Miracle-dz/UniFAR-FTUs huggingface dataset:
FIR Filter Implementation for High-Performance Application in a High-End FPGA

In this paper a high-performance application which uses multiple 48k tap FIR filters is presented. Due to its size, complexity and restrictions such as real-time, small latency and large memory bandwidth, the filter was implemented in UltraScale+, a high-end FPGA from Xilinx. The system was verified using a gold reference model written in C (high-level algorithm verification) and an analytical model calculated manually. The system was also tested using a development board and SystemVerilog (for register-transfer level and timing verification). The obtained results show a perfect match between the reference models and the actual output. The main novelty of the paper is the implementation of such a immense real-time signal processing system based on FIR filters consisting of over a million taps all together in a single chip. Details about the resources allocated within the FPGA are also given in a table in the results chapter. Keywords-FIR filter, FPGA, real-time
Dynamic Information Disclosure for Deception*

We analyze in this paper how a deceptive information provider can shape the shared information in order to control a decision maker's decisions. Data-driven engineering applications, e.g., machine learning and artificial intelligence, build on information. However, this implies that information (and correspondingly information providers) can have influential impact on the decisions made. Notably, the information providers can be deceptive such that they can benefit, while the decision makers suffer, from the strategically shaped information. We formulate (and provide an algorithm to compute) the optimal deceptive shaping policies in the multi-stage disclosure of, general, multi-dimensional Gauss-Markov information. To be able to deceive the decision maker, the information provider should anticipate the decision maker's reaction while facing a trade-off between deceiving at the current stage and the ability to deceive in the future stages. We show that optimal shaping policies are linear within the general class of Borel-measurable policies even though the information provider and the decision maker could be seeking to minimize quite different quadratic cost functions.
Towards a Hierarchical Multitask Classification Framework for Cultural Heritage

Digital technologies such as 3D imaging, data analytics and computer vision opened the door to a large set of applications in cultural heritage. Digital acquisition of a cultural assets takes nowadays a couple of seconds thanks to the achievements in 2D and 3D acquisition technologies. However, enriching these cultural assets with labels and relevant metadata is still not fully automatized especially due to their nature and specificities. With the recent publication of several cultural heritage datasets, many researchers are tackling the challenge of effectively classifying and annotating digital heritage. The challenges that are often addressed are related to visual recognition and image classification. In this paper, we present a novel approach of hierarchical classification for cultural heritage assets. The metadata structural differences that exist between cultural assets motivated us to design a classification framework that can efficiently perform the classification of multiple types of assets. Our approach relies on several deep learning classifiers, each of them is assigned the task of classifying a certain type of assets. The classification framework starts the labeling process by first determining the asset type. The asset is then assigned to a specific classifier in order to be annotated with data fields related to its type. As a preliminary step, we successfully designed a general cultural type classifier and a specific type classifier for paintings. Our approach is currently achieving interesting results and is set to be improved by the integration of more asset types.
Continuously Distinct Sampling over Centralized and Distributed High Speed Data Streams

Distinct sampling is fundamental for computing statistics (e.g., the age and gender distribution of distinct users accessing a particular website) depending on the set of distinct keys (e.g., user IDs) in a large and high speed data stream such as a sequence of key-update pairs. However, the major shortcoming of existing methods is their high computational cost incurred by determining whether each incoming key in the data stream is currently in the set of sampled keys and keeping track of sampled keys’ update aggregations. To solve this challenge, we develop a new method <italic>random projection and eviction</italic> (RPE) that uses a list of buckets to continuously sample distinct keys and their update aggregations. RPE processes each key-update pair with small and nearly constant time complexity <inline-formula><tex-math notation="LaTeX">$O(1)$</tex-math><alternatives><inline-graphic xlink:href="wang-ieq1-2865452.gif"/></alternatives></inline-formula>. Besides centralized data streams, we also develop a novel method DRPE to deal with distributed data streams consisting of key-update pairs observed at multiple distributed sites. We conduct extensive experiments on real-world datasets, and the results demonstrate that RPE and DRPE reduce the memory, computational, and message costs of state-of-the-art methods by several times.
A mm-Wave Multi-Beam Directional and Polarimetric Agile Front-End for 5G Communications

A millimeter wave multi-beam directional and full polarimetric agile front-end module for 5th generation of wireless communications is presented. Active voltage summing was used for the lossless rotation of polarization enhancing the envisaged flexibility of 5G air interfaces. The module comprises a low-temperature co-fired ceramic multilayer module, hybrid-integrated monolithic microwave integrated circuits, and an incorporated dual-polarized array antenna. Beamsteering and polarization angles and states are electronically controllable. The front-end exhibits an overall gain of 38 dB and a noise figure of 4.1 dB at a compact module size of $\pmb{74} \ \text{mm} \ \pmb{\times 74} \ \mathbf{mm,}$
Vertically Stacked Gate-All-Around Si Nanowire CMOS Transistors with Reduced Vertical Nanowires Separation, New Work Function Metal Gate Solutions, and DC/AC Performance Optimization

We report on vertically stacked gate-all-around (GAA) Si nanowire (NW) MOSFETs, integrated in a CMOS dual Work Function Metal Replacement Metal Gate (RMG) flow. The integration of a lower temperature STI module and a SiN liner, designed to mitigate the oxidation-induced NW size loss and improve the width/height aspect ratio and NW controllability, is validated electrically. Additionally, Si GAA devices with reduced vertical nanowire spacing are demonstrated. The challenges in terms of Work Function Metal thickness scaling are highlighted, and a thinner nMetal process with low VTH capability and no JG/PBTI lifetime penalty is proposed. Electrically, these process innovations lead to a large improvement of ION/IOFF performance and short channel margin. Finally, a ring oscillator circuit demonstration is shown, with a improvement of gate delay from 24ps down to 10ps at matched VDD demonstrated.
Pre-Performance Routine Training Tool Using Simple Brain-Wave Sensor

This paper describes a pre-performance routine (PPR) training tool, which uses a simple brain-wave sensor. Our tool shows us the current status of concentration and notifies us of the concentration-stabilizing phenomenon on a wearable computer or a tablet computer. PPRs entail the performance of determined motions before an action and are often executed in sports for the purpose of removing stress or raising concentration. The concentration-stabilizing phenomenon was discovered by our previous research and it determined that the phenomenon appears more conspicuous in the case of experts and PPRs. We optimized the procedure for notification such that the concentration-stabilizing phenomenon could be determined without disturbing the subject's concentration. Finally, we verified the effectiveness of our PPR training tool by performing an experimental dart game.
Outage Effective Capacity of Buffer-Aided Diamond Relay Systems Using HARQ-IR

In this paper, transmission over buffer-aided diamond relay systems under statistical quality of service (QoS) constraints is studied. The statistical QoS constraints are imposed as limitations on delay violation probabilities. In the absence of channel state information (CSI) at the transmitter, truncated hybrid automatic repeat request-incremental redundancy (HARQ-IR) is incorporated to make better use of the wireless channel and the resources for each communication link. The packets that cannot be successfully received upon the maximum number of transmissions will be removed from buffer, i.e., outage occurs. The outage effective capacity of a communication link is defined as the maximum constant arrival rate to the source that can be supported by the goodput departure processes, i.e., the departure that can be successfully received by the receiver. Then, the outage effective capacity for the buffer-aided diamond relay system is obtained for HARQ-IR incorporated transmission strategy under the end-to-end delay constraints. It is shown that HARQ-IR can achieve the same performance as the one achieved with the decode-and-forward protocol with perfect CSI at the transmitters under certain delay constraints.
Relationship between Teachers' Self-Efficacy and Instructional Strategies Applied among Secondary School Teachers in Implementing STEM Education

STEM is an acronym for Science, Technology, Engineering and Mathematics. Malaysia prioritizes STEM Education in the education transformation with the target to fulfill the demand of national workforce. Strengthening STEM initiatives stated in the Malaysian Blueprint 2013–2025 targets students to be nurtured with the skillset to survive the hardships of a fast-moving pace technological world. As teachers play an essential role in ensuring achievement of this transformation, this study was conducted to identify the level of self-efficacy and dominant instructional strategies among secondary school STEM teachers in the district of Kemaman, Terengganu in Malaysia. A simple random survey method was used in this study involving 217 teachers. The instruments used in this study were Teacher Efficacy Scale (TES) and Minnesota Effective Practice Instructional Strategies Assessment (MEPISA). The analysis of descriptive statistics and Pearson correlation was done using SPSS software. The findings of this study show that the mean for both general and personal teaching self-efficacy are at a high level. While, the mean for dominant instructional strategies perceived by teachers is at a moderate level. Furthermore, there is a low but significant positive correlation found between the general and personal teaching self-efficacy with instructional strategies in implementing STEM education.
Revealing the Misuse of Motorcycle Ride-sharing Applications using Extended Deterrence Theory Approach

This study determines the influence of security countermeasures on perceived sanctions which impacts the misuse intentions of ride-sharing applications by motorcycle taxi rider. The research model was built using eight hypotheses as adopted from Deterrence Theory. The data were collected using questionnaires that were distributed directly to the motorcycle taxi rider in ride-sharing. There are 198 samples obtained and processed using the Partial Least Square Structural Equation Modeling (PLS-SEM) method. This study found that severity of sanctions perceived and moral beliefs of motorcycle taxi rider have a significant negative impact to the misuse intentions of mobile application. The certainty of perceived sanction does not have a significant relationship with the intention of motorcycle taxi rider to misuse the mobile application. Furthermore, it revealed that security countermeasures have a significant positive impact with the sanctions perceived and the moral beliefs of motorcycle taxi rider.
Balanced Drive Currents in 10–20 nm Diameter Nanowire All-III-V CMOS on Si

We use a self-aligned, gate-last process providing n-type (InAs) and p-type (GaSb) MOSFET co-integration with a common gate-stack and demonstrate balanced drive current capability at about $100\ \mu \mathrm{A}/\mu \mathrm{m}$. By utilizing HSQ-spacers, control of gate-alignment allows to fabricate both n- and p-type devices based on the same type of vertical heterostructure InAs/GaSb nanowire with short gate-lengths down to 60 nm. Refined digital etch techniques, compatible with both sensitive antimonide structures and InAs, enable down to 16 nm diameter GaSb channel regions and 10 nm InAs channels. Balanced performance is showcased for both n- and p-type MOSFETs with $I_{\text{on}}=156\ \mu \mathrm{A}/\mu \mathrm{m}$, at $I_{\text{off}}=100\ \text{nA}/\mu \mathrm{m}$, and $98 \mu \mathrm{A}/\mu \mathrm{m}$, at $\vert V_{\text{DS}}\vert =0.5$, respectively.
State-Based Control of Timed Discrete-Event Systems

The problem of supervisor synthesis for discrete-event systems (DES) has been proven to be NP-hard. Nevertheless, state tree structures (STS) have turned out to be a computationally efficient framework to design supervisors for very large-scale systems. But this framework relies on a state-based control theory. To expand STS to timed systems, known as timed discrete-event systems (TDES), a state-based control theory for TDES is required. In this paper, such a theory will be introduced and it will be proven that this approach is indeed equivalent to the existing language-based control theory for TDES.
Modulation of Magnetism and Magnetic Anistropy at the Heavy-Metal/FeRh Interface

Herein, using first-principles calculations, we explore the magnetic-phase order and magnetic anisotropy energy (MAE) of FeRh (001) films with different heavy transition-metal contact layers (HTM = Hf, Ta, and W). While the antiferromagnetic ground state of FeRh still persists at the W/FeRh interface with the thicker FeRh films, the earlier HTMs of Hf and Ta favor the robust ferromagnetism in the interfacial FeRh layers. Moreover, in contrast to an in-plane magnetization of W/FeRh bilayer, the magnetization direction of FeRh reorients from in-plane to perpendicular in the presence of Hf and Ta overlayers. In particular, a large perpendicular MAE of 2 meV is identified at the Hf/FeRh interface, which is associated with the interfacial magnetic-phase transition and the large spin-orbit coupled <inline-formula> <tex-math notation="LaTeX">$3{d}$ </tex-math></inline-formula>–<inline-formula> <tex-math notation="LaTeX">$5{d}$ </tex-math></inline-formula> hybridization.
Four-Element Reconfigurable Coupled Loop MIMO Antenna Featuring LTE Full-Band Operation for Metallic-Rimmed Smartphone

This paper describes a low-profile <inline-formula> <tex-math notation="LaTeX">$2\times 2$ </tex-math></inline-formula> multi-input multi-output (MIMO) antenna system that is fully functional over the entire long-term evolution (LTE) spectrum 699–960 MHz (lower frequency spectrum) and 1710–2690 MHz (higher frequency spectrum) that is applicable to real-life metallic smartphone platforms. The presented methodology entails utilizing the longitudinal edges of the ground plane amid an extremely narrow ground clearance of 2 mm. The metallic frame of the smartphone is utilized along with a stub network to devise a reconfigurable coupled loop antenna topology. The proposed <inline-formula> <tex-math notation="LaTeX">$2\times 2$ </tex-math></inline-formula> MIMO antenna configuration is measured and confirmed to exhibit efficient envelope correlation coefficient (<0.5) and one of the highest radiation efficiencies to be reported in the literature across the entire LTE spectrum.
Pathway-Centric Analysis of the TCGA - NSCLC Transcriptome Data Pertaining to Deceased Patients

Lung cancer among other cancer types is the most prevalent disease with about 1.9 million new cases observed each year and ranks the fifth most common cause of death according to the World Health Organization. Of the two main subtypes of lung cancer, non-small cell lung carcinoma (NSCLC) accounts for the majority of all cases. The two major subtypes of NSCLC, lung squamous cell carcinoma and lung adenocarcinoma are extensively sampled as part of The Cancer Genome Atlas (TCGA) project. In this study, we took a pathway centric focus on the analysis of RNA-Seq data belonging to dead NSCLC patients involved in TCGA. We applied statistical tests comparing subgroups of patients based on varying clinical traits such as tumor pathologic staging and the total number of days passed from diagnosis till death for the subjected patients. We also compared the transcriptome of smokers and nonsmokers to gain insights about the effect of tobacco smoking history on the gene expression patterns of deceased NSCLC patients. Neuroactive ligand-receptor interaction pathway was overrepresented in patients who died at pathologic T2 stage as well as in those lung cancer patients who survived less than a year. Down-regulation of the signaling pathways such as retrograde endocannabinoid, Hippo, AGE-RAGE in diabetic complications, Wnt, and oxytocin was also striking in patients who survived shorter. We show concordant results with previous findings about the down-regulation of nitric oxide synthase in smokers. This study may encourage more focused analyses of the TCGA data with a potential to cast new perspectives onto lung cancer research.
University Students' M-leaming Adaption Behavioral Factors: A Pilot Study

This study analyzes factors affecting international student's intentional m-learning use in higher education. Using the UTAUT model and four other variables, a framework was developed. Data was collected from seventeen students' from a Canadian public university. This data was analyzed using the SPSS version 24.0 and WarpPLS 5.0. Results show that performance expectancy and effort expectancy equally predicts m-learning behavioral intention in higher education. Furthermore, social factors have the highest significant factor on the behavioral intention. Finally, facilitating condition negatively influences m-learning behavioral intention. This study presents both theoretical and empirical contribution in order to understand predicting variables on m-learning use in higher education.
Deep Metric Learning for Color Differences

Numerous attempts have been made to define a color space and a color distance metric that would closely resemble the human color vision. The uniformity has been the main challenge, the human vision system is more sensitive to some colors while less sensitive to others. A distance given by an ideal metric would match the color difference seen by the human vision system. This study attempts to define such a metric utilizing the spectral data and the available information on the distinguishable colors. Deep neural networks are used in metric learning for modeling the color space and the metric. The resulting metric is then tested against the standard CIEDE2000 metric. DNNs are also used to project spectral data onto a new color space. The results indicate that the new color space with the Euclidean metric is more perceptually uniform than the standard LAB color space with the CIEDE2000 metric. The new metric enables better understanding about the human vision system and measuring the color differences.
Numerical and Experimental Determination of Local Building Factors of a Three-Phase Transformer Core Package

The analyses of flux distributions and losses in transformer cores need highest expenditure if performed in experimental ways. This paper presents a novel combined methodology for the evaluation of local and global loss building factors BF. As a first step, the local patterns of the dynamic induction vector <inline-formula> <tex-math notation="LaTeX">$B(t)$ </tex-math></inline-formula> were calculated, by means of a novel numerical “magnetic anisotropic circuit calculation (MACC) methodology. The latter considers the core materials non-linear permeability functions in rolling direction and transverse direction, as well as non-linear effects of overlaps in corners and T-joints. In a second step, the calculated induction patterns were exactly simulated on the hexagonal Vienna rotational single sheet tester and the corresponding local losses <inline-formula> <tex-math notation="LaTeX">${p}$ </tex-math></inline-formula> were measured electrodynamically. Finally, the values <inline-formula> <tex-math notation="LaTeX">${p}$ </tex-math></inline-formula> were allocated to the corresponding core positions, taking into account the entire core geometry. BF of the core was estimated from the total of loss values weighted to the corresponding volume portions. The method was applied for a three-phase core of highly grain-oriented material, magnetized with <inline-formula> <tex-math notation="LaTeX">$B_{\text {NOM}} = 1.7$ </tex-math></inline-formula> T. The procedure shows the local distributions of losses, yielding also information on those of eddy currents and rotational magnetization (RM). As an example, the T-joint, as the area of highest RM, yields a local loss increase of about 50%. Apart from RM, the local induction variations—including waveform distortions, caused mainly by circulating magnetization—prove to have a high impact on losses, locally yielding 50% as well. These highly convincing results indicate that the complicated sensor studies of cores can partly be replaced by: 1) numerical modeling of induction distributions and 2) subsequent allocations of loss values as detected by RSST simulations.
Impacts of Proton Radiation on Heavy-Ion-Induced Single-Event Transients in 65-nm CMOS Technology

<inline-formula> <tex-math notation="LaTeX">$3 \times 10^{13}/\text{cm}^{2}$ </tex-math></inline-formula> 1.2-MeV proton radiation will significantly increase heavy ion single-event transient (SET) cross sections and pulsewidths in 65-nm bulk CMOS technology. After proton radiation, heavy ion SET sensitivity increase in N-hit blocks is more than that in P-hit blocks. The analysis suggests that pMOS transistor on current (<inline-formula> <tex-math notation="LaTeX">$I_{\mathrm{\scriptscriptstyle ON}}$ </tex-math></inline-formula>) reduction due to total ionizing dose effects is the main reason for this effect. It is suggested that alternate heavy ion and proton experiments should be performed for radiation hardness assurance of candidate electronic devices used in deep space missions.
Correction Method of Walking Posture Distortion of Elderly by Using Laser Pointer Task

The purpose of this study is to clarify the effectiveness of the new posture correction method of we suggest, aiming at the development of improvement training of posture distortion. We have used Kinect to measure the posture distortion caused by aging, and proposed a method to utilize it for maintaining the health of elderly people. In this paper, we propose a new method to correct posture distortion during walking with the laser pointer by hand, keeping the laser light to the target in the front direction, called Laser Pointer task, and clarify the effectiveness of the method by the experimental analysis. As a result, posture distortion and body wobble of the elderly are reduced during the performance of the Laser Pointer task. Such effects are realized by voluntary control of own gait speed caused by the task and feedback information indicated as the movement of the pointer on the target. This result suggests that the proposed Laser Pointer task is effective as a correction method of posture distortion.