Miracle-dz/UniFAR-FTUs huggingface dataset:
Switchable Beam Steering Antenna for Ka- Band Airborne Applications

A switchable beam-steering grid-array antenna at Ka-band is studied for airborne applications. Based on grid array antenna (GAA) configuration, the main beam of the antenna can be steered by switching the excitations at different locations. An antenna design with nine excitations achieve beam steering angle of ±19° at 29 GHz.
Traffic Analysis of IEEE 802.11 on Physical Layer by using Software Defined Radio

The security of wireless networks is a fairly discussed topic. There are many threads capable of attacking any personal, public, or company network. One way of protection is to analyze traffic on the desired wireless network and look for irregularities in the traffic. There are various approaches on how to capture and analyze wireless traffic. In this paper, we present three enablers on capturing wireless traffic, including Off-the-shelf wireless cards and software defined radios. The results provide the capabilities of used devices and possibilities on how to analyze the traffic. We also present our developed wireless traffic visualizer written in python that can be utilized to discover possible attacks on wireless networks visually.
A Tiny Neural Network Model for Estimating Next 24 Hour Temperature Transition

We propose a new tiny neural network model for estimating next 24 hour temperature transition. Conventional neural network models for temperature estimation are mainly focusing on the maximum or minimum temperature with huge nodes and connections, while our model is targeting the full 24 hour temperature with simple size. Our neural network model consists of minimum configuration, i.e. it consists of 24 hour temperature and pressure input nodes and output nodes with fully connections. According to the experiments by applying five major cities in Japan, it is found that MAPEs (Mean Absolute Percentage Errors) of the 24 hour temperature transition by our model are from 1.62% to 3.24% that is comparable accuracy to previous works. As the correlation between the temperature transition and the agriculture productivity or the electric power consumption, this model is useful for the domestic small local industry such as the local agriculture or the power supply company.
Online Health Estimate of Hybrid Energy Storage System Based on Fuzzy Brain Emotional Learning Neural Networks

This paper aims to propose a more efficient estimator and applies it to health estimation for battery and supercapacitor in the hybrid energy storage system (HESS). A novel method for online health estimator based on fuzzy brain emotional learning neural network (FBELNN) is proposed. It’s different from conventional fuzzy brain emotional learning neural network that the fuzzy inference system and the novel reward signal are applied in this paper. The proposed method uses wavelet packet decomposition (WPD) and principal component analysis (PCA) to extract features from impulse respond of load surges. The parameter adaptation laws of the FBELNN are derived and wavelet packet function selection method based on the frequency band energy entropy is presented. The method of WPD-PCA can reduce the workload of feature extraction. Through the neural network estimate the capacity of battery and supercapacitor in real-time, one can better ensure the safety of HESS. The training samples and test samples are collected from the response of voltage signals in HESS simulation platform. Compared to other conventional methods, it’s shown that the anti-noise performance and the accuracy are improved by the proposed method.
Land-cover Classification Based on SAR Data Using Superpixel and Cosine Similarity

Object-Based Image Analysis (OBIA) is one of the cutting edge image processing technologies attracting significant attention in remote sensing industry recent years and Synthetic Aperture Radar (SAR) possess a high potential for classification of earth surface. In this paper, a novel classification method, integrating OBIA and majority voting strategy, is proposed for land-cover classification based on SAR data. The main purposes of OBIA are delineating objects, extracting feature and measuring similarity by using superpixel segmentation technology and cosine similarity algorithm. The color histogram is utilized as feature in this study. Majority voting strategy provides an effective way for class determination. At last, the experimental result is presented and it demonstrates the proposed classification scheme is an appropriate method for land cover classification of SAR data.
GIN: Better going safe with personalized routes

Contextual data characterize distinct regions of the city, allowing them to differentiate them according to security, entertainment, services, among others. Using contextual data to suggest routes helps to understand new aspects of a city that can change users’ perceptions of different routes. The impact of each type of contextual data may vary according to the user’s profile, which is not taken into account in most of the systems proposed by the literature. Besides, it is necessary to consider the behavior of contextual data, which changes according to the type of data. To tackle the problems mentioned above, we propose a route suggestion system with space-time risk, called GIN. The system consists of three modules, namely: identification of contextual windows, context mapping, and route personalization. Moreover, we propose a strategy to decrease the number of route requests to improve system scalability. The results show that the system adapts to sensitive changes in user’s profiles. We obtained promising by using the behavior of contextual data to avoid unnecessary requests. This strategy allowed a reduction of up to 50% of requests made to the system.
Wireless Coherent Full-Duplex Double-Sided Two-Way Ranging (CFDDS-TWR) Approach with Phase Tracking Based Multipath Suppression for Submillimeter Accuracy Displacement Sensing

This paper presents a novel radar technology for precise position measurements (e.g. crane positioning) between two cooperating radar units that is especially suited for use in harsh industrial environments. The concept uses the novel coherent full-duplex double-sided two-way ranging (CFDDS-TWR) FMCW secondary radar concept and combines a beat frequency estimation and a coherent phase tracking even though the two cooperating radar units work incoherently. The novel CFDDS-TWR and phase tracking method allows for an efficient suppression of multipath distortions and enables a displacement measurement with a standard deviation of approx. 13 µm and improves the overall ranging accuracy compared to existing bistatic secondary radar approaches dramatically.
Modeling and Simulation of Sensor Placement Strategies to Detect Malicious UAS Operations

In this paper, we introduce a software framework for modeling and simulation of sensor placement strategies to detect malicious unmanned aerial systems operations. Three basic components are modeled – environment, detection sensors and UAS. The environment is represented in a form of a 3D model defined by a polygonal mesh with material values assigned. Four types of sensors are modeled – camera, acoustic sensor, radar and remote control radio signal detector. A two-phase iterative algorithm for sensor placement and its evaluation via simulation of UAS operations is introduced. We provide a taxonomy of malicious UAS operations based on data from various databases of incidents and attacks. Using this taxonomy, typical representatives of malicious UAS operations are generated for particular critical infrastructures. Features of the proposed framework were verified in scenarios with three typical representatives of critical infrastructures – airport, prison and industrial complex. The results of these experiments are discussed and general recommendations are provided.
Handover-based Load Balancing Algorithm for 5G and Beyond Heterogeneous Networks

In ultra-dense networks, an enormous number of small base stations (BSs) are required to be deployed, and the number of handovers (HOs) in heterogeneous networks (HetNets) increases as a result. Mobility management with the increasing number of HOs is a critical issue that requires uninterrupted connectivity due to user mobility in HetNets. However, some BSs in the network may be more heavily loaded than their neighbors. Load balancing (LB) involves load transfer from an overloaded BS to an under-loaded neighboring BS for the more load-balanced network. HO and LB are two important issues to improve network performance. In this paper, we propose an algorithm that utilizes user speed and received signal reference power to adapt HO margin (HOM) and time to trigger (TTT). Besides, the proposed algorithm balances the loads among neighbor BSs. Additionally, the proposed algorithm aims to reduce ping-pong HOs (HOPP) and HO failure (HOF) ratios. The simulation results show that the rates of HOPP and HOF are significantly reduced by the proposed algorithm, thus improving network performance under various mobile speeds. Moreover, the results show that the proposed algorithm minimizes the standard deviation of BS loads in the network. The proposed algorithm achieves load balancing and reduces overload during user mobility in HetNets. Therefore, there is more than 60% improvement in terms of the HOF, and 63% more balanced network is achieved with the proposed algorithm in the network.
Octave Frequency Range Triple-band Low Phase Noise K/Ka-Band VCO with a New Dual-path Inductor

This paper presents a triple-band voltage controlled-oscillator (VCO) with a new dual-path inductor. The change in inductance value of the proposed dual-path inductor is large while maintaining high Q, enabling to achieve low phase noise oscillation with octave frequency range. The inductances in the two modes of operation can be set independently, depending on the target frequencies. The inductance change is used as a coarse frequency tuning, while fine tuning is realized by a 2-bit capacitor bank with a small size varactor. As a proof of concept, a VCO in class-D biasing with the dual-path inductor has been implemented in a 65 nm CMOS process. The VCO achieves oscillation at three different frequency bands centered at 19, 28, and 36 GHz, while maintaining good phase noise and low power consumption. Measurement results show a peak figure of merit (FoM) of 185.7 dBc/Hz at 18.5 GHz, with 0.0875 mm2 (250 µm × 350 µm) area.
A 171k-LUT Nonvolatile FPGA using Cu Atom-Switch Technology in 28nm CMOS

A nonvolatile FPGA using atom-switch crossbars is implemented in a 28nm CMOS. The depopulated atom-switch crossbar with double-gate layout achieves 75% area saving. The routability degradation due to the depopulation is mitigated by a modified routing architecture of mixed segment lengths with thinning out connection block populations. To our knowledge, the novel FPGA provides the largest logic capacity of 171k lookup-table (LUT) among 3D-FPGAs based on monolithically integrated nonvolatile switch and memory. The operating frequency and dynamic power are significantly improved as compared to conventional atom-switch FPGAs.
Cabling Constraints in PV Array Architecture: Design, Mathematical Model and Cost Analysis

In this article, cabling constraints of different photovoltaic (PV) configurations is addressed in three steps: 1) a cable selection criterion is developed in accordance with metric system defined by American Wire Gauge (AWG); 2) a mathematical model is designed, which estimates the cable length for any array size; and 3) cost functions are devised owing to estimate the cables capital expenditure. The aforementioned steps are developed for Series (S), Parallel (P), Series-Parallel (SP), Total-cross-tied (TCT), Bridge-Link (BL) and Honey-Comb (HC). A comprehensive mathematical model is developed for each of the above mentioned architectures in the context of cabling cost versus energy payback time. This cost analysis provides a clear snapshot to the designers of PV plant about the capital investments of cabling system of specific architecture and its potential energy payback time. At the end, a design example for each configuration is presented against an array size of $10\times 2$ PV panels.
A Geometrically Shaped Hemispherical Cavity Resonator With Extended Spurious-Free Region

This paper presents a geometry-RF -integrated design approach to eliminate spurious resonances in air-filled high-quality-factor cavity resonators. The presented approach is implemented by properly shaping the geometry of the target cavity resonator with a set of tool cavity geometries. A new class of geometrically shaped air-filled hemispherical cavity resonator is proposed and it demonstrates a high unloaded quality factor ($Qu \sim 4680$) and highly reduced number of spurious resonances. The first spurious-mode frequency of the proposed resonator is nearly an octave of the fundamental-mode frequency, and compared to conventional cavity resonators the spurious-free region is significantly extended, without losing the high quality factor attribute of the resonator. The proposed geometrically shaped cavity resonator exhibits great potential in enhancing stopband performance of cavity filters.
SatOpt Partition: Dividing Throughput-Stability Region for IEEE 802.11 DCF Networks

This article investigates the throughput stability of nonsaturated 802.11 networks with distributed coordination function (DCF). We find that this throughput stability exhibits distinct characteristics in two different regions (or scopes) of parameter settings: the maximum stable throughput is higher than the saturation throughput and lasts for a long duration (say, in order of months) in one region, while the former is bounded by the latter in another region. Our core contribution is an innovative approach (called SatOpt partition) that can identify these two regions quickly and accurately, by a comparison between the saturated and optimal attempt rates. Our partition approach is suitable for a wide range of 802.11 DCF contention window settings, while our partition result is unique. Further, for 802.11 DCF standard settings, we predict the maximum stable throughput successfully, and reveal that it is often higher than the saturation throughput. We verify our approach via the widely adopted 802.11 DCF ns2 simulator (mostly with typical 802.11 DCF standard settings). We speculate that this two-region stability property should be inherent for any random-access networks. This suggests that the research on the throughput-stability problem should differentiate regions of parameter settings and failing to do so might produce inconsistent results. This study is expected to take a critical step toward solving the throughput-stability problem.
Investigating Taste-liking with a Humanoid Robot Facilitator

Tasting is an essential activity in our daily lives. Implementing social robots in the food and drink service industry requires the social robots to be able to understand customers’ nonverbal behaviours, including taste-liking. Little is known about whether people alter their behavioural responses related to taste-liking when interacting with a humanoid social robot. We conducted the first beverage tasting study where the facilitator is a human versus a humanoid social robot with priming versus non-priming instruction styles. We found that the facilitator type and facilitation style had no significant influence on cognitive taste-liking. However, in robot facilitator scenarios, people were more willing to follow the instruction and felt more comfortable when facilitated with priming. Our study provides new empirical findings and design implications for using humanoid social robots in the hospitality industry.
Impactos das biotécnicas reprodutivas no controle epigenético de genes imprinted

Assisted reproductive technologies (ARTs) are usually used in both human and veterinary medicine aiming the correction of heritable or acquired infertilities. The somatic cell nuclear transfer technique (SCNT) is of particular importance in veterinary as it enables the generation of genetically identical organisms, allowing the production of homogeneous genetically improved herds, and also serving as a model for reprogramming studies. However, the use of TRAs, SCNT in special, may be responsible for the increase of developmentalrelated abnormalities in the conceptuses. Such phenotypes are probably caused by a disruption in the epigenetic reprogramming due to the manipulation of gametes and embryos during the early development period, and therefore leading to disturbances in the epigenetic regulation of imprinted genes. The present review discusses how the epigenetic marks and expression of imprinted genes may influence the developmental competence of animals generated by SCNT or artificial insemination (AI). The understanding of the epigenetic mechanisms related to embryonic and fetal development, and in special, of those related to the epigenetic dynamics during genomic imprinting may contribute to the generation of efficient ARTs to be used in both regenerative medicine and animal production
Molecular characterization of an Indian muntjac cell line deficient in aspects of DNA repair

An Indian muntjac cell line, SVM, is deficient in an array of DNA repair processes. It exhibits hypersensitivity to UV irradiation and alkylating agents. SVM was transformed with the DNA virus SV40, and some evidence in the literature suggested that this transformation process may of itself have an effect on the repair phenotype of a cell. In order to investigate this possibility for SVM, a spontaneous UV' partial revertant was isolated and aspects of the SV40 virus were characterized in the mutant cell line, SVM(M), and the revertant cell line, SVM(R). Investigation of the integration site of SV40 has revealed a change between SVM(M) and SVM(R). This change is due to an amplification of the control region of SV40 (containing an enhancer and an origin of replication) at the viralcellular DNA junction. This amplification has no effect either qualitatively or quantitatively on the biologically important gene product of SV40, the large T-antigen. This study reveals novel T-antigens in the SVM cell lines apparent at lOOkD and 76kD as compared to the reported wild-type product at 94kD. The nature of the lOOkD 'super T-antigen' was established as due to an internal duplication of SV40 sequences. The cellular sequence flanking the amplification was cloned and characterized. Northern blot analysis, utilizing probes generated from this region revealed that this cellular DNA encoded a 11kb transcript which was aberrantly overexpressed in SVM(M) and SVM(R) compared to CDM, a cell line considered normal with respect to its DNA repair capacity. Furthermore, one probe from this region revealed a 2.8kb transcript, which was also abundant in SVM cell lines compared to CDM. This transcript may also differ quantitatively between SVM(M) and SVM(R). In order to investigate whether aberrant overexpression of the 11 kb transcript was responsible for the DNA repair phenotype of SVM(M), an
Design and Performance Analysis of Robot Shuttle System

Improving storage capacity and operational efficiency for material handling system has attracted much research interest, especially in light of the booming development of E-commerce. This paper presents a robot shuttle system (RSS), featured by picking autonomous guided vehicle (AGV) transporting storage bins in batch to material handlers, which has higher storage capacity and operational efficiency. An open queueing network model is developed to describe the RSS and estimate system performance in terms of throughput capacity and order cycle time. Then, we investigate the influence of the number of storage boxes that the robot can carry on the system performance through numerical experiments, and find an appropriate balance between robot and picker operation proficiency.
Analyses on pistil differentiation process and related biochemical indexes of two cultivars of Prunus mume

In order to understand the pistil differentiation process of Prunus mume Sieb.et Zucc.and its abortion mechanism,the anatomical structure of longitudinal section of flower bud of two cultivars 'Longyan' and 'Daqiandi' of P.mume at different stages was observed by paraffin method.The development state of flower organ,percentage of flower bud,longitudinal and horizontal diameters of flower bud at different stages,and contents of soluble sugar,soluble protein and starch in flower bud of two cultivars were determined and analyzed.The results show that imperfect flower rate of cultivar 'Longyan' is significantly lower than that of cultivar 'Daqiandi' at pistil differentiation,late differentiation and full flowering stages,in which,that of cultivar 'Longyan' is only 5.0% while that of cultivar 'Daqiandi' is up to 76.3% at full flowering stage.The pistil differentiation process of cultivar 'Longyan' goes through four stages including pre-differentiation,early differentiation,differentiation and late differentiation stages,and finally,95.0% flower buds can smoothly form perfect flower at late differentiation stage.That of cultivar 'Daqiandi' goes through six stages including pre-differentiation,early differentiation,differentiation,disintegration,repair after disintegration and late differentiation stages,and only 23.7% flower buds can form perfect flower.At different stages of pistil differentiation,the change of longitudinal and horizontal diameters of flower buds of two cultivars is basically consistent with pistil differentiation process.Contents of soluble sugar and soluble protein in perfect flower of cultivar 'Longyan' are higher than those in perfect and imperfect flowers of cultivar 'Daqiandi',and its starch content is lower than that of the latter two flowers.While contents of soluble sugar and soluble protein in imperfect flowers of cultivar 'Daqiandi' all are the lowest and its starch content is the highest with significant difference to those in perfect flower of two cultivars.Comprehensive analysis results indicate that during the first and second ten days of December,flower bud of cultivar 'Daqiandi' does not continue to elongate,its pistil differentiation stagnates until gradual disintegration,which is the key stage of pistil abortion of cultivar 'Daqiandi'. The factors leading to selective abortion of P.mume pistil may relate to catabolism of macromolecule nutrients in flower bud.
Inferring Non-Stationary Human Preferences for Human-Agent Teams

One main challenge to robot decision making in human-robot teams involves predicting the intents of a human team member through observations of the human’s behavior. Inverse Reinforcement Learning (IRL) is one approach to predicting human intent, however, such approaches typically assume that the human’s intent is stationary. Furthermore, there are few approaches that identify when the human’s intent changes during observations. Modeling human decision making as a Markov decision process, we address these two limitations by maintaining a belief over the reward parameters of the model (representing the human’s preference for tasks or goals), and updating the parameters using IRL estimates from short windows of observations. We posit that a human’s preferences can change with time, due to gradual drift of preference and/or discrete, step-wise changes of intent. Our approach maintains an estimate of the human’s preferences under such conditions, and is able to identify changes of intent based on the divergence between subsequent belief updates. We demonstrate that our approach can effectively track dynamic reward parameters and identify changes of intent in a simulated environment, and that this approach can be leveraged by a robot team member to improve team performance.