revealed that Android phones are more vulnerable to malware. This paper analyses different kinds of malware, their detection techniques with pros and cons and their future scope.
Adaptive Observer based Fault Tolerant Control for Aircraft Engine with Sensors and Actuators Faults

The fault tolerant control on the basis of adaptive observer for aircraft engine with both sensors faults and actuators faults is considered in this paper. The adaptive observer can reconstruct the fault signal when the sensors and actuators faults appear simultaneously. And the obtained fault estimation signals are sent to the input and output terminals of the controller respectively to offset the faults of actuators and sensors. The aircraft engine fault tolerant control system is constructed as a result. It is proven that the faults estimation errors are stable by Lyapunov theory. Simulation on the two typical operation points of aircraft engine shows that the fault tolerant control system can effectively reduce the impact of sensor and actuator failures on the system.
Drugs Reviews Sentiment Analysis using Weakly Supervised Model*

The enormous amounts of vital data available in social media and health forums containing the expression of customers comments have recently provided resources for the research of Adverse Drug Reactions (ADRs) identification. However, in the existing methods, the neglect of noise data and the need for manual labeled data reduce the accuracy of prediction results and greatly increase human labor when applying social comment data. Based on the drug reviews of patients’ feedback, our objective is to recognize the sentiment inclination (positive/negative) of drug reviews by sentiment analysis for ADRs identification. Firstly, this paper proposes a weakly supervised mechanism (WSM) that applies the weakly labeled data to pre-train the parameters of the model then use labeled data to fine-tune initialed parameters, which reduces the effect of noise data on the consequences. Secondly, we present a novel architecture applys the WSM and combines the strength of Convolutional Neural Network (CNN) and Bi-directional Long Short-term Memory (Bi-LSTM) named as WSM-CNN-LSTM to complete the task for ADR reviews sentiment classification. Finally, experimental results demonstrate that our model marginally out-performes the comparison models in ADR identification and a small quantity of ADR-labeled examples are needed to attain optimal performance, which declines the influence of noise and reduces the manual labeled data.
An Improved Observation Model for Monte-Carlo Localization Integrated with Reliable Reflector Prediction*

Robust and reliable localization is a fundamental prerequisite for many applications of mobile robots which can be achieved in many ways. Among them, landmark-based localization is a proven and practical technique. However, incorrect detection of landmarks can seriously affect the positioning result. This paper presents an improved observation model for Monte-Carlo localization (MCL), which improves the robustness of localization by reliable reflector prediction in the ambiguous environments caused by incorrect reflectors detection. This improved observation model is based on a Bayesian network into which the reflective intensity of LIDAR and the labeled grid-map are considered. And then, a reflector probability field and a learned intensity observation model are proposed to accomplish fast probabilistic inference of robot pose based on our improved observation mode. Also, a variant MCL, called reflector prediction-based Monte-Carlo localization (RP-MCL) is realized based on our observation model. The effectiveness of the RP-MCL is verified in real-world scenarios using our self-developed robot and the results demonstrate that our observation model improves the localization performance in the ambiguous environments.