Miracle-dz/UniFAR-FTUs huggingface dataset:
A Probabilistic Model for Service Clustering - Jointly Using Service Invocation and Service Characteristics

Service clustering is the foundation of service discovery, recommendation and composition. Most of the existing methods mainly use service attribute information and ignore the semantic-based invocation relationships among service users. In fact, mutual invocation relationships between services occur on operations of the corresponding services, while service attributes are the whole service description. Our main challenge may be to effectively combine these two kinds of data for service clustering. To address this issue, we propose a new probabilistic generative model which contains two closely connected parts, one characterizing operation community memberships by using operation invocation relationships, and the other characterizing service cluster memberships by utilizing service attributes. The correlations between these two parts are characterized by the relationships between operation communities and service clusters. To train this model, we provide a nested expectation-maximization algorithm. Experimental results show its superior performance over the existing methods for service clustering.
Multi-Client Order-Revealing Encryption

Order-revealing encryption is a useful cryptographic primitive that provides range queries on encrypted data since anyone can compare the order of plaintexts by running a public comparison algorithm. Most studies on order-revealing encryption focus only on comparing ciphertexts generated by a single client, and there is no study on comparing ciphertexts generated by multiple clients. In this paper, we propose the concept of multi-client order-revealing encryption that supports comparisons not only on ciphertexts generated by one client but also on ciphertexts generated by multiple clients. We also define a simulation-based security model for the multi-client order-revealing encryption. The security model is defined with respect to the leakage function which quantifies how much information is leaked from the scheme. Next, we present two specific multi-client order-revealing encryption schemes with different leakage functions in bilinear maps and prove their security in the random oracle model. Finally, we give the implementation of the proposed schemes and suggest methods to improve the performance of ciphertext comparisons.
A Ka-Band Substrate Integrated Suspended Line to Rectangular Waveguide Transition

In this letter, a novel Ka-band transition from substrate integrated suspended line (SISL) to rectangular waveguide (RWG) is proposed. In order to broaden the bandwidth, a T-shaped patch is adopted. A back-to-back transition prototype has been designed and fabricated. From 24.6 to 38.5 GHz, i.e., a fractional bandwidth of 44%, the measured return loss is better than 12 dB and the insertion loss is less than 0.34 dB with a minimum of 0.11 dB. Fabricated by using a standard printed circuit board process, the proposed SISL-to-RWG transition has advantages of low manufacturing cost, compact size, lightweight, and self-packaging.
Maturity Model Architect: A Tool for Maturity Assessment Support

A Maturity Model represents a path towards an increasingly organized and systematic way of doing business. It is therefore a widely-used technique valuable to assess certain aspects of organizations, as for example business processes. A maturity assessment can enable stakeholders to clearly identify strengths and improvement points, and prioritize actions in order to reach higher maturity levels. Doing maturity assessments can range from simple self-assessment questionnaires to full-blown assessment methods. This work presents the Maturity Model Architect (MMArch), a maturity model repository and assessment tool, which purpose is to provide support for executing maturity assessment making use of enterprise architecture models, ontologies and description logics. For this purpose, this work details three possible methods for governing the application of these techniques. The main goal of this work is to develop a tool with the purpose of automating and supporting maturity assessment.
DataOps - Towards a Definition

Organizations seek to streamline their data and analytics structures in order to meet increasingly demanding business requirements. This can be difficult due to complex and fast-moving data landscapes. DataOps promises a remedy by combining an integrated and process-oriented perspective on data with automation and methods from agile software engineering, like DevOps, to improve quality, speed, and collaboration and promote a culture of continuous improvement. The goal of this on-going research is to elaborate DataOps as a new discipline. For this, it explores the body of knowledge and presents a working definition of DataOps as well as an initial research framework based on an explorative literature review and eight interviews with industry experts.
Comparison of Protein and Peptide Targeting for the Development of a CD169-Based Vaccination Strategy Against Melanoma

CD169+ macrophages are part of the innate immune system and capture pathogens that enter secondary lymphoid organs such as the spleen and the lymph nodes. Their strategic location in the marginal zone of the spleen and the subcapsular sinus in the lymph node enables them to capture antigens from the blood and the lymph respectively. Interestingly, these specific CD169+ macrophages do not destroy the antigens they obtain, but instead, transfer it to B cells and dendritic cells (DCs) which facilitates the induction of strong adaptive immune responses. This latter characteristic of the CD169+ macrophages can be exploited by specifically targeting tumor antigens to CD169+ macrophages for the induction of specific T cell immunity. In the current study we target protein and peptide antigen as antibody-antigen conjugates to CD169+ macrophages. We monitored the primary, memory, and recall T cell responses and evaluated the anti-tumor immune responses after immunization. In conclusion, both protein and peptide targeting to CD169 resulted in strong primary, memory, and recall T cell responses and protective immunity against melanoma, which indicates that both forms of antigen can be further explored as anti-cancer vaccination strategy.
Distributed Filtering Over Networks Using Greedy Gossip

This paper studies the problem of distributed filtering for state estimation of a dynamic system by using observations from sensors in a network, and proposes a greedy gossip-based distributed filtering (GG-DF) algorithm. The sensor nodes can make estimation and work collaboratively. The information transmission across the network abides by the asynchronous gossip strategy that only two neighboring nodes are selected to communicate and exchange information with each other in each communication round. First, we propose a cost function of the estimation error of the entire network. Then, we derive our algorithm by making a greedy selection to minimize the cost. Finally, we provide performance and convergence analysis of the proposed algorithm, along with simulation results compared with existing methods.
Multiple RGB-D Camera-based User Intent Position and Object Estimation

Human gaze represents the area of interests of the person. By analyzing a time-series of these areas, it is possible to obtain user behavioral pattern that can be used in various fields. Well-known techniques for estimating human gaze are inconvenient because they require a wearable device, or the measurement area is relatively narrow. In this paper, a method to implement gaze estimation system using 3D view tracking with multi RGB-D camera is proposed. Surround 3D cameras are used to extract the region of interest of the user from 3D gaze estimation without wearable device in living space. To implement proposed method, first, 3D space mapping through multiple RGB-D camera calibration is performed. The resulting 3D map is the measurement area, which depends on the number and specifications of the RGB-D cameras used for this purpose. Then, when a person enters the 3D map, the face region is detected using both 2D / 3D data, and 3D view tracking is implemented by detecting the gaze vector using the facial feature point and the head data center point extracted from the 3D map. Finally, when the gaze vector line intersects a specific point within the mapping space, the image coordinates corresponding to that point are extracted to implement user Intent position estimation. Applying object detection and classification algorithm to the extracted image can also estimate the intent object at that time.
Design and Fabrication of a Frequency and Polarization Reconfigurable Microwave Antenna on a Printed Partially Magnetized Ferrite Substrate

Design of a polarization reconfigurable and frequency-tunable patch antenna operating in the partially magnetized state of a ferrite substrate is presented in this communication. A low-cost additive manufacturing process based on a custom iron-oxide magnetic ink (to realize the magnetic substrate) and a silver-organo-complex metallic ink (to realize the antenna) has been used to demonstrate a novel fully printed magnetically controlled antenna. The magnetic substrate is characterized for its magnetostatic and microwave properties. The ink shows a saturation magnetic flux density of 156 mT with a squareness of 0.26. A prototype patch antenna at 6 GHz is implemented on the magnetic substrate using inkjet printing. When excited by an external magnetic field, the antenna shows frequency splitting and polarization reconfigurability. The measured results agree well with the simulation model of the antenna in the partially magnetized state. A maximum tuning range of 16.7% and 5% for the two splitted frequency points is obtained with circular polarizations of the opposite sense. The results show the viability of reconfigurable and tunable radio frequency components on partially magnetized substrates through low-cost additive manufacturing techniques.
Accurate Registration of Multitemporal UAV Images Based on Detection of Major Changes

Accurate registration of multitemporal images captured by UAV usually involves affine transformation and complicated non-rigid transformation, which makes it very difficult to achieve satisfying results. Pixel-wise correspondence is effective for handling images with complicated non-rigidity. However, objects with changes in the scene deform severely because there should be no pixel-wise correspondence but the algorithm erroneously matches the pixels. In this paper, we propose a coarse-to-fine registration method for multitemporal UAV images. First, a projective model is used to eliminate large scale changes as well as perspective distortion. Then the major changes of different temporal UAV images are most detected, which is used to mask the dense matches in changed areas. Finally, the optical flow field method is used to handle complicated non-rigid changes by matching dense SIFT feature. Experimental results on a challenging set of multitemporal UAV images demonstrate the effectiveness of our approach.
Investigating the perception of powertrain shuffle with a longitudinal dynamic driving simulator

Although dynamic driving simulators are widely used in the automotive development process, they are not commonly used for the evaluation of drivetrain drivability. One reason is the limited simulator workspace which requires most maneuvers to be scaled down. However, a tip-in/back-out maneuver, which is often used for drivability assessment, can be implemented in a driving simulator without downscaling. Characteristics of the maneuver are high transient torques which cause comfort reducing oscillations, so called shuffle. In this paper two experiments are reported on the dynamic driving simulator of the Institute for Mechatronic Systems in Mechanical Engineering (IMS) to investigate the absolute perception threshold above which shuffle is recognized. For this purpose, a method is introduced to mathematically approximate recorded tip-in/back-out maneuvers for the implementation on a simulator control. With the method an isolated online manipulation of maneuver parameters, e. g. the shuffle amplitude, is possible. The investigations reveal, that the maximum acceleration due to the tip-in masks the shuffle and hence has a major impact on the perception threshold.
Large-Scale Structure and Individual Fingerprints of Locally Coupled Sleep Oscillations

The temporal coordination of slow oscillations and sleep spindles is believed to underlie processes of sleep-dependent memory consolidation and reorganization. Accumulating evidence of the predominantly local expression of these individual oscillatory rhythms suggests that their interaction may have a similar local component. However, it is unclear whether local coupling holds uniformly across the cortex, and whether and how these dynamics differ between fast and slow spindles, and sleep stages. Moreover, substantial individual variability in the expression of both spindles and slow oscillations raise the possibility that their cross-frequency interactions show similar individual differences. Using two nights of multi-channel electroencephalography recordings from 24 healthy individuals, we characterized the topography of slow oscillation-spindle coupling. We found that locally coupled oscillations occur over widespread cortical areas, but that their dynamics vary with spindle class, sleep stage, and location. Moreover, the phase of the slow oscillation cycle at which spindles were expressed differed markedly across individuals but was stable across nights. However, individual variability of coupling phase was not correlated with overnight memory change. These findings both add an important spatial aspect to our understanding of the temporal coupling of sleep oscillations and demonstrate the heterogeneity of coupling dynamics, which must be taken into account when formulating mechanistic accounts of sleep-related memory processing.
Relationship between anxiety, depressive symptoms and compulsive overeating disorder in patients with cardiovascular diseases

ABSTRACT Objectives: to identify the presence of compulsive overeating disorder in patients with cardiovascular diseases and to verify its relation with sociodemographic, clinical variables and the presence of anxiety and depressive symptoms. Method: cross-sectional, correlational study with a sample of 111 patients with cardiovascular diseases. The presence of anxiety and depressive symptoms was assessed by the Hospital Anxiety and Depression Scale instrument and compulsive overeating disorder was assessed through a likert instrument called the Periodic Eating Disorder Scale (Binge Eating Scale). Results: there was a predominance of patients without compulsive overeating disorder (n=91, 82%), followed by moderated compulsive overeating (n=15, 13.5%) and severe (n=5, 4.5%) associating to high levels of body mass index (p=0.010) and the presence of anxiety (p=0.017). Conclusion: Compulsive overeating disorder was present in 18% of the patients, being associated with body mass index and anxiety, suggesting that health professionals should pay attention to the comprehensive evaluation of patients with cardiovascular diseases. Important results emerged from this study, emphasizing the need to implement programs to improve the patients’ mental and physical health in both primary and specialized care services.
Quadrotor Guidance-Control for flight like nonholonomic vehicles

This paper introduces a velocity based guidance strategy for 3D time-prescribed path following. A second alternative, acceleration based guidance law that incorporates an integral action, is proposed to deal with the more adverse environments. The proposed strategy, which is combined with an efficient nonlinear control strategy for under-actuated systems, is applied to a quadrotor. It ensures the convergence toward the reference trajectory and allows the quadrotor to imitate the behavior of a fixed-wing UAV in the plane (non-holonomic like-navigation). The effectiveness of the proposed Guidance & Control (G&C) loop is shown through some numerical simulations.
Approximate Calculation of HPBW for Uniform Circular Array

The computation of the half power beam width (HPBW) for uniform circular array (UCA) is usually complicated compared with uniform linear array. In this paper, the calculation of HPBW for UCA in the plane the array placed is investigated, and a simple and effective formula is proposed to compute it approximately. Simulation results are provided to verify the validity of the proposed formula. Also, the accuracy of the proposed formula is evaluated in absolute error and error rate by the numerical simulations.
A Real-time Pre-impact Fall Detection and Protection System

As the aging of the population aggravates, the problem of fall has aroused more attention. We have proposed a novel pre-impact fall detection algorithm and protection system. The real-time algorithm used the thresholds of vertical velocity and displacement profile to detect fall events in switching periods of fast motion. It can effectively solve the problem of false alarms of jump and jogging for daily-life applications. A second-order lag filtering algorithm method was utilized to reduce the drift of the vertical velocity with good performance. In addition, the vertical displacement profile was calculated by using the vertical velocity estimation. The algorithm got 93.6% sensitivity and 95.6% specificity, which was higher than the algorithm without displacement with 75.6% specificity. The results demonstrated the effectiveness of the proposed detection method, which were evaluated by subjects wearing fall detection and airbag system.
High-Efficiency Bridgeless Single-Power-Conversion Battery Charger for Light Electric Vehicles

Charging batteries of light electric vehicles require chargers with high efficiency and a high power factor. To meet this need, this paper presents a bridgeless single-power-conversion battery charger composed of an isolated step-up ac–dc converter with a series-resonance circuit. The bridgeless configuration reduces the conduction losses associated with the input diode rectifier, and the series-resonance circuit reduces the reverse-recovery losses of the output diodes by providing zero-current switching. In addition, direct and series-resonance current injections enable bidirectional core excitation by the transformer, thereby allowing high-power capability. The control algorithm derived from feedback linearization is also developed, which allows the proposed charger to correct the power factor and regulate the output power in a single-stage power conversion. This simple circuit structure leads to high efficiency and a high power factor. The theoretical concepts of the proposed charger are verified experimentally using a 1.7-kW prototype.
Design and Analysis of Waveguide-Coupled Photonic THz Transmitters With an Extremely Wide Fractional Bandwidth

The design and analysis of novel waveguide-coupled photonic transmitters, which can have an extremely wide <inline-formula><tex-math notation="LaTeX">$ \pm $</tex-math></inline-formula>3-dB fractional optical-to-electrical (O–E) bandwidth at near the terahertz (THz) operating frequency regime (100%; 0.1–0.3 THz), are presented. This novel module is composed of a customized WR-10-based wideband antenna and an ultrafast/high-power photodiode with a 0.33-THz 3-dB O–E bandwidth, which is flip-chip bonded onto an aluminum nitride substrate, integrated with an impedance matching circuit as well as a bow-tie radiator to serve as the antenna feed. The WR-10-based dual-ridge horn structure is adopted to realize the extremely wideband antenna because the dominant TEM mode supported by the dual ridges has no cutoff frequency. The proposed antenna exhibits more than 18 dB gain across the whole operating bandwidth (0.1–0.3 THz). With the transmitter operating at an output photocurrent of 10 mA and employing the same dual ridge-horn antenna at the receiving end, we can detect a reasonable power (31.6 <italic> μ</italic>W) at 0.24 THz through 1 cm wireless transmission.
PAIRS: Privacy-Aware Identification and Recommendation of Spatio-Friends

Due to the prevalence of location-based services, it has now become possible to infer social connections between people by observing their spatial behaviors over time. Such spatial behaviors, if shared, can be utilized to identify and recommend friends for web-based social service users. However, such approaches cannot be implemented without solving two key challenges: (a) guaranteeing an individual's privacy in the shared spatiotemporal data, and (b) addressing the inherent sparseness of shared spatiotemporal data. In this paper, we propose a Privacy-Aware Identification and Recommendation of Spatio-Friends (PAIRS) approach, that can infer and recommend potential social connections by analyzing spatiotemporal information of social media users using robust privacy guarantee mechanisms. To achieve this, PAIRS constructs co-occurrence profiles using a cluster-based anchor representation to alleviate the sparseness of shared spatiotemporal information. It utilizes the diversity, time and weighted frequency-based inference to efficiently infer the strength of potential social connections from co-occurrence profile by reducing the negative impact of coincidences and thereby enhances accuracy. To tackle the privacy concerns, PAIRS sanitizes the cluster-based anchors, the location entropy values as well as the co-occurrence profile under differential privacy, including optimization mechanisms to handle trade-offs in utility and privacy. Extensive experiments are conducted with real-world datasets including both individuals' spatiotemporal data and their actual social connections. We confirm that our approach can achieve two often contradictory goals: a provable robust privacy protection for sharing data and an efficient social strength inference and spatio-friend identification mechanism. Specifically, PAIRS remains approximately 70% accuracy (precision) and 80% efficiency (recommendation potential) after perturbation.
Bobrovsky-Zakai Bound for Filtering, Prediction and Smoothing of Nonlinear Dynamic Systems

In this paper, recursive Bobrovsky-Zakai bounds for filtering, prediction and smoothing of nonlinear dynamic systems are presented. The similarities and differences to an existing Bobrovsky-Zakai bound in the literature for the filtering case are highlighted. The tightness of the derived bounds are illustrated on a simple example where a linear system with non-Gaussian measurement likelihood is considered. The proposed bounds are also compared with the performance of some well-known filters/predictors/smoothers and other Bayesian bounds.
Environmental Assessment of Anthropogenic Effects on Recreation Zones: Osetr River in the Moscow Region

The article sums up environmental assessment of the Osetr River basin, the impact of anthropogenic factors on recreational areas in Zaraisk and Lukhovitsky districts in Moscow region. At the heart of the writing of the task tasks were based on data obtained during the summer period between June 22 to July 23, 2015 and from June 15 to June 25, 2016 in alignments no. 1, 2 of the settlement of Spas-Doschatyi in Zaraiskiy district and no. 3, 4 on the basis of Saturn in the Lukhovitsky district, on scientific concepts, the method for assessing the ecological state of recreational zones, quality standards for water bodies of domestic and drinking water and cultural and domestic water use, statistical data, cartographic materials, hydro-hydrochemical survey data and climate which includes information obtained from the results of field work for 2015-2016, as well as in the MOSEKOMONITORING and the Federal Agency for Water Resources.