Miracle-dz/UniFAR-FTUs huggingface dataset:
Same Same but Different: Finding Similar User Feedback Across Multiple Platforms and Languages

Users submit feedback about the software they use through application distributions platforms, i.e., app stores, and social media. Previous research has found that this type of feedback contains valuable information for software evolution, such as bug reports, or feature requests. However, popular applications receive thousands of feedback entities per day, making their manual analysis unrealistic. In this work, we present an approach to automatically identify similar user feedback across different languages and platforms. At the core of the approach is a word aligner that aligns words based on their semantic similarity and the similarity of their local semantic contexts. Additionally, we make use of machine translation, sentiment analysis, and text classification, to extract the sentiment polarity and content nature of user feedback written in different languages. We use the results of these components to compute a similarity score between user feedback pairs. We evaluated our approach on user feedback entities written in four different languages, and retrieved from five different mobile applications obtained from four different app stores and social networking sites. The obtained results are encouraging. Compared to human assessment, the overall performance for monolingual user feedback pairs yielded a strong correlation of 0.79. For the crosslingual feedback pairs the correlation was also strong, with a value of 0.78.
The 3D Smith Chart: From Theory to Experimental Reality

The Smith chart was primarily developed, extended, and refined by Phillip Hagar Smith [1] in a series of works published [2]-[4] between 1939 and 1969. Smith was born in Lexington, Massachusetts, in 1905. He majored in electrical communications at Tufts University and joined the Radio Research Department of Bell Telephone Laboratories (now Bell Labs) in 1928. While there, in around 1930, Smith started work on the diagram that was to become the Smith chart. He submitted the initial version to Electronics Magazine in 1937; the magazine finally published his diagram in 1939 [2]. The MIT Radiation Laboratory started using the chart. In 1940, and in 1944 Smith published a second article that incorporated further improvements, including the use of the chart with either impedance or admittance coordinates. In 1952, Smith was elevated to IEEE Fellow for his contributions to the development of antennas and the graphical analysis of transmission-line characteristics. The first issue of Microwave Journal (1958) published a biography of Smith to acknowledge the importance of his contributions. In 1969, he wrote the book Electronic Applications of the Smith Chart in Waveguide, Circuit and Component Analysis; he retired from Bell Labs in 1970. In 1975, he received the IEEE Microwave Theory and Techniques Society? s Special Recognition in Microwave Applications award for the Smith chart, and in 1994 he was elected to the New Jersey Inventors Hall of Fame.
How developers believe Invisibility impacts NFRs related to User Interaction

The advance of Ubiquitous Computing (UbiComp) and Internet of Things (IoT) brought a new set of Non-Functional Requirements (NFRs), especially related to Human-Computer Interaction (HCI). Invisibility is one of these NFRs, and it refers to either the merging of technology in the user environment or the decrease of the interaction workload. This new NFR may impact traditional NFRs (e.g., Usability), revealing positive correlations, when one NFR helps another, and negative correlations, when a procedure favors an NFR but creates difficulty for another one. Software engineers need to know about these correlations, so they can select appropriate strategies to satisfy Invisibility and traditional NFRs. Correlations between NFRs are usually stored in catalogs, which is a well-defined body of knowledge gathered from previous experience. Although Invisibility has been recently cataloged with development strategies, the literature still lacks catalogs with correlations for this NFR. Therefore, this work aims at capturing and cataloging invisibility correlations for UbiComp and IoT systems. To do that, we also propose to systematize the definition of correlations using the following well-defined research methods: Interview, Content Analysis and Questionnaire. As a result, we defined a catalog with 110 positive and negative correlations with 9 NFRs. This well-defined body of knowledge is useful for supporting software engineers to select strategies to satisfy Invisibility and other NFRs related to user interaction.
A Wideband True-Time-Delay Phase Shifter with 100% Fractional Bandwidth Using 28 nm CMOS

A fully integrated passive true-time-delay (TTD) phase shifter is presented for a wideband phased array antenna using 28-nm CMOS technology. By using a delay-compensation technique, a linear phase characteristic is achieved within a wide frequency range over 8−24 GHz. A combined bridged-tee network (BTN) delay cell is proposed to accomplish the delay compensation with the most significant bit (MSB) at 29.6 ps and the least significant bit (LSB) at 7.4 ps, which are 45° and 180° at 16 GHz, respectively. The measured insertion loss is in the range of 7.8−12 dB with an RMS gain error less than 1.4 dB from 8 GHz to 24 GHz. In addition, the measured RMS TTD phase and delay errors are less than 1.6 ps and 1.5°, respectively, within 8−24 GHz. The chip size of the proposed TTD phase shifter is 0.48 mm2.
MAMBA: Adaptive and Bi-directional Data Transfer for Reliable Camera-display Communication

Camera-display communication leverages visible light to transfer data wirelessly by using a screen as a transmitter and a camera as a receiver. Such an approach faces several challenges to be employed in practice, including unreliable decoding due to imperfect synchronization and channel impairments. This article introduces MAMBA, a mobile application framework for adaptive camera-display communication with color barcodes. MAMBA employs efficient computer vision techniques and scales with the number of blocks in the barcode, rather than with the number of pixels in the captured image. As a consequence, it allows to take full advantage from the high-resolution cameras available on modern mobile devices. In addition, MAMBA realizes an adaptive and bi-directional protocol for camera-display communication with fast feedback. Specifically, MAMBA carries out dynamic adaptation of both frame rate and length based on environmental conditions and the processing capabilities of the devices. Experimental results show that MAMBA is effective, thereby allowing reliable realtime communication in a variety of operating conditions.
INVITED: Computation on Sparse Neural Networks and its Implications for Future Hardware

Neural network models are widely used in solving many challenging problems, such as computer vision, personal-ized recommendation, and natural language processing. Those models are very computationally intensive and reach the hardware limit of the existing server and IoT devices. Thus, finding better model architectures with much less amount of computation while maximally preserving the accuracy is a popular research topic. Among various mechanisms that aim to reduce the computation complexity, identifying the zero values in the model weights and in the activations to avoid computing them is a promising direction.In this paper, we summarize the current status of the research on the computation of sparse neural networks, from the perspective of the sparse algorithms, the software frameworks, and the hardware accelerations. We observe that the search for the sparse structure can be a general methodology for high-quality model explorations, in addition to a strategy for high-efficiency model execution. We discuss the model accuracy influenced by the number of weight parameters and the structure of the model. The corresponding models are called to be located in the weight dominated and structure dominated regions, respectively. We show that for practically complicated problems, it is more beneficial to search large and sparse models in the weight dominated region. In order to achieve the goal, new approaches are required to search for proper sparse structures, and new sparse training hardware needs to be developed to facilitate fast iterations of sparse models.
Efficient Rate Splitting Method Using Successive Beamforming Techniques

It has been shown that rate splitting multiple access (RSMA) promises high data rates in the multi-user multiple-input single-output broadcast channel (MISO BC) with superior performance under imperfect channel state information (CSI) and the possibility to fulfill various quality of service (QoS) constraints. In this work, we use the 1-layer RS approach for the sum rate maximization under a total power constraint in the multi-user multiple-input multiple-output broadcast channel (MIMO BC). We adapt the iterative weighted minimum mean squared error (WMMSE) approach to the MIMO BC. However, we propose an efficient approach that splits the optimization problem into a "private" part based on the previously proposed linear successive allocation (LISA) method, a "common" part carried out by an iteratively SINR maximizing method, and a power allocation part using the waterfilling algorithm. Numerical simulations show performance gains in the medium and high SNR region when applying the proposed method.
One-Way Observation-based Cooperative Robot Mapping

This paper addresses the problem of cooperative mapping in multi-robot SLAM (simultaneous localization and mapping) with unknown initial relative poses among robots. If mutual observation measurements between robots are available when the robots encounter each other, the map transformation between robots for cooperative mapping can be easily obtained. However, the mutual observation measurements require too strict assumptions such as a rendezvous and encounters, which is not practical in real multi-robot systems. Moreover, the mutual observation measurements may contain inevitable errors due to the errors in sensors. To relax the assumption and correct the errors, this paper proposes a one-way observation-based technique for cooperative mapping. The proposed technique was tested with datasets obtained by real experiments with two mobile robots. Each robot was equipped with a sensor fusion system to observe other robots. The test results showed that the proposed technique worked well and improved the accuracy of the cooperatively produced map.
IoT Ecosystems Design: A Multimethod, Multicriteria Assessment Methodology

This article proposes a methodology to assist decision makers in the selection of a more proper device system for a specific task, a versatile methodology providing mechanisms for an assessment based on multicriteria with the capacity to apply different decision methods, taking also into consideration criteria constraints defined by stakeholders. Decision makers are able to have better reasoning and more aware analysis of diverse (e.g., hardware architecture and communication protocols) and very often contradicting criteria, such as energy consumption versus computation speed. This is addressed using a model-driven-based approach, which gives support for a high openness to the use of different, new, and even user-defined decision methods, including criteria and respective constraints through their formal specification. Proposing an assessment methodology with multimethods, multicriteria, and multiconstraints, this work tries to answer which methods could be applied or developed to assist in devices [i.e., Internet-of-Things (IoT) systems] assessment showing that a more conscious/aware, accurate selection of the more suitable device system(s) can be made, and consequently improve IoT ecosystems design.
Haptic-guided shared control grasping: collision-free manipulation

We propose a haptic-guided shared control system that provides an operator with force cues during reach-to-grasp phase of tele-manipulation. The force cues inform the operator of grasping configuration which allows collision-free autonomous post-grasp movements. Previous studies showed haptic guided shared control significantly reduces the complexities of the teleoperation. We propose two architectures of shared control in which the operator is informed about (1) the local gradient of the collision cost, and (2) the grasping configuration suitable for collision-free movements of an aimed pick-and-place task. We demonstrate the efficiency of our proposed shared control systems by a series of experiments with Franka Emika robot. Our experimental results illustrate our shared control systems successfully inform the operator of predicted collisions between the robot and an obstacle in the robot’s workspace. We learned that informing the operator of the global information about the grasping configuration associated with minimum collision cost of post-grasp movements results in a reach-to-grasp time much shorter than the case in which the operator is informed about the local-gradient information of the collision cost.
An Algorithm for Accurate Detection and Correction of Technical and Nontechnical Losses Using Smart Metering

Power losses in electric distribution systems are categorized into technical losses (TL) and nontechnical losses (NTL). TL refer to the heat losses in the distribution system components. NTL, however, refer to losses that come in different shapes and forms, such as tampering with smart meters, attacking the data transmitted from smart meters, malfunctioning of smart meters, and tapping service cables. To accurately detect and correct NTL, it is essential to first estimate the TL. Estimating TL requires knowledge of the network topology and cable impedances, which might not be readily available for the concerned utility company. This article proposes an algorithm with the following functions: remotely characterizing and updating the cable impedances, detecting and classifying the type of losses, estimating the TL and NTL when a smart meter is in error, estimating these losses due to tapping a power cable by a registered or an unregistered user, and estimating these losses due to a cyber-attack. Both active and reactive powers are considered. The proposed algorithm deploys a modified version of the Hamming code, which is originally used in the detection and correction of errors in binary data transmission. Simulation results verify the accuracy and effectiveness of the proposed algorithm.
Parasitic Model to Describe Breakdown in Stacked-FET SOI Switches

A simple passive capacitance model has been optimized to predict breakdown in a stacked SOI FET. Specifically, as the number of FETs in a switch increases, an equivalent increase in breakdown is not seen in hardware; instead, the breakdown performance saturates as the number of stacks in the FET increases. This phenomenon is not predicted by the FET foundry model. This work is focused on FETs for RF switches in flip chip topologies. As a result of this work, the different components that contribute to off-state capacitances were also described which is important for model development and accuracy.
Sparse Activity, Timing Detection and Channel Estimation for Grant-Free Uplink Communications

This paper considers a grant-free uplink scenario in which the user activity (UA), the timing offsets (TOs), and the channel state information (CSI) of user equipments (UEs) are unknown to the serving base station (BS). In this scenario, the number of potential UEs is large while only a few UEs are active. Due to the sparse nature of the UA, a detection algorithm using approximate message passing (AMP), a compressed sensing (CS) algorithm, is proposed to recover the UA, TOs, and CSI. The proposed algorithm maps the asynchronous system to a virtual system and applies AMP to it. After AMP converges, to minimize the detection error probability, a Bayes test is derived and utilized. Besides, state evolution (SE) analysis is conducted on the virtual system to predict the performance of the proposed algorithm. Simulation results show that when the number of pilot symbols is large enough, the proposed algorithm can achieve the same detection error probability and channel estimation error as those of an ideal system in which the UEs are synchronized. Analytical results show that SE is able to predict the minimum number of pilot symbols needed to achieve a required detection error probability, and predict the performance when the number of pilot symbols is large.
ARNA, a Service robot for Nursing Assistance: System Overview and User Acceptability

Using robots capable of collaboration with humans to complete physical tasks in unstructured spaces is a rapidly growing approach to work. Particular examples where increased levels of automation can increase productivity include robots used as nursing assistants. In this paper, we present a mobile manipulator designed to serve as an assistant to nurses in patient walking and patient sitting tasks in hospital environments. The Adaptive Robotic Nursing Assistant (ARNA) robot consists of an omnidirectional base with an instrumented handlebar, and a 7-DOF robotic arm. We describe its components and the novelties in its mechanisms and instrumentation. Experiments with human subjects that gauge the usability and ease of use of the ARNA robot in a medical environment indicate that the robot will get significant actual usage, and are used as a basis for a discussion on how the robot’s features facilitate its adaptability for use in other scenarios and environment.
Design of a Broadband Integrated Notch Filter in Silicon Nitride

A broadband integrated notch filter, using the silicon nitride (Si3N4) platform, is presented. It achieves an extinction ratio (ER) of 60 dB and a full width at half maximum (FWHM) of 10 nm at the central wavelength (CW) 785 nm. The main filter components are Bragg gratings (BGs). For separating the occurring reflections from the input waveguide, two identical BGs are combined with a directional coupler (DC) acting as optical circulator. The 3-dB bandwidth of the passband (790 nm to 1200 nm) is more than 400 nm.
Low Power Tiny Binary Neural Network with improved accuracy in Human Recognition Systems

Human Activity Recognition requires very high accuracy to be effectively employed into practical applications, ranging from elderly care to microsurgical devices. The highest accuracies are achieved by Deep Learning models, but these are not easily deployable in handheld or wearable devices with very constrained resources. We therefore present a new HAR system suitable for a compact FPGA implementation. A new Binarized Neural Network (BNN) architecture achieves the classification based on data from a single tri-axial accelerometer. From our experiments, the effect of gravity and the unknown orientation of the sensor cause a degradation of the accuracy. In order to compensate for these issues, we propose a HW-friendly algorithm to pre-process the raw acceleration signal. Moreover, the very low power and hardware friendly BNN has been trained and validated on the PAMAP2 dataset, for which the pre-processing operations increase the accuracy from 51% to 99% in the best case. Aiming for a low-power design, we designed both a custom circuit to perform the pre-processing operations and a hardware accelerator for the BNN. The design on FPGA features a power dissipation of 72 mW and occupies 6788 LUTs.
Dynamical analysis of the neural and equilibrium seeking movement activity

This work is devoted to the study of the process of maintaining equilibrium in an experiment with a balance platform. The conducted experiment is very original in comparison with similar experiments conducted using stabilized platforms with remote control due to the presence of active feedback from the subject. We have analyzed the effect of learning from session to session during the experiment. We observe the changes in the patterns of electrical activity of the brain that occurred at the time of equilibrium for the main EEG activity frequency ranges.
Compact Six-Port Network Using Lange Coupler For Sub-6 GHz Fifth Generation Communication

This paper presents a wide band six port network (SPN) with two input ports and four out ports. The designed network consists of conventional wideband Lange couplers and a Wilkinson power divider having features of out of band harmonic suppression over a wide frequency. Operation band of the SPN extends from 2.3 - 4.0 GHz covering IEEE 802.11 WLAN band at 2.4 GHz and sub-6 GHz band from 3.3 - 3.8 GHz for 5G application. A good matching at the input ports are achieved with return loss of better than 20 dB for the entire frequency range with minimum isolation between the ports is 12 dB. At frequency 3.5 GHz the output powers at the four ports are -5.56 dB, -5.47 dB, -7.07 dB, -7.16 dB with input at port-1 and the powers are -6.05 dB, -7.8 dB, -5.02 dB, -6.56 dB with input at port-2. Differential phase between two adjacent output ports are ± 90 degree.
Generalized LMRD Code Bounds for Constant Dimension Codes

In random network coding so-called constant dimension codes (CDCs) are used for error correction and detection. Most of the largest known codes contain a lifted maximum rank distance (LMRD) code as a subset. For some special cases, Etzion and Silberstein have demonstrated that one can obtain tighter upper bounds on the maximum possible cardinality of CDCs if we assume that an LMRD code is contained. The range of applicable parameters was partially extended by Heinlein. Here we fully generalize those bounds, which also sheds some light on recent constructions.
Towards a Non-Stationary Correlated Fading Process for Diffuse Scattering in Ray Tracing

In this paper we introduce the AIT ray tracer (RT) that is able to accurately simulate propagation effects of wireless communication channels. It covers the classical propagation mechanisms such as specular reflections, transmission and edge-diffraction. The novelty of our RT is that it allows to obtain correlated diffuse scattering and, thus, provides a time-variant Doppler spectral density. This is achieved by introducing a lattice-based surface tiling, which does not alter the position of the scattering points during simulation but provides high resolution diffuse scattering. The selection of the basis vectors for the finite lattice ensures that each ray falls into a separate delay bin (at least for first-order scattering). We implement our RT using the NVIDIA OptiX ray tracing engine, this enables us to trace a vast amount of rays in a single pass. We compare our RT simulations to a measurement conducted in a non-stationary urban intersection scenario achieving a near perfect match in terms of second order statistics.
Free Space Optical Cooperative Communications via an Energy Harvesting Harvest-Store-Use Relay

In this paper, we consider a three-node free space optical (FSO) cooperative network with an energy harvesting (EH) decode-and-forward (DF) relay. The relay is equipped with an energy buffer and implements the harvest-store-use (HSU) architecture where the harvested energy is accumulated and used for forwarding the information from the source node to the destination node. We propose a novel HSU-based relaying strategy based on the simultaneous lightwave information and power transfer (SLIPT) concept where the relay harvests energy from the optical signal transmitted by the source. Firstly, we analyze the performance of the considered system by modeling the energy buffer as a continuous-space Markov chain (MC) for the sake of deriving the limiting distribution of the stored energy. Secondly, we discretize the state space and use the resulting discrete-space MC to derive the steady-state distribution of the buffer content. Thirdly, we propose an approximate discrete-space MC for capturing the energy buffer dynamics in a simple manner. The third approach is useful for relating the outage probability to the channel coefficients and average amounts of harvested energy in a simple closed-form manner. Simulation results validate the presented analytical evaluation and demonstrate the performance improvement that is achieved by the proposed scheme.