Miracle-dz/UniFAR-FTUs huggingface dataset:
Coverage-Guided Learning-Assisted Grammar-Based Fuzzing

Grammar-based fuzzing is known to be an effective technique for checking security vulnerabilities in programs, such as parsers, which take complex structured inputs. Unfortunately, most of existing grammar-based fuzzers require a lot of manual efforts of writing complex input grammars, which hinders their practical use. To address this problem, recently proposed approaches use machine learning to automatically acquire a generative model for structured inputs conforming to a complex grammar. Even such approaches, however, have major limitations: they fail to learn a generative model for instruction sequences, and they cannot achieve good coverage of instruction-parsing code. To overcome such limitations. this paper proposes a collection of techniques for enhancing learning-assisited grammar-based fuzzing. Our approach allows for the learning of a generative model for instruction sequences by training a hybrid character/token-level recursive neural network. In addition, we exploit coverage metrics gathered during previous runs of fuzzing in order to efficiently refine (or fine-tune) the learnt model so that it can make high coverage-inducing new inputs. Our experiments with a real PDF parser show that our approach succeeded in generating new sequences of instructions (in PDF page streams) that induce better code coverage (of the PDF parser) than state-of-the-art learning-assisted grammar-based fuzzers.
Social Network Group Identification based on Local Attribute Community Detection

Online social network has become an important platform for people's daily communication, information dissemination and sharing. The similarity of attribute characteristics such as content and behavior is very important to evolution and control of social network groups. Therefore, it is a challenge to consider the topology and attributes of network nodes in community identification effectively. In this paper, a social group identification method based on local attribute community detection (LA-CD) is proposed. a novel node pair similarity framework is proposed, and a novel local similarity distance factor is defined. It can eliminate the problem that the local similarity of nodes is too large due to the large number of adjacent nodes, and prevent the situation that having more neighbor sets can get lower local similarity values instead. Experiments on several real attributed ego-networks and artificial benchmark networks show that LA-CD can discover more real and effective network community than other state-of the-art approaches.
Deletion Propagation for Multiple Key Preserving Conjunctive Queries: Approximations and Complexity

This paper studies the deletion propagation problem in terms of minimizing view side-effect. It is a problem funda-mental to data lineage and quality management which could be a key step in analyzing view propagation and repairing data. The investigated problem is a variant of the standard deletion propagation problem, where given a source database D, a set of key preserving conjunctive queries Q, and the set of views V obtained by the queries in Q, we try to identify a set T of tuples from D whose elimination prevents all the tuples in a given set of deletions on views △V while preserving any other results. The complexity of this problem has been well studied for the case with only a single query. Dichotomies, even trichotomies, for different settings are developed. However, no results on multiple queries are given which is a more realistic case. We study the complexity and approximations of optimizing the side-effect on the views, i.e., find T to minimize the additional damage on V after removing all the tuples of △V. We focus on the class of key-preserving conjunctive queries which is a dichotomy for the single query case. It is surprising to find that except the single query case, this problem is NP-hard to approximate within any constant even for a non-trivial set of multiple project-free conjunctive queries in terms of view side-effect. The proposed algorithm shows that it can be approximated within a bound depending on the number of tuples of both V and △V. We identify a class of polynomial tractable inputs, and provide a dynamic programming algorithm to solve the problem. Besides data lineage, study on this problem could also provide important foundations for the computational issues in data repairing. Furthermore, we introduce some related applications of this problem, especially for query feedback based data cleaning.
Analysis of a failure mechanism occurring in SiGe HBTs under mixed-mode stress conditions

This paper presents an investigation of hot carrier degradation in advanced SiGe HBTs. This failure mechanism is observed under mixed mode stress conditions. Its physical location is examined through DC measurements from 2D transistors $(\mathrm{L_{E}} > > \mathrm{W}_{\mathrm{E}})$ with different emitter width WE. TCAD simulations were performed to confirm its physical origin and location. The methodology permits to identify the origin of the degradation mechanism located at the emitter-base spacer interface. It is based on the scalable analysis of the DC characteristics measured after stressing the devices during 10 000s under mixed mode (MM) stress conditions. This study confirms the mechanism responsible of the MM degradation for SiGe HBTs.
A 93.4–104.8-GHz 57-mW Fractional- ${N}$ Cascaded PLL With True In-Phase Injection-Coupled QVCO in 65-nm CMOS Technology

A fully integrated 93.4–104.8-GHz 57-mW fractional-<inline-formula> <tex-math notation="LaTeX">${N}$ </tex-math></inline-formula> cascaded phase-locked loop (PLL) with true in-phase injection-coupled quadrature voltage-controlled oscillator (QVCO) is reported. By cascading the fractional-<inline-formula> <tex-math notation="LaTeX">${N}$ </tex-math></inline-formula> PLL and the subsampling PLL, good phase noise, high resolution, and wide acquisition range are achieved simultaneously. The transformer-based true in-phase injection coupled technique is adopted in the QVCO to obtain both low phase noise and low-power consumption. The proposed cascaded PLL was fabricated in a 65-nm CMOS technology with silicon size of 0.88 mm<sup>2</sup>. The measured phase noise of QVCO and PLL is −113.26 and −106.63 dBc/Hz at 10-MHz offset, respectively. The FOM and FOM<sub>T</sub> of the QVCO at 10-MHz offset are −178.4 and −180.0 dBc/Hz, respectively. The frequency resolution of the 100-GHz output is less than 3.6 kHz.
Behavioural phenotyping of sodium‐myo‐inositol cotransporter heterozygous knockout mice with reduced brain inositol

Inositol plays a key role in dopamine, serotonin, noradrenaline and acetylcholine neurotransmission, and inositol treatment is reported to have beneficial effects in depression and anxiety. Therefore, a reduction in brain intracellular inositol levels could be a cause of some psychiatric disorders, such as depression or anxiety. To determine the behavioural consequences of inositol depletion, we studied the behaviour of sodium‐dependent myo‐inositol cotransporter‐1 heterozygous knockout mice. In heterozygous mice, free inositol levels were reduced by 15% in the frontal cortex and by 25% in the hippocampus, but they did not differ from their wild‐type littermates in cholinergic‐mediated lithium–pilocarpine seizures, in the apomorphine‐induced stereotypic climbing model of dopaminergic system function, in the Porsolt forced‐swimming test model of depression, in amphetamine‐induced hyperactivity, or in the elevated plus‐maze model of anxiety. Reduction of brain inositol by more than 25% may be required to elicit neurobehavioural effects.
A Revenue-Maximizing Bidding Strategy for Demand-Side Platforms

In real-time bidding (RTB) systems for display advertising, a demand-side platform (DSP) serves as an agent for advertisers and plays an important role in competing for online advertising spaces by placing proper bidding prices. A critical function of the DSP is formulating proper bidding strategies to maximize key performance indicators, such as the number of clicks and conversions. However, many small and medium-sized advertisers’ main goal is to maximize revenue with an acceptable return on investment (ROI), rather than simply increase clicks or conversions. Most existing approaches are inapplicable of satisfying the revenue-maximizing goals directly. To solve this problem, we first theoretically analyze the relationships among the conversion rate, ROI, and ad cost, and how they affect revenue. By doing so, we reveal that it is a challenge to increase revenue by relying solely on improving ROI without considering the impact of the ad cost. Based on this insight, the maximal revenue (MR) bidding strategy is proposed to maximize revenue by maximizing the ad cost with a desirable ROI constraint. Unlike previous studies, the proposed MR first distinguishes bid prices from ad costs explicitly, which makes it more applicable to the real second-price auction (GSP) auction mechanism in RTB systems. Then, the winning function is empirically defined in the form of tanh that provides a promising solution for estimating ad costs by jointly considering ad costs with the winning function. The experimental results based on two real-world public datasets demonstrate that the MR significantly outperforms five state-of-the-art models in terms of both revenue and ROI.
On dynamic multi-objective optimization, classification and performance measures

In this work we focus on defining how dynamism can be modeled in the context of multi-objective optimization. Based on this, we construct a component oriented classification for dynamic multi-objective optimization problems. For each category we provide synthetic examples that depict in a more explicit way the defined model. We do this either by positioning existing synthetic benchmarks with respect to the proposed classification or through new problem formulations. In addition, an online dynamic MNK-landscape formulation is introduced together with a new comparative metric for the online dynamic multi-objective context.
An Emotional Symbolic Music Generation System based on LSTM Networks

With the development of AI technology in recent years, Neural Networks have been used in the task of algorithmic music composition and have achieved desirable results. Music is highly associated with human emotion, however, there are few attempts of intelligent music composition in the scene of expressing different emotions. In this work, Biaxial LSTM networks have been used to generate polyphonic music, and the thought of LookBack is also introduced into the architecture to improve the long-term structure. Above all, we design a novel system for emotional music generation with a manner of steerable parameters for 4 basic emotions divided by Russell’s 2-demonsion valence-arousal (VA) emotional space. The evaluation indices of generated music by this model is closer to real music, and via human listening test, it shows that the different affects expressed by the generated emotional samples can be distinguished correctly in majority.
RECi-P: Rapid, Economical Circuit Prototyping

Rapid, Economical Circuit Prototyping (RECi-P) is a method for the rapid prototyping of conductive traces that can be used for electronic circuits. This method utilizes an inexpensive craft cutter that can cut copper tape with sub-millimeter accuracy. The layout of cut copper tape pieces is preserved, making it easier to accurately create complicated patterns. Using RECi-P, designs can be fabricated and tested in under 30 minutes, for approximately the same cost as prototypes made by manually cutting copper tape. Using a 5-GHz coupled-line bandpass filter as a demonstration device, three fabrication methods were compared: RECi-P, photolithography and wet etching, and mechanical milling. The performance of the filter fabricated using RECi-P is similar to that of the other methods, showing that RECi-P is a rapid, economical method for the prototyping of devices and circuits.
PIT-HOM: an Extension of Pitest for Higher Order Mutation Analysis

Mutation testing is a well-known, effective, fault-based testing criterion. First order mutation introduces defects in the form of a single small syntactic change. While the technique has been shown to be effective, it has some limits. Higher order mutation, where the faults introduced include multiple changes, has been proposed as a way to address some of these limits. Although the technique has shown promising results, there is no practical tool available for the application and study of higher order mutation on Java programs. In this paper we present PIT-HOM, an extension of Pitest (PIT) for higher order mutation. Pitest is a practical mutation analysis tool for Java, applicable on real-world codebases. PIT-HOM combines mutants in a same class to create higher order mutants of user-defined orders, it runs the mutants and reports the results in an easy to process format. We validate PIT-HOM using two small Java programs and report its performance as well as some characteristics of the mutants it creates.
SSK Performance with SWIPT based Dual-Hop AF Relay over Rayleigh Fading

A cooperative communication system with space shift keying (SSK) modulation and simultaneous wireless information and power transfer (SWIPT) scheme is proposed. SWIPT can eliminate the need of external power supply at the relay whereas SSK modulation scheme reduces inter-channel interference, excludes inter antenna synchronization requirement and the number of radio frequency chains. An upper bound expression for the average bit error probability (ABEP) is obtained with multiple amplify-forward relays and a direct link from source node to destination node. Further, ABEP is analyzed for partial relay selection operation. Numerical and computer simulation results demonstrate performance improvement for SSK modulation combined with SWIPT.
Couple VCT clients in Ethiopia: A heterogeneous HIV risk group

Abstract Studies show reduced HIV risk behaviors after couple voluntary counseling and testing (VCT), either resulting from the couple counseling process or the type of people it attracts. A total of 1858 sexually active individual VCT clients in partnerships were compared to 866 sexually experienced couple VCT participants with multilevel logistic regression. Sexually experienced couple VCT clients were also compared to those couple VCT clients who never had sex. Among sexually experienced participants in partnerships, women, non-premarital testers, and those who felt at risk for HIV were less likely to attend couple VCT than individual VCT. Among couple VCT clients, sexually inexperienced individuals were more likely to be: testing for the first time, premarital testers, and more educated than those who were sexually experienced. Couple VCT's effectiveness might partly result from who it attracts. Addressing the diverse needs of a heterogeneous testing population is a programmatic challenge for couple VCT in Ethiopia.
An Example of Underwater Acoustic Network based on Modems Incorporating Open-Source Networking Software Framework

Organization of real-time access to data collected underwater requires sensors to be fitted out with digital communication means. Also, underwater autonomous vehicles (AUVs) operating in a group require intensive exchange of navigation data when engaged in cooperative maneuvering or performing coordinated measurements, or agreeing on modifying the current mission with an operator on the surface support vessel. This paper presents a development of an underwater acoustic sensor network. The technology enables data transfer in a network of an arbitrary topology, in which the number of relay nodes between data source and data receiver may be fixed or variable, data delivery route can be static or dynamic. Particular implementation of the digital underwater acoustic network is represented in form of a program framework (EviNS-Evologics intelligent Networking Software) – a stack of network protocols, each of which is designed to solve the problem of hydro-acoustic data delivery under certain conditions of underwater acoustic environment.
An Advanced Cooperative Positioning Algorithm Based on Improved Factor Graph and Sum-Product Theory for Multiple AUVs

In this research, a novel autonomous underwater vehicle (AUV) cooperative positioning algorithm is proposed to solve the implementation problem of multi-sensor-fusion applications. Different from the traditional methods [i.e., the extended Kalman filter (EKF), unscented Kalman filter (UKF), and iteration extended Kalman filter (IEKF)], which have large linearity error under the condition of nonlinear observation equation when multiple AUV are cooperative positioning, the proposed algorithm utilized the Baysis filter to solve the AUV cooperative problem. Factor graph and sum-product (FGS)-based cooperative positioning algorithm is established to mathematically implement the Bayse filter by converting the global function estimation problem into a local function sum-product estimation problem. Furthermore, to improve the performance of the proposed algorithm, a robust data processing method is presented by introducing a transform matrix to the estimated position information. To demonstrate and verify the proposed methods, the simulation and real tests in different scenarios are performed in this research. Compared with the traditional EKF, UKF, and IEKF cooperative positioning algorithm, the positioning error of the proposed improved FGS (IFGS) cooperative positioning algorithm is obviously smaller than that of the other three algorithms. Moreover, the IFGS algorithm can reduce the complexity of the algorithm, available improving the computational speed of the whole system. This proposed algorithm has important theoretical and practical value for the both industry and academic areas.
An Efficient Resonant Converter Based Charging Scheme for Electric Vehicle

The acceptance of electric vehicle around the world, represents a brand new paradigm for the transportation sector and for the particular and future power grids. Generally electric vehicles employ on board chargers. This paper suggests another candidate for isolated unidirectional DC/DC converter in electric vehicle on-board charger based on Full bridge- LLC resonant converter. Here a simple method is proposed to improve the charging profile. The circuit possess the inherent advantages like good voltage regulation performance at light load conditions and soft switching of power devices. The feasibility of proposed model has been verified with MATLAB/Simulink.
Information Diffusion Prediction via Recurrent Cascades Convolution

Effectively predicting the size of an information cascade is critical for many applications spanning from identifying viral marketing and fake news to precise recommendation and online advertising. Traditional approaches either heavily depend on underlying diffusion models and are not optimized for popularity prediction, or use complicated hand-crafted features that cannot be easily generalized to different types of cascades. Recent generative approaches allow for understanding the spreading mechanisms, but with unsatisfactory prediction accuracy. To capture both the underlying structures governing the spread of information and inherent dependencies between re-tweeting behaviors of users, we propose a semi-supervised method, called Recurrent Cascades Convolutional Networks (CasCN), which explicitly models and predicts cascades through learning the latent representation of both structural and temporal information, without involving any other features. In contrast to the existing single, undirected and stationary Graph Convolutional Networks (GCNs), CasCN is a novel multi-directional/dynamic GCN. Our experiments conducted on real-world datasets show that CasCN significantly improves the prediction accuracy and reduces the computational cost compared to state-of-the-art approaches.
Compressive Sensing-based Colocated MIMO Radar with Reduced Number of Transmit Antennas

Exploiting the sparsity of the radar scenes, the idea of compressive sensing-based (CS-based) MIMO radars has been promoted either to improve the detection/estimation performance or to reduce the cost and the complexity of the conventional MIMO radars (e.g. by reducing the number of antennas). In this paper, we propose a joint scheme of antenna placement and power allocation aiming at reducing the required number of transmit antennas as compared to the conventional colocated CS-based MIMO radar. To not sacrifice the sparse recovery performance (and thereby the detection performance), we constrain the coherence of the resulting sensing matrix to not exceed the coherence value of the corresponding conventional MIMO array. We derive this problem as a constrained $l_{0}$-norm minimization. To solve it, we develop an iterative algorithm using smoothed $l_{0}$-norm which we call adapted SL0 (ASL0). Using numerical simulations, we show that the proposed scheme yields a lower number of transmit antennas compared to the conventional MIMO radar while exhibiting the same performance.
Analysis and Resonant Length Formulation of Dual Band Microstrip Antenna with Modified Ground

A dual band microstrip antenna with defected ground plane is proposed in this paper. The dual bands are achieved by appropriately embedding pair of slots on the ground plane to tune TM30 mode resonant frequency. These slots essentially reduces $\mathbf{TM}_{\pmb{30}}$ mode frequency and places it closer to fundamental mode frequency. Broadside radiation pattern is observed at both the frequencies with maximum gain of nearly 3 dBi. The effect of the ground slot is studied and are portrayed by showing resonance plot for variation in the slot length. Empirical formulation of resonant length for fundamental as well as higher order $\mathbf{TM}_{\pmb{30}}$ mode frequency is suggested in the paper. The calculated frequencies obtained using the proposed formula closely matches with the simulated values. Thus these formulas can be applied to design dual band antenna with similar configuration at any given operating frequency.
Design of MMIC Subharmonic Mixer for K-band Receiver Based on 0.25 µm SiGe BiCMOS Technology

A block diagram of K-band SoC receiver frontend (FE) is proposed. It is shown that the use of subharmonic mixer (SM) as well as phase shifter in local oscillator (LO) channel makes possible the implementation of SiGe FE with smaller dimensions. The MMIC SM is designed using single-balanced topology based on Gilbert cell. To form the quadrature LO signal, a polyphase filter and passive balun are used. In the 18.25 GHz RF frequency band, the 0.25 μm SiGe BiCMOS MMIC SM provides conversion gain of $G _{C} =$-15. –19.5 dB; return losses at RF and IF ports better than -8 dB; RF-IF isolation better than –14. –27 dB, LO-RF and LO-IF isolations better than -40 dB. The 1-dB compression point for input RF signal is greater than -11 dBm at $P _{LO} =$18 dBm. Die area of the SM is $1.5 \times 0.9$ mm2 including the pads