Miracle-dz/UniFAR-FTUs huggingface dataset:
An Approach to the Development of Software for Effective Search of Scientific Articles

The paper considers a method of information retrieval of scientific articles. Search engine users often find it difficult to formulate a query using a proper terms related to the research area. We propose an approach, in which the system does not modify the user's query but analyses the articles using natural language processing methods and adds semantically similar articles to the initial set of documents. The system for the article search was developed and tested on the collection of 280 scientific articles.
Extraction of a SPICE Model for Investigating the Cable Discharge Event in Flat Ribbon Cables Based on Transmission Line Theory

Imagining a specific SPICE model for the Cable Discharge Event (CDE) is impossible because the model depends on the cable length, material, and type. This paper aims to propose an instruction to extract a SPICE model for Flat Ribbon Cables (FRCs), which have a wide range of applications in electronics. This work introduces general information and considerations about the CDE in FRCs, and the conductor of the FRC considers a transmission line which to Extract its equivalent circuit; a technique based on S-Parameter measurement and transmission line theory is demonstrated. Also, this work regards the mutual capacitance between the conductor of FRC in the extracted SPICE model. In this work, the analytical technique and the 3D full-wave software synergize with each other to increase the reliability of the proposed SPICE model. This work evaluates the effect of cable length and termination resistance on the discharge waveform. The proposed instruction can be expanded to the other cables. It helps the designers observe the CDE impacts besides other transient events on their circuits and systems without spending much time and expense.
IOT and GSM integrated multi purpose Security system

This paper details the design and development of IoT based security surveillance system in buildings using Raspberry Pi Single Board Computer (SBC) with WiFi network connectivity. Adding wireless fidelity to embedded systems will open up various feasibilities such as worldwide monitoring and control, reliable data storage etc. This system comprises of wireless sensor nodes and a controller section for surveillance. Remote user alerts, live video streaming and portability are the prime features of the system. WiFi enabled IoT (Internet of Things) module processes the sensor based events and sends the sensor status to controller section. Upon receiving the event notification, the controller enables the camera for capturing the event, alerts the user via email, phone call and SMS and places the live video of event on webpage. The IoT module eliminates the need of a microcontroller and wireless transceiver module in the sensor node, thus it makes the node compact, cost effective and easy to use. The biggest advantage of the system is that the user can seek surveillance from anywhere in the world and can respond according to the situations.
Research on Flexible Joint Friction Identification of Space Lab Manipulator

In order to verify the flexible joint friction model with harmonic drive, the method of on orbit identification and the effect of joint friction on joint control, Chinese Space Laboratory Tiangong - 2 equipped with a Space Manipulator and Dexterous Hand System (SMDHS). Manipulator joint friction identification experiment was carried out on orbit. In this paper, a flexible joint model of manipulator is established. By using the experimental data obtained on orbit, the friction model of viscous friction plus coulomb friction, the cubic polynomial friction model and the Stribeck friction model are compared and analyzed. At the same time, the effect of gravity difference on joint friction is also analyzed. The on orbit experiment prove that the quasi-linear model of viscous friction plus coulomb friction can be used to predict the friction of unrecognized velocity range, the accuracy of joint position control can also tolerate the error of this quasi-linear friction model in engineering applications. The flexible joint model and on orbit identification method established in this paper are helpful to develop the follow up large scale space manipulator and recognize the joint friction characteristics more clearly in the orbital application, so as to further improve the fine operating performance of the manipulator.
An Improved Teaching-Learning-Based Optimization

Teaching-learning-based optimization(TLBO) is a new proposed heuristic algorithm for optimization applications $\mathrm{in}$ recent years. In this paper, an improved TLBO algorithm (ITLBO) is presented. In the teacher phase, the second-teaching strategy and self-exploration study of teacher are introduced to improve the convergence speed. And the improved learner phase can ensure the diversity of the population to avoid the possibility of falling into a local optimum. Meanwhile, second-teaching strategy and the improved learner phase enable the algorithm to use fine local search and improve the precision. To assess the performance of ITLBO algorithm, experiments are implemented on 8 classical benchmark functions. The result show that ITLBO algorithm is an effective approach.
Understanding In-App Ads and Detecting Hidden Attacks through the Mobile App-Web Interface

Mobile users are increasingly becoming targets of malware infections and scams. In order to curb such attacks it is important to know how these attacks originate. We take a previously unexplored step in this direction. Numerous in-app advertisements work at this interface: when the user taps on the advertisement, she is led to a web page which may further redirect until the user reaches the final destination. Even though the original applications may not be malicious, the Web destinations that the user visits could play an important role in propagating attacks. We develop a systematic static analysis methodology to find ad libraries embed in applications and dynamic analysis methodology consisting of three components related to triggering web links, detecting malware and scam campaigns, and determining the provenance of such campaigns reaching the user. Our static analysis system identified 242 different ad libraries and dynamic analysis system was deployed for a two-month period and analyzed over 600,000 applications while triggering a total of about 1.5 million links in applications to the Web. We gain a general understanding of attacks through the app-web interface and make several interesting findings including a rogue antivirus scam, free iPad scams, and advertisements propagating SMS trojans.
Sparse Approximation Methods and Their Parallel Implementation

The article is devoted to a new approach in the analysis of geoacoustic pulses. The authors proposed a mathematical model based on a sparse representation of the signal. An adaptive matching pursuit method has been developed to identify model parameters. A parallel implementation of this algorithm is proposed on the CUDA (Compute Unified Device Architecture) platform. This allows real-time processing and modeling of signals.
Multi-link Articulated Wheeled In-pipe Robot with Underactuated Twisting Joints

This paper presents a multi-link articulated wheeled in-pipe robot that can drive the wheels and roll-joints by only a single actuator mounted in each link. The robot can not only move forward/backward but also move helically in pipes to change its orientation while twisting the body shape. This underactuated motion is generated by a simple miter-geared differential mechanism installed in each joint. Whether the robot moves straight or moves helically depends on the load applied to the wheels and roll-joints. In this study, we assume that this load can be generated by driving the rear wheels and the front wheels of the robot alternatively. To verify the basic performance of our proposed mechanism, experiments in horizontal and vertical straight pipes, as well as a bent pipe, were conducted. We further validated how the different spring stiffnesses influence the underactuation. Thanks to this mechanism, it is not necessary to install an additional actuator for the helical movement (twist of the body shape). Therefore, downsizing and lightweight of the whole robot including cable-savinz can be expected.
Alternative Population Initialization Schemes for Group Search Optimization for Data Clustering

Clustering has become an important mechanism for exploratory data analysis and understanding. Many Evolutionary Algorithms (EAs) have been applied for data clustering, given their flexibility to deal with difficult environments and their capabilities to escape from local minima points from the problem search space. However, given their stochastic nature, EAs may be slower to converge in comparison to traditional clustering models, such as K-Means algorithm, if no historical information is provided. In this work, Hybrid Intelligent Systems (HISs) based on K-Means and Group Search Optimization (GSO) technique are presented, in such a way that K-Means is used as a local search operator in an attempt to improve GSO initial population. Four different population initialization schemes are proposed. Experiments are performed on fifteen real benchmark data sets to evaluate the efficiency of proposed initialization schemes in comparison to standard K-Means and other well-known hybrid K-Means and EAs models from data clustering literature. Experimental results showed the influence of population initialization on the behavior of GSO while dealing with clustering task, and also, the relevance of contextual information to improve initial population for EAs.
Saliency Detection Algorithm Based on Local Linear Constraint

In order to separate a large amount of redundant information in image recognition, an image saliency detection algorithm based on local linear constraints is proposed. Based on the traditional method of reconstructing the error, the image is detected with the local constraint. The traditional method is only constructed based on the background codebook. At the same time, the foreground dictionary is constructed by single-scale segmentation, and the image reconstruction residual is calculated on our method. The error value of the image region is calculated, and the foreground and background dictionary are combined at the same time. Then we adapt the process and normalize the acquired foreground and background saliency maps. Finally we test our method on public databases such as ASD, SED1, SED2, and SOD. The experimental data shows that the proposed algorithm is effective in detecting significant targets of images on the three criteria of P-R curve, F-measure value, and MAE value.
EXPERT EVALUATION OF A NOVEL LIGHT-FIELD VISUALIZATION FORMAT

Light-field visualization is continuously emerging in industrial sectors, and the appearance on the consumer market is approaching. Yet this process is halted, or at least slowed down, by the lack of proper display-independent light-field formats. Such formats are necessary to enable the efficient interchange between light-field content creation and visualization, and thus support potential future use case scenarios of this technology. In this paper, we introduce the results of a perceived quality assessment research, performed on our own novel light-field visualization format. The subjective tests, which compared conventional linear camera array visualization to our format, were completed by experts only, thus quality assessment was an expert evaluation. We aim to use the findings gathered in this research to carry out a large-scale subjective test series in the future, with non-expert observers.
RBM-5 modulates U2AF large subunit-dependent alternative splicing in C. elegans

A key step in pre-mRNA splicing is the recognition of 3’ splicing sites by the U2AF large and small subunits, a process regulated by numerous trans-acting splicing factors. How these trans-acting factors interact with U2AF in vivo is unclear. From a screen for suppressors of the temperature-sensitive (ts) lethality of the C. elegans U2AF large subunit gene uaf-1(n4588) mutants, we identified mutations in the RNA binding motif gene rbm-5, a homolog of the tumor suppressor RBM5. rbm-5 mutations can suppress uaf-1(n4588) ts-lethality by loss of function and neuronal expression of rbm-5 was sufficient to rescue the suppression. Transcriptome analyses indicate that uaf-1(n4588) affected the expression of numerous genes and rbm-5 mutations can partially reverse the abnormal gene expression to levels similar to that of wild type. Though rbm-5 mutations did not obviously affect alternative splicing per se, they can suppress or enhance, in a gene-specific manner, the altered splicing of genes in uaf-1(n4588) mutants. Specifically, the recognition of a weak 3’ splice site was more susceptible to the effect of rbm-5. Our findings provide novel in vivo evidence that RBM-5 can modulate UAF-1-dependent RNA splicing and suggest that RBM5 might interact with U2AF large subunit to affect tumor formation. Author summary RNA splicing is a critical regulatory step for eukaryotic gene expression and has been involved in the pathogenesis of multiple diseases. How RNA splicing factors interact in vivo to affect the splicing and expression of genes is unclear. In studying the temperature-sensitive lethal phenotypes of a mutation affecting the splicing factor U2AF large subunit gene uaf-1 in the nematode Caenorhabditis elegans, we isolated suppressive mutations in the rbm-5 gene, a homolog of the human tumor suppressor gene RBM5. rbm-5 is broadly expressed in neurons to enhance the lethality of the uaf-1 mutants. We found that the uaf-1 mutation causes aberrant expression of genes in numerous biological pathways, a large portion of which can be corrected by rbm-5 mutations. The abnormal splicing of multiple genes caused by the uaf-1 mutation is either corrected or enhanced by rbm-5 mutations in a gene-specific manner. We propose that RBM-5 interacts with UAF-1 to affect RNA splicing and the tumor suppressor function of RBM5 might involve U2AF-dependent RNA splicing.
ERPL: An Enhanced Peer-to-Peer Routing Mechanism for Low-Power and Lossy Networks

The Routing Protocol for low-power and Lossy networks (RPL) is the most popular routing protocol for low-power and lossy networks (LLNs). Recent studies demonstrate that RPL performs poorly in peer-to-peer (P2P) communication. However, P2P communication is of immense importance in many LLNs that require actuation and control operations, such as cyber-physical systems. In order to alleviate the performance problem of RPL, we present a mechanism to enhance P2P route construction and data packet forwarding in RPL’s storing and non-storing mode of operations (MoPs), which we call Enhanced RPL (ERPL). The salient features of ERPL include the following: (i) optimized P2P routing and data forwarding, (ii) no additional control messages, and (iii) ERPL can coexist with standard RPL implementations. We have implemented ERPL in the Contiki operating system and extensively evaluated it against a RPL implementation using Cooja-based emulation and physical testbed based experiments. Our results demonstrate that ERPL outperforms standard RPL in P2P communication and its optimized P2P route construction and data forwarding algorithms also positively impact the protocol’s performance in multipoint to point (MP2P) and point to multipoint (P2MP) communications. Moreover, ERPL is more energy-efficient. Our results also shed light on the performance of MP2P, P2MP, and P2P communications relative to RPL’s destination-oriented directed acyclic graph (DODAG) depth, i.e., a deeper DODAG negatively impacts the performance of MP2P and P2MP communications, however it positively impacts P2P communication, while the reverse holds true for a relatively shallow DODAG.
An Adaptive Feedback Turning SIR Particle Filter and its Application on Active Fault-Tolerant Control of Auxiliary Power Unit

With the development of aero-engine control technology, the complexity of the control system is getting higher and higher, and the requirements of high security and reliability have made active fault-tolerant control more urgent. Because of the bad working environment, sensors are very prone to malfunction. SIR particle filter can be used to implement the estimation of the engine state parameters in the active fault-tolerant control and fault diagnosis of sensors, and an adaptive feedback correction mechanism is provided to improve particle degradation in SIR particle filter, which will improve the estimation precision of the engine condition measured by sensors that may fail. For An APU, exhaust gas temperature is originally adopted for closed-loop control in the starting process, and a novel closed-loop control based on the rotor acceleration is designed to reconstruct the control law when the exhaust gas temperature sensor fails while the exhaust temperature value estimated by the particle filter is used for over-temperature protection control. The simulations show that there is no severe jump in the engine states after exhaust temperature malfunctions and the switching process is stable, and the starting time and exhaust temperature meet the design requirements.
A Novel Electric and Magnetic Gap-Coupled Broadband Patch Antenna With Improved Selectivity and Its Application in MIMO System

A novel broadband patch antenna with electric- and magnetic-coupled elements and its application in multiple-input-multiple-output (MIMO) system is proposed in this communication. Unlike the conventional gap-coupled patch antennas, the electric and magnetic coupling between adjacent patches is considered and studied. Also, for improved understanding of the broadband nature of the proposed configuration, the phase relationships between patch elements are studied. Two- and three-patch prototypes are designed for validation of the concept, and the three-patch antenna is fabricated and measured showing a good agreement between the measured and simulated results. Considerable selectivity is observed in the results of the three-patch antenna because of the radiation nulls introduced by the electric and magnetic coupling. Apart from the broadband operation, the proposed antenna elements show promise for application in high-isolation MIMO systems due to their inherent band-reject characteristic when they are closely placed. For validation in this application, a four-element MIMO antenna is designed, fabricated, and measured. The measured results agree well with the simulated ones.
A Multiobjective Approach Applying in a Brazilian Emergency Medical Service

Facility Location Problem (FLP) is one of the classic topics in Operational Research and proposes to define the best installation points of $p$ facilities to serve $n$ demands. One of its versions, the Maximum Coverage Location Problem (MCLP), aims to cover as highest demand as possible within a preestablished limit (time or distance). In this work, the MCLP was applied to a bi-objective problem that aims to, besides to maximize the number of covered calls, minimize the standard deviation of the mean for a response time. The Non-dominated Sorting Genetic Algorithm (NSGA-II) was used to settle the problem with the real data from the Mobile Medical Emergency Service in the city of Belo Horizonte, Brazil. The compromise solutions were compared with the mono-objective optimal solution for MCLP, found by CPLEX. The optimal solution resulted in the 25% greater coverage than the current one. The results, on average, had more than twenty Pareto-Optimal solutions. In some cases, it was possible to decrease the standard deviation of the optimal covering value, solved from the exact method. The result gives different possibilities, and it might be used to managers to find the best solution according to their goals.
Three-dimensional simulation of the effects of Cu protrusion of Cu-filled TSVs on thermal fatigue behavior of micro-bump joints in 3D integration

A single-layered TSV structure model without micro-bump joints and a three-layered TSV structure model with micro-bump joints were constructed to simulate the changes of Cu plastic deformation regions and Cu protrusion of Cu-filled TSVs under different thermal cycling conditions, by means of finite element (FE) simulation. On the basis of strain energy theory, the effects of Cu protrusion of Cu-filled TSVs on thermal fatigue behavior of micro-bump joints were investigated. The simulation results manifest that under the thermal cycling with peak temperature 125 °C, the plastic deformation regions mainly locate in Cu pads, while spreading to Cu fillers under the thermal cycling with peak temperature 175 °C, and Cu protrusion height increases with increasing peak temperature. Significantly, it is found that the increase in Cu protrusion leads to the decrease in thermal fatigue life of micro-bump joints.
Gradient-based Mechanism For PSO Algorithm: A Comparative Study On Numerical Benchmarks

Due to the growing need for metaheuristics with features that allow their implementation for highly complex and real-time problems, this paper describes a gradient-based mechanism to handle with the constraints and dimensional limits of the search space in an optimization problem. The proposed mechanism aims to control the flight of the particles in the Particle Swarm Optimization (PSO) algorithm, improving its application in complex domains. As a result, the gradient-based PSO presents efficient convergence when compared to other variations of this algorithm. The proposed algorithm is also suitable for real-time problems when the actual optimum is difficult to be reached since a feasible and optimized solution is found in comparison to an initial solution. In this sense, the gradient-based PSO is tested using eight benchmark functions in the continuous domain, namely: Sphere, Rosenbrock, Rastrigin, Griewank, Alpine, Schaffer, Schwefel, and Ackley. The proposed PSO was compared to other three algorithms (with adaptive individual inertia, with constant inertia weight and with linearly decreasing inertia weight). This way, the proposed PSO algorithm was able to reach better-optimized results in seven out of the eight tested benchmark functions at the end of 2000 iterations. By means of the obtained results, it is noteworthy to mention that the proposed constraint-handling mechanism features extremely efficient convergence for the PSO algorithm.
Adaptive Fuzzy Robust Fault-Tolerant Optimal Control for Nonlinear Large-Scale Systems

The problem of adaptive fuzzy decentralized fault-tolerant optimal control is investigated for nonlinear large-scale systems with actuator faults in this paper. Fuzzy logic systems are utilized to approximate the unknown nonlinear functions and learn cost functions. Filtered signals are adopted to circumvent the problems of an algebraic loop on designing the decentralized controllers. Based on the backstepping technique and fault-tolerant control technique, a decentralized feedforward control strategy is designed. Based on the adaptive critic technique, a decentralized feedback optimal control strategy is designed. By combining the feedforward control strategy with the feedback optimal control strategy, a novel adaptive fuzzy decentralized fault-tolerant optimal control scheme is established. The stability of the closed-loop system is proved by using the Lyapunov stability theory. The effectiveness of the proposed decentralized control approach is confirmed via a simulation example.