Miracle-dz/UniFAR-FTUs huggingface dataset:
URefFlow: A Unified Android Malware Detection Model Based on Reflective Calls

In Android malware detection, sensitive data-flows provide more accurate information on the application's behavior than regular features such as signatures and permissions. Currently, Android static taint analysis is widely adopted to identify sensitive data-flows because of its high code coverage and low false negative rate. However, existing static taint analysis tools cannot effectively analyze applications that adopt Android reflection mechanism. Reflection mechanism can block the control-flows and data-flows of the application. When constructing a call graph, the call information will point directly to the system's reflection processing method, rather than the actual method invoked by the application. This significantly affects the accurate representation of the application's behavior. To address this issue, this paper proposes a unified Android malware detection model based on reflective calls named URefFlow, in which the reflective call statement is replaced by the non-reflective call statement to make the reflective calls explicit by combining the parameters of the reflective calls into standard function calls. After extracting the complete sensitive data-flows with reflective calls from an application, we analyze the characteristics of these data-flows to determine whether the application is malicious. Evaluation results on thousands of applications show that URefFlow can achieve an impressive detection accuracy of 95.6% with a false positive rate of 0.8%. In addition, the proposed approach complements well with existing static stain analysis techniques.
DrosophilaTGIF Proteins Are TranscriptionalActivators

ABSTRACT The information carried by transforming growth factor β (TGF-β) signaling molecules induces profound responses in target cells. To restrict this information to appropriate cells, TGF-β signaling pathways are tightly regulated by dynamic interactions with transcriptional activators and repressors. Numerous cross-species experiments have shown that TGF-β family members and their signal transduction machinery (receptors and Smad signal transducers) are functionally conserved between vertebrates and invertebrates. TG-interacting factor (TGIF) is a homeodomain-containing transcriptional corepressor of TGF-β-dependent gene expression in mammals that is associated with holoprosencephaly in humans. Here we report a biochemical analysis of TGIF from zebra fish and Drosophila. Our study reveals an unprecedented role reversal between vertebrate and invertebrate TGIF proteins. Zebra fish TGIF, like its mammalian relative, interacts with general corepressors and represses TGF-β-responsive gene expression. We identified a tandem duplication of TGIF genes in Drosophila. In contrast to vertebrate TGIFs, both Drosophila TGIFs strongly activate transcription. We also demonstrate that Drosophila TGIF proteins physically interact with both Mad and dSmad2, suggesting a role in Dpp and activin signaling. Thus, dTGIF may be the first transcription factor in the Drosophila activin pathway. Overall, our study suggests that assumptions about the functional equivalence of conserved proteins must be validated experimentally.
Test Pattern Generation for Approximate Circuits Based on Boolean Satisfiability

Approximate computing has gained growing attention as it provides trade-off between output quality and computation effort for inherent error tolerant applications such as recognition, mining, and media processing applications. As a result, several approximate hardware designs have been proposed in order to harness the benefits of approximate computing. While these circuits are subjected to manufacturing defects and runtime failures, the testing methods should be aware of their approximate nature. In this paper, we propose an automatic test pattern generation methodology for approximate circuits based on boolean satisfiability, which is aware of output quality and approximable vs non-approximable faults. This allows us to significantly reduce the number of faults to be tested, and test time accordingly, without sacrificing the output quality or test coverage. Experimental results show that, the proposed approach can reduce the fault list by 2.85× on average while maintaining high fault coverage.
Adiabatic Implementation of Manchester Encoding for Passive NFC System

Energy plays an important role in NFC passive tags as they are powered by radio waves from the reader. Hence reducing the energy consumption of the tag can bring large interrogation range, increase security and maximizes the reader’s battery life. The ISO 14443 standard utilizes Manchester coding for the data transmission from passive tag to the reader in the majority of the cases for NFC passive communications. This paper proposes a novel method of Manchester encoding using the adiabatic logic technique for energy minimization. The design is implemented by generating replica bits of the actual transmitted bits and then flipping the replica bits, for generating the Manchester coded bits. The proposed design was implemented using two adiabatic logic families namely; Positive Feedback Adiabatic Logic (PFAL) and Improved Efficient Charge Recovery Logic (IECRL) which are compared in terms of energy for the range of frequency variations. The energy comparison was also made including the power-clock generator designed using 2-stepwise charging circuit (SWC) with FSM controller. The simulation results presented for 180nm CMOS technology at 1.8V power supply shows that IECRL shows approximately 40% less system energy compared to PFAL family.
Droop Control Based on Improved Virtual Impedance in a Stand-Alone Microgrid

A virtual impedance approach is added to the inverter control loop to improve active and reactive power sharing when the line impedance is less inductive. However, the conventional droop control with virtual impedance cannot properly solve adverse impacts caused by nonlinear loads and noise, such as output distortion. Therefore, this paper proposed virtual impedance with a high-order general-integrator (HOGI) approach to reduce distortion of the output voltage and current as well as to improve power-sharing between parallel distributed generations (DGs). The Matlab/Simulink simulation results verified that the proposed method improved the control system performance.
ASSOCIATIONS BEIWEEN BREAST C ' ANCER AND PlASMA ' IRIGLYCERIDE AND OiOIESTEROL

A case-control study investigating the association between plasna lipids and breast cancer was conducted in Buffalo, New York. Women aged 30-80 conpleted a questionnaire and donated a fasting blocxi sample prior to diagnostic breast biopsies. '! he 83 women fO\. li'Xl to have breast cancer (cases) had significantly higher plasna triglyceride values than did the 113 women fO\. li'Xl not to have breast cancer (controls). I.ower betacarotene values were associated with breast cancer, but only in those women with elevated triglyceride or cholesterol. Plasna cholesterol values were lower in those breast cancer cases presenting with a more advanced stage of disease suggesting that metabolic effects of clinical and preclinical breast cancer may lower cholesterol levels. The obseJ:vation of a positive association with triglycerides and a negative association with beta-carotene is consistent with the hypothesis that women who develop breast cancer may consume diets higher in total and saturated fat, and lower in carotene-rich vegetables. Running title: Breast cancer and plasna lipids
Student Eye Gaze Tracking During MOOC Teaching

In order to solve the problem that the teacher cannot monitor students e-learning status and evaluate the students e-learning effect during MOOC teaching, in this paper, we capture the student learning images by computer camera and adopt the "Three Angles Synthesis" to judge whether the student is watching the teaching video online. First locate the center of the iris by the Average Feature Point method to calculate iris deflection angle and the distance from the iris center to the eye center; and detect the face key feature points(eye, nose, mouth, etc.) by calling face key point detector in Dlib to determine the face rotation angel; then extract the student target body by Maximum Connected Domain Moment Characteristic method to calculate the student body tilt angle; last determine whether the three angles meet the giving conditions, further judge the student is watching the teaching video online or not.
Graphene oxide multilayers: Synthesis, properties and possible applications in electronics

Preparation of graphene via oxidization and subsequent exfoliation of graphite is one of the most common techniques. However, this technique has the disadvantages of being time consuming and environmentally toxic for large-scale production. Therefore, in this work we proposed and employed a new, simple, cost-effective pyrolytic method to synthetize graphene oxide multilayers samples (GO) by using the bamboo pyroligneous acid (BPA) as material source. The GO-BPA samples were synthesized by using the double thermal decomposition (DTD)-method under controlled nitrogen atmosphere in an automated pyrolysis system for different carbonization temperatures varying from 673 to 973 K. The morphological, structural, compositional, vibrational, electrical and magnetic properties were studied and it was found that GO-BPA samples exhibit nanoplatelets morphology with thicknesses varying from 25 to 100 nm and lateral size varying from 5 to 100 µm, polycrystalline structure with crystal size varying from 1.3 to 1.9 nm, vibrational characteristics of thermal isolator material with conduction mainly by phonon-phonon interaction, electrical behavior as narrow band-gap semiconductor system at band-gap values varying from 0.11 to 0.30 eV with conduction mainly by carrier-impurity interaction and magnetic properties of soft material with ferromagnetism order observed at room temperature showing saturation magnetization around 40 × 10–3 emu/g induced mainly by boundary defects presence in the samples. These results revealed a DTD-method as a new technique to obtain graphene oxide multilayers with high stability and reproducibility in its transport properties and suggest these samples in some possible applications in electronics as sensors and devices.
Secure and Efficient Anonymous Authentication Protocol for Global Roaming Services

An important contribution of ubiquitous GLobal MObility NETwork (GLOMONET) is to provide global roaming services. However, the underlying strategy shows several challenges to be achieved such as user anonymity, authenticity, security and low computation cost. Several approaches have been proposed in recent research to address these issues. Unfortunately, some of them still failed to achieve desired security and design features. This article presents a secure and efficient anonymous authentication protocol for global roaming services based on Elliptic Curve Cryptography (ECC). The protocol is formally verified using widely accepted AVISPA tool which ensures its ability to resist various security attacks. Additionally, the informal security analysis of the protocol is carried out based on individual features. The performance analysis section at the end of this article shows that the proposed protocol achieves low computation cost as compared to several recently proposed protocols and thus, making it more suitable for lightweight practical applications of roaming services over GLOMONET.
Socialite: Social Activity Mining and Friend Auto-labeling

As people's friend lists grow longer, it becomes more and more difficult to manage a friend list by labeling or grouping friends manually. In this paper, we leverage on-board sensors of smart devices and propose a social activity mining framework Socialite, which is able to achieve social group discovering and friend auto-labeling by exploring users' interactions in physical word. Socialite considers different deployment strategies and mainly contains two stages: social activity recognition and social group detection. Together with several data analysis approaches, a voting based lightweight neural network is designed for high accuracy diverse activity recognition. Then we propose a novel algorithm for social interaction feature generation and measure correlation among features of even asynchronous social activities. For system evaluation, we conduct extensive real life experiments. Results demonstrate that Socialite can recognize diverse social activities with above 94% accuracy, and 100% accuracy with our voting scheme. Socialite can also detect social groups in different scenarios with high accuracy. For example in two people activities, our proposed method achieves 92.2% accuracy for walk and 92.6% accuracy for table tennis.
Digital Commpetence Curriculum for Schools' Employees: Croatian e-Schools Project Example

The Curriculum for the Enhancement of Digital Competences of School Employees: Teachers and Associates, Principals and Administrative Staff developed as the result of Croatian e-Schools project is presented. An open curriculum approach has been chosen that characterizes the flexibility of design and is based on recommendations that allow creativity and the introduction of change in the course of implementation. The digital competence curriculum is intended for the training of beneficiaries who are considered adults, therefore specifics related to adult education are implemented. As the digitalization of society, work and education is moving fast, there is a need to set a guidance to improve digital competence. Schools should be leaders on the use of digital technologies for learning, acquiring skills and competences and to emphasize the importance of digital technologies for future education and employment. We believe that this Curriculum can help address some of the key challenges that schools are currently facing.
Security Assessment of Microfluidic Fully-Programmable-Valve-Array Biochips

The fully-programmable-valve-array (FPVA) is a general-purpose programmable flow-based microfluidic platform, akin to the VLSI field-programmable gate array (FPGA). FPVAs are dynamically reconfigurable and hence are suitable in a broad spectrum of applications involving immunoassays and cell analysis. Since these applications are safety-critical, addressing security concerns is vital for the success and adoption of FPVAs. This study evaluates the security of FPVA biochips. We show that FPVAs are vulnerable to malicious operations similar to digital and flow-based microfluidic biochips. FPVAs are further prone to new classes of attacks - tunneling and deliberate aging. The study establishes security metrics and describes possible attacks on real-life bioassays.
Color Based Person Tracking with Illumination Compensation by using Multiple Statistics of Scene

Person tracking is an important technology for several applications of video surveillance, robot vision and human interface. Key features of the person tracking are the shape and color. Especially, color information provides important information to distinguish individuals in scenes including multiple persons. However, color information is influenced by illumination color. In this paper, we propose a novel person tracking method based on color tracking with illumination color compensation. The illumination color is estimated from three statistical features obtained from the whole scene. The scene statistics are an average value, a maximum value and "gray-edge" value that means an average of edge component of the scene. Person is tracked as the concentration of registered colors by using the particle filter. In the proposed method, the positions and velocity of points are defined as a system model of the particle filter. Three likelihoods of each particle are calculated by colors compensated by three scene statistics. Then, the maximum likelihood of three likelihoods is selected as the likelihood of the particle. We conducted experiments for evaluation of the proposed method. The results showed the improvement of the accuracy of tracking in comparing with the previous method that compensated color by only average value of the scene.
Lightweight IoT Group Key Establishment Scheme From the One Time Pad

Secure group communication in the Internet of Things (IoT) requires the establishment and management of one or more group keys to provide group security services such as confidentiality of group messages. One of the main challenges in ensuring secure group communication in IoT is designing a group key establishment scheme that is feasible for nodes with limited computational capabilities. In this paper, we propose a lightweight group key establishment scheme based on fast symmetric-key encryption. We show a mechanism for designing a lightweight and secure IoT group key establishment and management scheme whose security is underpinned by the perfect secrecy provided by the One Time Pad. We then argue that the scheme is convenient for IoT group applications where nodes are resource-constrained. We prove that our scheme is secure under a threat model where the attacker has sufficiently large computational power. We also prove that the scheme provides desired group security properties such as confidentiality, key secrecy and independent group session keys generation.
RiverOpt: A Multiobjective Optimization Framework Based on Modified River Formation Dynamics Heuristic

In river formation dynamics (RFD) method, water drops pursue a probable path to flow from high altitudes to flat surface. This geographical metaphor adopts a decreasing gradient principle supported by sedimentation and erosion mechanisms to reach for a feasible solution. In this paper, a new multi-objective optimization framework, RiverOpt is presented based on a modified RFD method. In this method, the probability of selecting the next path in RFD method is modified to exploit both transverse and longitudinal slopes. Further, the sedimentation parameter in RFD method is improved by introducing a sediment coefficient. Later, an external archive is integrated with RiverOpt framework to keep track of nondominated solutions in each generation. For benchmarking the performance of the proposed framework, a set of standard multiobjective test problems is employed. The results are compared with peer multiobjective optimization algorithms using two performance indicators (i.e., generational distance and hypervolume). Experimental results show that the proposed RiverOpt framework demonstrates competitive results in terms of convergence and diversity of Pareto optimal solutions. Finally, a case study of low noise amplifier circuit is analyzed to showcase effectiveness of the proposed framework.
Time-Domain Development of Negative Refraction

Negative refraction in prisms built of periodic unit cells is a steady-state phenomenon that requires a finite amount time to develop. A signal transmitted through such a prism will initially be refracted positively. As time increases, the direction of refraction shifts toward the steady state angle of refraction. Signals that are shorter than the time required to reach steady state are not negatively refracted.
Dynamic Adaptive Mutation Based Genetic Programming for Ring Oscillator PUF

Recently, the damage caused by semiconductor counterfeit has become a serious problem in our lives. Physical Unclonable Function (PUF) has attracted attention as a countermeasure method. In the countermeasures, a ring oscillator (RO) PUF is one of the most popular PUFs. Regarding tamper resistance of RO PUFs, Genetic Programming (GP) based attacks have been proposed. However, the GP based attacks only apply the basic genetic strategy. To evaluate tamper resistance of RO PUF accurately, improvement of GP based attack for RO PUF is important. Therefore, this study proposes an accurate attack which is based on GP using dynamic adaptive mutation.
Heterogeneous Cloud Computing: Design Methodology to Combine Hardware Accelerators

Heterogeneous cloud computing servers provide access to different types of hardware accelerators in order to satisfy the computational demands that standalone general-purpose multi-processors can not deliver. The combination of different technologies provides more opportunities to accelerate the most compute-intensive applications by exploiting the key features of each type of hardware accelerator. Unfortunately, the design effort drastically increases when considering complex applications. We propose a methodology which provides an early speedup prediction when combining hardware accelerators and insights about potential performance leaks. In addition, we consider a couple of metrics to analize the computational use of the accelerators and the exploitation of the heterogeneous system. Our methodology is applied to a real-time surveillance system, which is composed of Field-Programmable Gate Arrays (FPGA) and Graphic-Processing Units (GPU). The methodology is used to provide an early speedup prediction, which is used to guide the combination of both accelerators. The achieved acceleration is only a 3.5% lower than estimated by our methodology,
Improved results on asymptotic stability criteria for additive time-varying delay system and its applications

This paper is interested with the asymptotic stability for time-varying delay system. Using the higher order reciprocally convex technique, we derived a new delay-dependent sufficient conditions for the stability analysis of considered system in terms of Linear Matrix Inequalities (LMIs) by using Lyapunov-Krasvoskii Functional (LKF) method. Finally, two numerical examples are solved to express the effectiveness and less conservatism of the derived conditions.
Predictive Iterated Kalman Filter for INS/GPS Integration and Its Application to SAR Motion Compensation

This paper deals with the problem of state estimation for the integration of an inertial navigation system (INS) and Global Positioning System (GPS). For a nonlinear system that has the model error and white Gaussian noise, a predictive filter (PF) is used to estimate the model error, and based on this, a modified iterated extended Kalman filter (IEKF) is proposed and is called predictive iterated Kalman filter (PIKF). The basic idea of the PIKF is to compensate the state estimate by the estimated model error. An INS/GPS integration system is implemented using the PIKF and applied to synthetic aperture radar (SAR) motion compensation. Through flight tests, it is shown that the PIKF has an obvious accuracy advantage over the IEKF and unscented Kalman filter (UKF) in velocity.
Design and Implementation of a Piezoelectric Accelerometer Using Arduino Mega for Detection of Vibration on the 20 kV Transformer Tank

The distribution transformer is an important tool in the power system. During operation, the transformer produces vibrations indicated on its performance. Transformer monitoring based on the condition of the transformer becomes very important due to mechanical failure resulting in different vibration patterns caused by winding, cores or both. Differences in the design and placement of sensors used can give different vibration measurement results on the transformer. This research designs piezoelectric accelerometer sensors to detect vibrations in a 20kV distribution transformer tank. The results show that the piezoelectric accelerometer sensor design has a reading accuracy of 5 × 10–5 m/s? in positive or negative acceleration, with the measuring instrument of vibration meter Lutron VB-8200 and proves that the main source of vibration caused by winding and cores located 2/3 from the bottom to the middle on the measurement of vibration on the secondary side of the transformer tank.