Miracle-dz/UniFAR-FTUs huggingface dataset:
Suction Cup Based on Particle Jamming and Its Performance Comparison in Various Fruit Handling Tasks

Suction cups are widely used in pick and place tasks in well-structured and controlled environments with low variance in task requirements. For tasks requiring higher demands and variations, such as quality control of citrus fruits, commercial suction cups do not have the required reliability. The design and performance of a novel suction cup based on particle jamming is presented in this paper. Particle jamming allows operation in two states, a malleable state to adapt to large irregularities in object surfaces, and a stiff state to rigidly hold the object for manipulation and prevent the cup collapsing in on itself. This jamming cup is shown to successfully adapt to surfaces with up to 7 times variations compared to standard suction cups. Additionally, for similar scale cups, the holding force is comparable and has <50% deviation.
Secure-iGLU: A Secure Device for Noninvasive Glucose Measurement and Automatic Insulin Delivery in IoMT Framework

The growth of healthcare technologies has made a great impact on human life for the last few years. Various innovations in implantable and wearable medical devices improve the quality of life. Internet-of-Medical-Things (IoMT) based smart healthcare with continuous sensing, connectivity, and automatic medication is the latest trend. With the growth of technologies and connectivity, the security of these devices is a growing concern. The security of medical devices is important as the security compromise may lead to critical situations. This paper explores the security aspect of the IoMT system with a non-invasive glucose monitoring device integrated with an insulin delivery system (called iGLU) as a specific example. We call this secure system as Secure-iGLU. The paper presents a Hardware-Assisted Security (HAS) paradigm using Physical Unclonable Function (PUF) to design Secure-iGLU. PUF is a useful primitive to generate fingerprint of the hardware, and it has a great potential to mitigate the security problem of iGLU. The simulation results confirm the security of our Secure-iGLU using PUF in IoMT with safe insulin delivery system.
Optimizing Resolution-Adaptive Massive MIMO Networks

We consider the uplink of a cellular network wherein each base-station (BS) simultaneously communicates with multiple users. Each BS is equipped with a large number of antenna elements and a limited number of RF chains. Each RF chain (on each BS) houses an analog-to-digital converter (ADC) whose bit resolution can be configured. We seek to jointly optimize user transmit powers and ADC bit resolutions in order to maximize the network spectral efficiency, subject to power budget constraints at each user and BS. This joint optimization becomes intractable if we insist on exactly modeling the nonlinear quantization operation performed at each ADC. On the other hand, simplistic approximations made for tractability need not be meaningful. In this work, we propose a methodology based on a constrained worst-case quantization noise formulation, along with another one that assumes quantization noise covariance to be diagonal. In each case, using a series of effective mathematical re-formulations we are able to express our problem in a form that is well-suited for alternating optimization, in which each sub-problem can be efficiently and optimally solved. Through a detailed performance analysis, we demonstrate that the optimized transmit powers and bit resolutions can yield very significant improvements in achievable spectral efficiency, at a reduced sum power consumption and an affordable complexity.
VCF: Virtual Code Folding to Enhance Virtualization Obfuscation

Code virtualization, also called virtualization obfuscation, is a code obfuscation technique that protects software from malicious analysis. Unlike code packing or code encryption techniques, code virtualization does not restore the original code on the memory. However, because basic components of the structure are simple, if a virtualization structure is revealed statically, there is a limitation in that the analysis process is somewhat constant. In this paper, we propose Virtual Code Folding (VCF) as a new code virtualization technique. The proposed method reduces the amount of virtual code that is statically revealed by folding the virtual code inside a virtualization structure and enables the virtual code to be decoded by generating multiple diversified dispatchers. The folded virtual code is restored by the random key, and then fetched and decoded by the diversified dispatcher. This process makes it possible for VCF to effectively obfuscate correspondence between virtual code and handler code (i.e., code that performs real functionality) without significant performance overhead or strong assumptions.
ZeroWall: Detecting Zero-Day Web Attacks through Encoder-Decoder Recurrent Neural Networks

Zero-day Web attacks are arguably the most serious threats to Web security, but are very challenging to detect because they are not seen or known previously and thus cannot be detected by widely-deployed signature-based Web Application Firewalls (WAFs). This paper proposes ZeroWall, an unsupervised approach, which works with an existing WAF in pipeline, to effectively detecting zero-day Web attacks. Using historical Web requests allowed by an existing signature-based WAF, a vast majority of which are assumed to be benign, ZeroWall trains a self-translation machine using an encoder-decoder recurrent neural network to capture the syntax and semantic patterns of benign requests. In real-time detection, a zero-day attack request (which the WAF fails to detect), not understood well by self-translation machine, cannot be translated back to its original request by the machine, thus is declared as an attack. In our evaluation using 8 real-world traces of 1.4 billion Web requests, ZeroWall successfully detects real zero-day attacks missed by existing WAFs and achieves high F1-scores over 0.98, which significantly outperforms all baseline approaches.
Performance Comparison of Single-Phase SAPF Using PQ Theory and SRF Theory

In this paper a highly non-linear load has been modelled to compare the performance of PQ-Theory and SRF-Theory based extraction techniques for Active Power Filter (APF) using Simulink. To compare the dynamic and the steady state performance of these extraction techniques, a highly inductive load is connected after a certain simulation time and the behavior of the APF to this change has been studied. The extraction techniques originally designed for three phase systems has been adapted for a single-phase system and the implementation of it has been explained. The topology of the inverter, system parameters and load parameters are kept the same throughout this study for fair performance comparison of the two extraction techniques. Also, the reactive power compensation offered by these extraction techniques and certain anomalies seen in the waveforms have also been studied.
Hybrid IoT based Hazard Detection System for Buildings

Monitoring and Automating the process of Hazard detection has been a challenging task for many eras, with the rise of internet of things and sensor based network any easy and viable solution can be built to detect the various hazards that can occur to a building, this IOT task focuses on constructing a smart wireless hazards preventing system. These consist of temperature, fire, light, and smoke manage security against the hazard in a single system which has many sensors integrated together to detect the hazards and as well as generate a timely detection and produces an alarm. This device is to provide effective monitoring to reactive services. The research work carried out is tested with multiple type of sensors in multiple conditions and the results have shown a good accuracy rate.
Study of Three Phase VSC Models for Controller Design by Using Port-Controlled Hamiltonian

The Port-Based system modeling is applied and becomes an attractive topic in the field of control engineering. Due to its energy based concept, it can model physical systems in an effective and systematic manner, e.g. Port-Controlled Hamiltonian approach. However different model structures can be obtained, if the system contains switching devices, e.g. voltage source converter. This paper presents two approaches for converter modeling and their effect on the system behavior, when the controller is designed by the IDA-PBC concept. The simulation results show that the responses of the closed loop system hardly depend on the structure of converter model, even the obtained controllers are different. Especially when the systems operate around the operating point.
Error Resilient Machine Learning for Safety-Critical Systems: Position Paper

Machine learning (ML) has increasingly been adopted in safety-critical systems such as autonomous vehicles (AVs) and industrial robotics. In these domains, reliability and safety are important considerations, and hence it is critical to ensure the resilience of ML systems to faults and errors. On the other hand, soft errors are becoming more frequent in commodity computer systems due to the effects of technology scaling and reduced supply voltages. Further, traditional solutions for masking hardware faults such as Triple-Modular Redundancy (TMR) are prohibitively expensive in terms of their energy and performance overheads. Therefore, there is a compelling need to ensure the resilience of ML applications to soft errors on commodity hardware platforms.We first experimentally assess the resilience of safety-critical ML applications to soft errors. We demonstrate through fault injection experiments that even a single bit flip due to a soft error can lead to misclassification in Deep Neural Network (DNN) applications deployed in AVs, leading to safety violations. However, not all the errors in an DNN will result in serve consequences such as safety violations, and hence it is sufficient to protect the DNN from the ones that do. Unfortunately, finding all possible errors that result in safety violations is a very compute intensive task. We propose BinFI, a fault injection approach that efficiently injects critical faults that are highly likely to result in safety violations, based on the unique properties of DNNs. Finally, we propose Ranger, an approach to protect DNNs from critical faults with minimal performance overheads and no accuracy loss. We will conclude by presenting some of our ongoing work, and the future challenges in this area.
NodeRacer: Event Race Detection for Node.js Applications

The Node.js platform empowers a huge number of software systems programmed with JavaScript. Node.js employs an asynchronous execution model where event handlers are scheduled nondeterministically, and unexpected races between event handlers often cause malfunctions. Existing techniques for detecting such event races require complex modifications of the Node.js internals, or target only certain kinds of races. This paper presents a new approach, called NODERACER, that detects event races in Node.js applications by selectively postponing events, guided by happens-before relations. The technique is implemented entirely with code instrumentation, without modifications of the Node.js system. Our experimental results give evidence that NODERACER finds event race errors with higher probability than a state-of-the-art fuzzer, and that the use of happens-before relations helps avoiding false positives. Furthermore, we demonstrate that NODERACER produces actionable error reports, and that it can be helpful for detecting test flakiness that is caused by event races.
Mathematical modeling of the Caenorhabditis elegans RMD motor neurons

The nematode Caenorhabditis elegans has been established as a model organism for developmental biology, drug screening, and human disease studies. Its nervous system has been completely characterized in neurons number and connections and, therefore, it constitutes an ideal framework for the study of simple, yet realistic, neuronal systems. In this context, biophysical mathematical models of single neurons could effectively help to deepen our knowledge of C. elegans neuronal dynamics. In this work, we present a Hodgkin-Huxley model of the RMD motor neurons, based on available experimental data. Our results properly reproduce the electrical oscillations of RMD neurons membrane potential in response to external stimuli and highlight the role of T-type calcium channels in the bistability of the neuron. Our work gives a basis for the in silico modeling of the nematode nervous and muscular system, with possible applications in the study of channelopathies effects on neuronal and muscular activity.
Are We Ready for Mobile Payment?

This study aims to identify the factors influencing the readiness and acceptance of mobile payment applications. The study is performed using the survey method. Quantitative data analysis are used to measure the relationship between the perceived usefulness, perceived ease of use, and perceived security on the readiness of Malaysian in using mobile payment applications. The results shown that perceived usefulness, perceived ease of use, and perceived security have a positive and significance relationship with the usage of mobile payment applications. Moreover, perceived ease of use is reported as the strongest factor towards usage of mobile payment applications, following by perceived security and perceived usefulness. This study is able to provide information on the current stage of use on mobile payment in Malaysia and it is also beneficial to the mobile payment facilities provider into find out strategies that could improve the acceptance and use of mobile payment application.
Effects of Smoking on HR Circadian Rhythm in Hypertensive and Non Hypertensive Subjects

Clinical parameters as Blood Pressure and Heart Rate (HR) are influenced by hypertension and smoking. To evaluate how these risk factors influence HR, usually punctual or mean evaluation of these signals on daytime or nighttime are made. However, since HR has a circadian behavior, changing during 24h, a punctual description represents only a rough approximation of this comportment. In this study, we analyzed the influence of smoking and hypertension on the circadian rhythm of HR with a standard temporal resolution. Data coming from 618 hypertensive/non-hypertensive, smokers/non-smokers subjects were recorded using a Holter BP monitor. Results confirmed significant higher values of HR during day and nighttime in smokers than in non-smokers also highlighting different velocity of HR linear changes in three periods of the 24h (daytime, nighttime, early morning).
Optimal Number of Edge Devices in Distributed Learning Over Wireless Channels

We consider a distributed learning system, where a parameter server (PS) assigns data and computational tasks to edge devices to build a global model. Distributing data to multiple workers involves communication between PS and edge devices and entails a fundamental tradeoff between computation and communication. In this paper, we aim at characterizing the optimal number of edge devices required for guaranteeing convergence and for achieving a certain accuracy within a finite time horizon.
Architectural Advancement of Digital Low-Dropout Regulators

Digital Low-dropout (DLDO) regulators have been widely utilised for highly-efficient fine-grained power delivery and management in system-on-chips (SoCs) due to their process scalability, ease of integration, and low-voltage operation. However, conventional DLDOs suffer gravely from the power-speed tradeoff, which arises from the use of sampling clocks. To obtain reasonable performance in the undershoot and recovery during load transient states, a large output capacitor is inevitably required in these DLDOs. Moreover, they inherently involve large steady-state voltage ripples and poor power-supply rejection (PSR). These limitations of synchronous DLDOs and their counter measures are thoroughly discussed in this paper. Various design strategies of major building blocks, i.e. comparators and power transistor arrays, are explained in detail with examples. Architectural advances are also expounded including state-of-the-art DLDO architectures such as clock-boosted synchronous, analog-assisted synchronous, asynchornous, event-driven, and hybrid DLDOs. These state-of-the-art DLDOs do not only address the power-speed tradeoff and achieve fast load transient responses, but also can eliminate the use of an output capacitor in some cases. Moreover, some hybrid DLDOs successfully removed the steady state ripples and achieve high PSR. All of these DLDO are compared on basis of their performance metrics and figure-of-merits (FOMs).
A Production-worthy Fan-Out Solution - ASE FOCoS Chip Last

The 5th Generation (5G) wireless systems popularity will push the package development into a high performance and heterogeneous integration form. For high I/O density and high performance packages, the promising Fan Out Chip on Substrate (FOCoS) provides a solution to match Outsourced Semiconductor Assembly and Testing (OSAT) capability. FOCoS is identified the Fan Out (FO) package, which can flip chips on a ball grid array substrate, and FOCoS constructs from multi-chips with short distance between chip to chip by multi-chip system for interposer less structure, which has the potential for heterogeneous integration and functional chip in one package. Heterogeneous integration refers to the integration of separately manufactured components into a higher level assembly. In this study, the yield of the production over 99% and of FOCoS chip last package was presented. To reduce the wafer warpage effect, we used three dimensional finite element method (3D-FEM) and advanced Metrology Analyzer (aMA) can find the optimum thickness and Coefficient of Thermal Expansion (CTE) of the glass carrier. About FOCoS chip last device, large-size packages with 8 complex chips especially with fine line RDL and different size μbump joint structures inside have been successfully developed. In reliability examination, the test vehicle also passed the JEDEC and IPC qualification, respectively. Finally, ASE has successfully established the FOCoS chip production line, and further developed it in a larger area, and higher integration complexity to meet the growing needs of the 5G era.
Auto-Weighted Incomplete Multi-View Clustering

Nowadays, multi-view clustering has attracted more and more attention, which provides a way to partition multi-view data into their corresponding clusters. Previous studies assume that each data instance appears in all views. However, in real-world applications, it is common that each view may contain some missing data instances, resulting in incomplete multi-view data. To address the incomplete multi-view clustering problem, we will propose an auto-weighted incomplete multi-view clustering method in this paper, which learns a common representation of the instances and an affinity matrix of the learned representation simultaneously in a unified framework. Learning the affinity matrix of the representation guides to learn a more discriminative and compact consensus representation for clustering. Moreover, by considering the impact of the significance of different views, an adaptive weighting strategy is designed to measure the importance of each view. An efficient iterative algorithm is proposed to optimize the objective function. Experimental results on various real-world datasets show that the proposed method can improve the clustering performance in comparison with the state-of-the-art methods in most cases.
Analysis and Design of Broadband Ridge-Gap-Waveguide Tight and Loose Hybrid Couplers

A wideband broad-wall directional coupler is designed using the ridge-gap-waveguide (RGW) technology operating on the quasi-TEM mode. Large coupling apertures are used between two mirrored RGWs. Several coupling levels are achieved according to the number of apertures used and the ridge height in the two RGWs. Furthermore, a design procedure to obtain the desired coupling levels is introduced. Simulations and measurements show that tight-to-loose coupling levels (3–33 dB) can be achieved with the same coupler configuration, but with different parameters within ±1-dB coupling variations. The couplers achieve better than 15-dB return loss and better than 20-dB isolation within a 40% bandwidth with ±1 dB and ±2 degrees of magnitude and phase errors, respectively.
Compact Quarter-Mode Substrate-Integrated Waveguide Dual-Frequency Millimeter-Wave Antenna Array for 5G Applications

A compact linearly polarized quarter-mode substrate-integrated waveguide (QMSIW) dual-frequency millimeter-wave antenna is presented in this letter. The antenna has two unequal-sized quarter-mode parts of two square substrate-integrated waveguide (SIW) cavities for two operating bands. Each quarter can be tuned independently. The two quarters are realized within one layer of substrate laminate and are placed in a back-to-back configuration, sharing the same row of metalized vias, which makes the structure very simple and compact. For the demonstration, a QMSIW dual-frequency antenna simultaneously operating at 28 and 38 GHz bands was designed for fifth-generation (5G) applications. Compared with a traditional full-mode SIW slot antenna, our element design merits in an antenna footprint miniaturization of 53.5%. A four-element corporate-fed antenna array was also designed, fabricated, and measured. Good agreement between the measured and simulated results is obtained. The measured peak antenna gains of 9.5 dBi and 11.0 dBi are obtained for the lower and upper bands, respectively.
Automated Model Generation Including Variations for Formal Verification of Nonlinear Analog Circuits

With the advancements in analog/mixed-signal (AMS) systems and continuously shrinking design sizes, there is an increased demand for reliable verification to ensure correct behavior. To overcome this obstacle, using formal verification is a promising option. We present a modeling system that automatically provides dependable set-valued models from circuit netlists in a form suitable for reachability analysis. Our method is based on local linearizations of the nonlinear circuit. Linearized locations are computed on-the-fly depending on which states are reachable to avoid the state-space explosion problem. The set-valued models include device parameter variations, modeling errors and uncertain input stimuli.
An equivalent investigation of space charge for plane samples and coaxial cables under a temperature gradient

In this research, the equivalence of space charge for coaxial cables and plane samples are analyzed through simulation. Bipolar charge transport models of coaxial cables and plane samples are established with the same material-dependent parameters, the bulk charge and total space charge distributions are simulated and comparatively researched under isothermal and temperature gradient conditions. The presented results indicate that the space charge behavior shows a basic equivalence in terms of charge variation laws and distribution. In addition, few discrepancies in the heterocharge amount and charge waveform amplitude are observed and mainly ascribed to the sample geometry, mobility gradient distribution and the spatial resolution of the measuring system, respectively. Investigations of space charge characteristics with a plane pulsed electro-acoustic measurement system may be accepted as a practice for providing the space charge characteristics of coaxial cable insulation, unless it is necessary to investigate the cable space charge distribution under actual operating conditions.