Miracle-dz/UniFAR-FTUs huggingface dataset:
Multivariate Pattern Analysis of EEG-Based Functional Connectivity: A Study on the Identification of Depression

Resting-state electroencephalography (EEG) studies have shown significant group differences in functional connectivity networks between patients with depression and healthy controls. The present study aims to identify the altered EEG resting-state functional connectivity patterns of depressed patients, which can be used to test the feasibility of distinguishing individuals with depression from healthy controls. In the present study, the phase lag index was employed to construct functional connectivity matrices. An altered Kendall rank correlation coefficient was used to identify the features with high discriminative power, and several classifiers were employed to classify a total of 27 depressed patients and 28 demographically matched healthy volunteers. Permutation tests were used to evaluate classifier performance. The best classification results demonstrate that more than 92% of subjects were correctly classified by binary linear SVM through leave-one-out cross-validation for the full frequency band, and the AUC was 0.98. Our findings suggest that the depression affects brain activity in nearly the whole cortex and that changes in brain oscillation patterns in the delta, theta, and beta frequency bands are more significant than those in the alpha frequency band. The current study sheds new light on the pathological mechanism of depression and suggests that EEG resting-state functional connectivity analysis may identify potentially effective biomarkers for its clinical diagnosis.
Considerations of Integrating Computing-In-Memory and Processing-In-Sensor into Convolutional Neural Network Accelerators for Low-Power Edge Devices

In quest to execute emerging deep learning algorithms at edge devices, developing low-power and low-latency deep learning accelerators (DLAs) have become top priority. To achieve this goal, data processing techniques in sensor and memory utilizing the array structure have drawn much attention. Processing-in-sensor (PIS) solutions could reduce data transfer; computing-in-memory (CIM) macros could reduce memory access and intermediate data movement. We propose a new architecture to integrate PIS and CIM to realize low-power DLA. The advantages of using these techniques and the challenges from system point-of-view are discussed.
Network Monitoring Enhancement based on Mathematical Modeling

Information about the network status can be obtained by analyzing the monitored network traffic. Because the network traffic is huge in size and is continuously varying in time, the process of analyzing the monitored traffic is extremely difficult and time and space consuming. To keep the monitoring system running, the administrator has to manage a trade-off between the amount of derived significant information vs. monitoring process complexity vs. time and space availability. This paper proposes a method that can simplify the administrator's work as well as the monitoring process of, without sacrificing significant information about the network. The proposed method presents a mathematical model that decomposes the monitored network traffic into two main parts: significant traffic and non-significant traffic. The decomposition rules are implemented based on experimental observations of the monitored network. Basic experiments show that the proposed mathematical model decomposes the network traffic based on the selected rules, and the model achieves a traffic reduction of approximately 80%.
Development of E-mail Delivery Mediation System Based on Interruptibility and Its Evaluation in Daily Office Work Scenario

Notifications of e-mail arrivals at inappropriate times disrupt workers engaged in intellectual activities and reduce their productivity. We propose an e-mail delivery mediation system to deal with this issue. The system suspends e-mail delivery and estimates users’ interruptibility from their PC operation activities. Then, it delivers e-mail only when the estimated interruptibility matches certain delivery criteria, especially when a user switches applications. A long-term evaluation in a real office revealed that e-mail mediation based on the system’s estimates of user interruptibility can shift a certain percentage of the notifications to task or subtask breakpoints or to times at which the user is less engaged in a task.
Algebraic Patterns of Vulnerabilities in Binary Code

This paper presents an algebraic approach for formalizing and detecting vulnerabilities in binary code. It uses behaviour algebra equations for creating patterns of vulnerabilities and algebraic matching methods for vulnerability detection. Algebraic matching is based on symbolic modelling. This paper considers a known vulnerability, buffer overflow, as an example to demonstrate an algebraic approach for pattern creation.
Design of an Adaptive Multi-Channel Algorithm in WLANs

The IEEE 802.11 specification for Wireless Local Area Networks (WLANs) supports multichannel transmissions up to the 160 MHz band. However, inefficiencies arise when the entire bandwidth is allocated for a single user and when the size of the transmitted data is very small. In this paper, we propose a novel medium access control method, which is called the Adaptive Multi-Channel Access (AMCA) protocol, for an ad hoc wireless network. The AMCA enables simultaneous transmissions to multiple stations on different channels. We implement and evaluate the AMCA using the MATLAB platform. In addition, we compare the AMCA with the IEEE 802.11 multichannel and the IEEE 802.11 single channel. The simulation results show that the adaptive common channel method for the coordination of the channel use allocation between the STAs offers a similar performance to the IEEE 802.11.
Position-Based Control of Under-Constrained Haptics: A System for the Dexmo Glove

The Dexmo glove is a haptic exoskeleton that provides kinesthetic feedback in virtual reality. Unlike many other gloves based on string–pulleys, the Dexmo uses a free-hinged link-bar to transfer forces from a crank to the fingertips. It also uses an admittance-based controller parameterized by position, as opposed to an impedance-based controller parameterized by force. When setting the controller's target position, developers must use its native angular coordinate system. The Dexmo has a number of uninstrumented degrees of freedom. Mature forward models can reliably predict the hand pose, even with these unknowns. When it comes to computing angular controller parameters from a target pose in Cartesian space however, things become more difficult. Complex models that provide attractive visuals from a small number of sensors can be non-trivial or even impossible to invert. In this letter, we suggest side-stepping this issue. We sample the forward model in order to build a lookup table. This is embedded in three-dimensional space as a curve, on which traditional queries against world geometry can be performed. Controller parameters are stored as attributes of the sample points. To compute the driver parameters for a target position, the application constrains the position to the geometry, and interpolates them. This technique is generalizable, stable, simple, and fast. We validate our approach by implementing it in Unity 2017.3 and integrating it with a Dexmo glove.
Designing a Metasurface-based Tag Antenna for Wearable Vital Sign Sensors

This paper aims to design a tag antenna with metasurfaces for use in a wearable vital-sign sensing system. The system is based on a bistatic self-injection-locked (SIL) radar that consists of a chest-worn SIL oscillator (SILO) tag and a wireless handheld receiver. A frequency selective surface (FSS) and an electromagnetic bandgap (EBG) surface are placed on the front and back side of the tag antenna to reduce the influence of moving clutter and body proximity, respectively, on the system. In the experiment, a 5.8 GHz prototype system was implemented with the proposed tag antenna to monitor vital signs of a wearer who was walking in place.
Analysis of Anisotropic Inhomogeneous Dielectric Waveguides With Discrete Mode Matching Method

The aim of this paper is to present the extension of the discrete mode matching (DMM) method to analyze multilayered microwave structures with inhomogeneous dielectric layers. The structures with lossy and/or anisotropic (both electric and magnetic) material are taken into consideration. The procedure involves the use of a full-wave equivalent circuit to obtain the system equation. The mathematical formulation is presented, and its application is demonstrated by analyzing various waveguide structures. The validation has been done with open literature and good agreement has been observed between the results.
Novel Approach to Design DPL-based Ternary Logic Circuits

Present paper introduces a novel strategy to design Double Pass-transistor Logic (DPL)based Ternary (base-3)logic circuit in favour of wave-pipelined applications. Ternary can be a feasible candidate to replace conventional binary (base-2)number system due to faster computation, reduced interconnect complexity, reduced fan-in/fan-out, less storage requirement and so on. Careful design with proper coarse and fine tuning of wave-pipelined circuit can improve the overall performance and reliability of digital SOC. DPL is a favourable candidate for wave-pipelining and is employed in this work. Ternary digit (“trit”)value “0”, “1” and “2” are coded with 0 V, 0.9 V and 1.8 V respectively. In order to validate proposed strategy the 2-input TXOR, TAND and TOR circuits are designed and the simulation results are verified. Speed-power performance of designed circuit is recorded. All the simulations are carried out on TSMC $0.18\mu\mathrm{m}$ CMOS technology with 1.8 V supply rail and at 25°C temperature using Tanner EDA.V13.
Improved Success Probability of Code-Expanded Single-Attempt Random Access by Massive MIMO

Code-expanded Random Access (CeRA) is a promising RA technique to enable massive access. Unfortunately, if the uplink resources are limited, the code ambiguity problem in CeRA will largely affect the success probability of single-shot attempt RA. In this paper, we propose a codeword detection method with the support of massive MIMO to address the code ambiguity problem in CeRA. The merit of the proposed codeword detection method is that the uplink resources could be effectively allocated to the actually transmitted codewords, thus resulting in significantly improved success probability. To this end, we first model the codeword signal of CeRA in massive MIMO system and then demonstrate that the proposed codeword detection method is able to detect the codewords without ambiguity by exploiting the quasi-orthogonality characteristic of massive MIMO. Simulation results verify the effectiveness of resource allocation in the CeRA with massive MIMO. Moreover, properties of the success probability of single-shot attempt RA with respect to system parameters are revealed. Compared to CeRA and LTE, it is shown that the CeRA with massive MIMO benefits from increasing of preamble space size and could provide a much higher success probability of single-shot attempt RA.
In silico identification of potential inhibitors against Mycobacterial proteasome

Foremost barriers in eradicating tuberculosis (TB) are expansion in multi drug resistant, extensively drug resistant and confection of HIV and TB. There is an exigency of potential target as well as efficient anti-tuberculosis agents Mycobacterial proteasome acknowledged to be a satisfactory target having persistence property against human immune defence and obligatory for degradation of some vital proteins. Virtual screening and Molecular docking are the productive tools for quick prediction of lead compounds. So a library of 650 antimicrobial compounds from Enamine database were screened with PyRx virtual screening tool (open source software) and best selected compounds with higher docking affinity were further used for docking with Autodock vina to validate the results. Interactions of ligands and receptor residues were found out using Autodock Tool (ADT) and ligplot. Comparative analysis was carried out to predict the cytotoxicity against human proteasome. Two molecules with id Z1020863610 and Z106766984 were concluded to have favourable specifications to be a powerful drug like candidate so in vitro and in vivo affirmation are required to analyse the consistency of research.
Accelerating Packet Classification with Two Class Cuckoo Filters (TC-CF)

Flexible and high speed packet classification is a key element to enable Software Defined Networks (SDNs) but implementing large matching tables with rules that contain wildcard bits at high speed is challenging. This paper considers the use of Cuckoo Filters (CF) to accelerate packet classification implemented with hash tables. In particular, the filters are used to reduce the number of hash table accesses needed for each packet lookup. In this context, it is beneficial to use a filter that can support two types of elements, popular and unpopular so that patterns with fewer elements (unpopular) get a lower false positive rate. The paper introduces a new structure, the Two Class Cuckoo Filter (TCCF) that efficiently supports two types of elements. The TCCF is evaluated and compared to the use of a plain CF or the existing LACF for several sets of rules. The results show that the TCCF can support both popular and unpopular elements regardless of the filter occupancy and outperforms the other alternatives. Therefore, it can be an interesting option to accelerate packet classification implemented with hash tables in SDN applications.
Distributed Digital Predistortion Architecture for 5G Active Antenna System

This paper presents a distributed digital predistortion (DPD) architecture which separates the adaptation and actuator parts. Unlike conventional DPD architectures in which these two parts are usually placed in the same FPGA, the proposed architecture puts the actuator parts into a transceiver chipset which can provide such a function. Compared to conventional DPD architectures, the proposed distributed architecture can save more than 80% of the DPD FPGA resource in an active antenna system with 64 branches.
Nano-scale electronics: rigorous quantum study of a single molecule device

A single molecule made of carbon atoms, namely C100, has been rigorously simulated for application in quantum electronics and related devices. A self-consistent calculation, using density functional theory and a master-slave perturbation approach, has been done in order to characterize the curren-voltage curves of the above nano-scale component, that could be the building block for future device concepts based on quantum transport. Charging effects, quantum tunneling, ballistic transport, are shown to characterize the device under study, making it an important element of a potential scalable platform for unconventional electronics with extremely high charge sensitivity.
CNNP-v2:An Energy Efficient Memory-Centric Convolutional Neural Network Processor Architecture

An energy efficient memory-centric convolutional neural network (CNN) processor architecture is proposed for smart devices such as wearable devices or internet of things (IoT) devices. To achieve energy-efficient processing, it has 2 key features: First, 1-D shift convolution PEs with fully distributed memory architecture achieve 3.1TOPS/W energy efficiency. Compared with conventional architecture, even though it has massively parallel 1024 MAC units, it achieve high energy efficiency by scaling down voltage to 0.46V due to its fully local routed design. Next, fully configurable 2-D mesh core-to-core interconnection support various size of input features to maximize utilization. The proposed architecture is evaluated 16mm2 chip which is fabricated with 65nm CMOS process and it performs real-time face recognition with only 9.4mW at 10MHz and 0.48V.
Design and analysis of a wide band dual circularly polarized dielectric resonator antenna

In this paper, a wide band circular polarized dielectric resonator antenna of dual sense i.e left hand circular polarization (LHCP) and right hand circular polarization (RHCP) is presented for C band applications. The antenna has been modeled by using DR (Dielectric Resonator), a pair of stubs which are microstrip-fed is printed on a substrate, truncated ground plane to improve impedance matching and a decoupling network. Based on the feed port excitated the antenna can radiate left hand CP (LHCP) or right-hand CP (RHCP) fields. The isolation betwixt two feed ports is enhanced by using the comb shaped decoupling structure and Metamaterials over the operating band. Wide band dual circularly polarized Dielectric Resonator Antenna is fabricated and results are validated.
Compact frequency Reconfigurable rectangle patch with double slot Antenna for Cognitive Radio Applications

Cognitive radio systems required frequency reconfiguration, which is an essential requirement for today's wireless communication. In this proposed work a square patch is designed at a frequency of 4.26 GHz with two slots on the substrate of Rogers RT/duriod 5880(tm) patch. The size of the patch is 18×18mm. Two PIN diodes are connected between the slots for altering the current distribution on the patch surface and it leads to re-configurability. In this study The designed reconfigurable patch antenna works in nine different frequency bands with resonant frequencies of 2.3GHz, 3.8GHz, 4.3GHz, 6.8GHz, 8.8GHz, 12.8GHz, 13.2GHz, 14.6GHz and 16GHz. This antenna reconfiguration bands are suitable for Wi-Fi, Radio Alternatives, GSM, WLAN, RADAR and Satellite communications applications. Different frequency bands can be stipulated by using PIN diode switches. Ansoft HFSS 16 is used for the proposed antenna simulation.
A Genetic Algorithm Formulation for Rogue Taxa Problem

Phylogenetic reconstruction methods like the most common maximum likelihood or Bayesian methods usually result in a large number of slightly varying trees over same set of taxa, known as bootstrap replicates (usually hundreds to thousands in numbers). Extracting useful information from this set of trees involve summarizing most common information in all these trees in a single tree, often called a consensus tree. Presence of rogue taxa greatly reduces resolution of consensus. Some good algorithms are available to identify and remove these but they work only for binary trees. This paper flows with the rogue taxa problem, description and comparison of available algorithms, and our Genetic Algorithm formulation for the problem.
A Tri-Band Meander-Shaped Patch Antenna for WLAN and Radio Navigation Applications

In this paper, a compact tri-band antenna is proposed for radio navigation and WLAN applications. The proposed antenna is designed to operate in the frequency bands 2.26-2.46GHz, 4.02-4.42GHz, and 5.15-5.5GHz with resonating frequency 2.36GHz, 4.2GHz, and 5.3GHz respectively. The first lower resonating frequency has been achieved by using the meander-shaped patch and other two higher resonating frequencies have been generated by using two inverted L-shaped back resonators. Extensive analyses of the reflection coefficient, radiation patterns, and peak gain at different resonating frequencies are presented. The peak gain at three different resonating frequencies is 3.42dBi, 4.12dBi, and 3.47dBi respectively. Multiple bands and higher gain performance of the proposed design make it suitable for the practical applications.
Predicting Collaborative Performance at Assessment Level using Machine Learning

Most of the machine learning-based educational data mining (EDM) studies in university education merely focus on the predication of individual students' performance at institutional/program and course levels. To predict collaborative performance, this study demonstrates the application of a rough set theory-based machine learning technique at the assessment level of a university course. It unveils if-then rules comprising key factors affecting assessment scores and categorizes them into performance classes of ‘Low’, ‘Medium’ and ‘High’. The results are applicable in chalking out strategies related to teaching and student advising to improve academic performance.
Frequency-Tunable Substrate-Integrated Waveguide Filter using Contactless Rotatable Flaps

This paper introduces a substrate-integrated waveguide (SIW) filter that can be tuned using contactless rotatable flaps. There is no mechanical contact between the tuning flaps and the filter body, and this gives a number of advantages in frequency tuning since the flaps do not experience any friction. In addition, it can be tuned with little power consumption, while maintaining stability. Periodic mushroom shaped pins are formed in the flap so that the field generated in the resonator does not leak. Therefore, the Q-factor of the resonator does not decrease even though the flaps are floating in the air. A third-order SIW filter was fabricated and measured for verification. The center frequency is from 2.66 GHz to 3.34 GHz and the insertion loss varies from 0.79 dB to 0.88 dB.
Stress Analysis in Uniaxially Strained-SiGe Channel FinFETs at 7N Technology Node

The uniaxial compressive strain has been an indispensable performance booster for p-channel FinFETs. In this work, based on extensive 3D process and device simulations, performance assessment of nanoscale tri-gate FinFETs with uniaxially strained SiGe channel (fin) has been presented. A comprehensive study based on stress tuning parameters is carried out to investigate the possible highest amount of process induced stress transfer to SiGe fin for optimization of device performance. The impact of process induced stress on carrier mobility enhancement in 7nm technology node is another major focus of this study. The stress transfer efficiency is shown for different process conditions with various Ge contents. Technology CAD simulations show that strain in the fin is large for higher Ge contents in the SiGe layer for p-channel FinFETs. For the first time, the conversion of biaxially strained SiGe to uniaxially strained SiGe via process simulation has been demonstrated, and implemented as uniaxial strained-SiGe channel (fin) in tri-gate FinFETs for high performance.
An Investigation into the Causes of COSS Losses in GaN-on-Si HEMTs

In high-frequency, soft-switched power converters, off-state losses from resonantly charging and discharging the semiconductor output capacitor, or "COSS losses", have severely limited the achievable performance. In this work, we investigate the origin of these losses in GaN-on-Si High Electron Mobility Transistors (HEMTs) using TCAD simulation and experimental techniques, and find that COSS losses can be separated into resistive loss and GaN-stack trap related loss. The resistive loss, or i2R losses, are a combination of resistance in the GaN stack and the Si substrate, and we detail the effect of displacement current through the highly-resistive substrate layer. The GaN-stack trap-related loss is dominated by trapping dynamics. An estimated contribution percentage from these two dominant loss mechanisms is calculated and presented to focus future efforts on solving these two problems.Our insights are supported by device simulation and experimental, including supplementing the Sawyer-Tower test technique with external substrate resistors and temperature variation. From device simulation, we observe the expected dependence of substrate displacement current on dV/dt, and the importance of resistive loss is further confirmed with an experimental Sawyer-Tower test with an external resistor attached to the substrate. Under the assumption that the resistive loss is insensitive to temperature change, GaN-stack trap related loss is investigated with the temperature-controlled Sawyer-Tower test, pointing to the criticality of trapping dynamics in COSS losses.