Miracle-dz/UniFAR-FTUs huggingface dataset:
A fast hierarchical clustering approach based on partition and merging scheme

Hierarchical clustering is one major kind of clustering approaches. As far as we know, given n data points, the time complexity of most existing hierarchical clustering approaches is O(n). Although some state-of-the-art fast hierarchical clustering approaches have lower time complexity, their clustering accuracy is sacrificed and sensitive to some certain data distribution types. This paper therefore presents a partition-and-merging scheme for fast hierarchical clustering, which divides data objects into proper groups and merges them within their groups to save computation cost. Since both spatial distance and density difference, which contain local and global distribution information of data, are considered in the merging stage, the proposed approach has outstanding performance in terms of effectiveness, efficiency and robustness. Experimental results show the promising results in comparison with the existing counterparts.
Malayalam grammar learning software based on finite state transducer

India is a country with a diversity of languages. Malayalam belongs to the Dravidian family of languages with literary tradition. In 2013, it is designated as one of the classical languages in India and is the official language of Kerala, the south-western state in India. In Kerala, people give a high priority for education. In most of the schools run by private trusts and individuals in Kerala, English is the medium of instruction. But the State Government schools use both English and Malayalam as language of instruction. The structure of spoken English has influenced the structure of spoken Malayalam in certain aspects. Due to this influence, Malayalam has assumed certain new dimensions on account of the impact of English grammar. It is also seen that Malayalam grammar is taught using the linguistic terms in English. For example, the words noun and verb are more commonly used instead of the corresponding Malayalam words and tafto even while teaching Malayalam grammar. Most students do not like grammar. This has resulted in the elimination of grammar from today's classrooms. In this paper, we have presented the details of how Finite State Transducer is utilized to implement a Malayalam morphological generator. The software helps the students to discover the rules of Malayalam grammar. The children of keralites, who are settled abroad can learn the rules of their mother tongue and know how native speakers speak in real Malayalam conversation. They can study structures of word, like morphemes. Morph generator provides different types of inflections to the root word according to the provided morpholexical information. In the present version of the software, two modules are included. In learning module, the user can study the grammar. Exercise module, conducts test to know the level of knowledge the user learned.
Low power, low phase noise current reuse 2.45 GHz LC oscillator with MOS resistor

This work presents a current reused low power 2.45 GHz LC oscillator. The paper provides a cross coupled LC oscillator used with NMOS resistor and the current reuse topology where two series transistors as staked switches and MOS resistor for symmetric output are used. This oscillator is designed with 0.5-μm CMOS process in ADS. Two topologies of LC oscillator are designed. The topology 2/1 draws only 117.9/68 μA current at 2/2.5 V DC supply, resulting in the oscillator consuming a very low power (0.2358 /0.17mW). The phase noise of proposed oscillator is −139 dBc/Hz at an offset 1 MHz. In order to eliminate mismatch in the output, an NMOS is used in triode region with 0.8235V gate voltage as a voltage drop provider.
Infall and outflow motions towards a sample of massive star-forming regions from the RMS survey

We present the results of an outflow and infall survey towards a distance-limited sample of 31 massive st ar-forming regions drawn from the Red MSX source (RMS) survey. The presence of young, active outflows is identified from SiO (8-7) emission and the infall dynamics are explored using HCO + /H 13 CO + (4-3) emission. We investigate if the infall and outflow parameters vary with source properties, exploring whether regions hosting potentially young active outflows show similarities or differences with regions harbouring more evolved, possibly momentum-driven, 'fossil' outflows. SiO emission is detected towards approximately 46 per cent of the sources. When considering sources with and without an SiO detection (i.e. potentially active and fossil outflows, respectively), only the 12 CO outflow velocity shows a significant difference between samples, indicating SiO is more prevalent towards sources with higher outflow velocities. Furthermore, we find the SiO luminosity increases as a function of the Herschel 70 μm to WISE 22 μm flux ratio, suggesting the production of SiO is prevalent in younger, more embedded regions. Similarly, we find tentative evidence that sources with an SiO detection have a smaller bolometric luminosity-to-mass ratio, indicating SiO (8-7) emission is associated with potentially younger regions. We do not find a prevalence towards sources displaying signatures of infall in our sample. However, the higher energy HCO + transitions may not be the best suited tracer of infall at this spatial resolution in these regions. © 2018 The Author(s). Published by Oxford University Press on behalf of the Royal Astronomical Society.
Analysis of time-frequency-space dispersion and nonstationarity in narrow-strip-shaped networks

This paper presents the analysis of time-frequency-space dispersion and nonstationarity in high-speed railway (HSR) communication networks with the narrow-strip-shaped coverage mode. A long-term evolution (LTE)-based channel sounding system is used to measure the propagation characteristics in a dedicated HSR LTE network with the echo channel effect (ECE) caused by the same signaling from different remote radio units (RRUs). The measurement data in a rural scenario are partitioned into the cases without and with the ECE. Based on the processed data, root mean square (RMS) delay spread, Doppler spread, and angular spread are analyzed and modeled. In addition, the nonstationarity of the HSR channel is studied focusing on the stationarity interval. The presented results will be useful in non-stationary time-frequency-space channel modeling for narrow-strip-shaped HSR communication networks.
Efficient virtual evolved packet core deployment across multiple cloud domains

Many ongoing research activities relevant to 5G mobile systems concern the virtualization of the Evolved Packet Core (EPC) elements aiming for system scalability, elasticity, flexibility, and cost-efficiency. Virtual Evolved Packet Core (vEPC) will principally rely on some key technologies, such as Network Function Virtualization (NFV), Software Defined Networking (SDN) and Cloud Computing, for enabling the concept of Mobile Carrier Cloud. The key idea beneath this concept, known also as EPC as a Service (EPCaaS), consists in deploying virtual instances (i.e., Virtual Machines or Containers) of key core network functions (i.e., Virtual Network Functions — VNF), such as the Mobility Management Entity (MME), Serving GateWay (SGW), and Packet Data network gateWay (PGW) over a federated cloud. In this vein, an efficient VNF placement algorithm is highly needed to sustain the Quality of Service (QoS) while reducing the deployment cost. Our contribution, in this paper, is to devise an algorithm that derives the optimal number and locations of vEPC's virtual instances over the federated cloud. The proposed algorithm is based on coalition formation game, wherein the aim is to build optimal coalitions of Cloud Networks (CNs) to host the virtual instances of the vEPC elements. The obtained results clearly indicate the advantages of the proposed algorithm in ensuring QoS given a fixed cost for vEPC deployment, while maximizing the profits of cloud operators.
MMC based multi-terminal HVDC subsea power transmission system with the integration of offshore renewable energy

Typical 2-level and 3-level converters are still widely implemented in offshore renewable and deep-water oil and gas applications due to their simplicity and maturity in these fields. However, it is difficult for these converters to operate in higher dc bus voltage due to the switching transients, large voltage stress on each switches and large losses. Therefore, Modular Multilevel Converter (MMC) has been gaining popularity over these converters in the field of high voltage and high power applications such as HVDC. In this paper, control of MMC based multiterminal HVDC transmission system for offshore wind energy integration and subsea oil and gas application are presented. Different strategies to regulate the DC link voltage, active and reactive power flow and AC grid voltage of the passive subsea grid in a 3-terminal offshore HVDC grid have been presented.
Dividing the threshold: Multi-probe localized EM analysis on threshold implementations

Cryptographic implementations typically need to be secured to retain their secrets in the presence of attacks. As a countermeasure to prevent side-channel attacks, threshold implementations are a commonly encountered concept. They resemble a multi-party computation, where the value is split in independent shares and processed separately. In this work, we challenge the underlying security assumption that observing these individually processed values is difficult. We observe leakage by spatially separating the shares on an FPGA using multiple electro-magnetic (EM) probes simultaneously for localized EM analysis. We experimentally verify that the security gain is 238 times less with this method when compared to the power side-channel. In total, we only need 4,300 traces to break a second-order secure implementation. Moreover, such a reduction in protection level is only possible when using multiple probes and applying our attack strategy which is based on state-of-the-art template attacks. This attack can easily be carried out by any attacker at the expense of buying more probes which emphasizes the danger of such attacks.
Resilience-oriented microgrids: A comprehensive literature review

The salient features of microgrid (MG), such as operational flexibility, self-adequacy, and coordinated energy management, make it a promising candidate for facilitating the restoration of distribution power system after “low-frequency, high impact” events. In the literature, various methods have been proposed for improving the resilience of the system using MG or networked-MGs (NMGs). This paper conducts a comprehensive review of the state-of-the-art methods reported in the literature, aiming to provide more valuable insights into this area and help the system operator/planner to design more effective restoration strategies based on microgrids. At first, the principle of MG for resilience is described, and the formulation of the resilience problem is revisited. Subsequently, restoration strategies are classified into several categories and reviewed respectively. Finally, conclusion and outlook for future research are discussed.
Stochastic stability and performance analysis for Markovian jump systems interconnected over an undirected graph

This paper considers the problems of stochastic stability and performance analysis for Markovian jump systems interconnected over an undirected graph is considered. A sufficient condition for the well-posedness, stochastic stability and contractive performance of such systems is presented in terms of linear matrix inequalities (LMIs), which gives a theoretical foundation for the further research. A numerical simulation is given to show the validity of the results.
Photographic image synthesis with improved U-net

Photographic image synthesis is the process of creating images that are accurate representations of a real scene with some form of image description and is a new application field o f deep l earning technology. T he U-net is a frequently used convolutional network architecture in deep learning technology and is mainly used for image segmentation. Currently, the U-net has been used for photographic image synthesis. However, the attenuation of image description information, the low memory ca-pacity of the network and the checkerboard artifacts in the output images cause the low quality of the images synthesized by the U-net. In order to solve the above problems, this paper presents an improved U-net (IUN) for photographic image synthesis. In IUN, the image description map is resized to the multiple resolutions and the resized images are merged into the different layers of IUN for enhancing the image description information. The resize-convolution layers in IUN replaces the deconvolution layers in the U-net to reduce the checkerboard artifacts. The proposed learnable residual blocks increase the memory capacity of the network. IUN can be easy trained end-to-end with the image description map and the corresponding photographic image. In experiments on datasets, two types of image description information, semantic and sketch, are used to synthesize the photographic images. Compared to the optimization-based networks, cascaded refinement networks (CRNs) and other methods, IUN gives more realistic results. Additionally, our network achieves a balance between memory capacity and time cost.
Localization of access points based on the Rayleigh lognormal model

Acquiring the knowledge of WiFi access point (AP) locations not only plays a vital role in various WiFi related applications, such WiFi-based indoor localization, the deployment of new WiFi APs, and so on, but also contributes to the emergence of novel applications. Most existing studies assume the well-known lognormal shadowing model, which only reflects large-scale fading in WiFi signal propagations but ignores small-scale fading induced by pervasive multipath effects. In this paper, we tackle the problem of AP localization based on the Rayleigh lognormal model which characterizes the influence of both large-scale and small-scale fading. Provided that a participant holding a smartphone is walking along a path and the smartphone automatically and continuously collects received signal strength (RSS) measurements from a target AP at known positions, particle filtering is applied to sequentially narrow the scope of possible locations of as well as the propagation parameters of the wireless signals emitted by the target AP, and the weighted mean of all candidate locations is returned as its final location estimate. Extensive experiments are carried out in typical indoor and outdoor scenarios, and reveal that the proposed method outperforms the solutions based on the lognormal model by 14.13%–70.38%.
Performance comparison of integrated magnetics used in LLC resonant DC-DC converter for low voltage energy storage system

In this paper, the performance of a novel structure of a 1.08 kW planar Linear Level Control (LLC) transformer with magnetic integration is evaluated and compared with the conventional top-up structure transformer. The developed planar LLC transformer has a number of advantages. The most significant advantage is that it adjusts the resonant inductance more effectively by changing the air-gap between the magnetic insertion and the transformer core. Compared to the conventional integrated transformers, the developed LLC transformer cannot only adjust the resonant inductance easily, but also achieves a 30% reduction in volume. The performance evaluation was conducted with the assisted modelling technique and verified with the impedance measurement result. Furthermore, three transformer prototypes were built and tested. An experimental efficiency comparison result is shown and analyzed.
Giardia Infection of the Small Intestine Induces Chronic Colitis in Genetically Susceptible Hosts

The lumen-dwelling protozoan Giardia is an important parasitic cause of diarrheal disease worldwide. Infection can persist over extended periods with minimal intestinal inflammation, suggesting that Giardia may attenuate host responses to ensure its survival, although clearance eventually occurs in most cases. IL-10 is an anti-inflammatory regulator critical for intestinal homeostasis and controlling host responses to bacterial exposure, yet its potential role in coordinating antiprotozoal host defense in the intestine is not known. In this study, we found that murine infection with the natural enteric pathogen Giardia muris induced a transient IL-10 response after 2–4 wk at the primary site of infection in the upper small intestine, but parasite colonization and eradication were not affected by the absence of the cytokine in gene-targeted mice. However, IL-10 was critical for controlling infection-associated immunological sequelae in the colon because severe and persistent diarrhea and colitis were observed in IL-10–deficient mice within 1–2 wk postinfection but not in uninfected littermate controls. Inflammation was characterized by epithelial hyperplasia, neutrophil and macrophage expansion, and Th1 induction and could be prevented by blockade of IL-12/IL-23 p40 but not depletion of CD11c+ dendritic cells. Furthermore, the intestinal microbiota underwent characteristic shifts in composition and was required for disease because antibiotics and loss of TLR signaling in MyD88-deficient mice protected against colitis. Together, our data suggest that transient infection by a luminal and seemingly noninflammatory pathogen can trigger sustained colitis in genetically susceptible hosts, which has broader implications for understanding postinfectious syndromes and other chronic intestinal inflammatory conditions.
Optimal power flow for IEEE 30 and 118-bus systems using Monarch Butterfly optimization

A new metaheuristic algorithm "Monarch Butterfly Optimization (MBO)" is used in this paper to extricate the problem of Optimal Power Flow (OPF) for standard IEEE 30 and 118-bus test power systems. Three functions (Fuel expenses, Total voltage deviation, and Real power loss in transmission) are enhanced by applying the suggested technique and the outcomes attained are juxtaposed with those of other techniques stated in the literature. This comparison demonstrates that Monarch Butterfly Algorithm imparts superior results than other algorithms.
A fully passive RFID temperature sensor SoC with an accuracy of ±0.4°C (3σ) from 0°C to 125°C

This paper presents a fully passive 13.56 MHz RFID temperature sensor system-on-chip. Its power management unit (PMU) operates over a large temperature range using a zero temperature coefficient (TC) bias source. On-chip temperature sensing is accomplished with low voltage, low power CMOS circuitry and time-domain signal processing. Two operating modes have been defined to study supply noise sensitivity: command mode and listening mode, which represent sensor operation during RFID command transfer and listening, respectively. Besides a standard readout command, a customized serial readout command is utilized to distinguish the data from both modes. In command mode, the sensor suffers from interference from the RFID command packet and outputs interference as well, while the sensor outputs no interference in listening mode. Measurements show that sensor resolution in listening mode is improved by a factor of approximately 16 compared to command mode. The chip was fabricated in a standard 0.35 ¡im CMOS technology and chip-on-board mounted to a tuned RFID transponder coil on an aluminum core FR4 PCB substrate. Realtime wireless temperature sensing has been demonstrated with a commercial HF RFID reader. With a two-point calibration, the SoC achieves a 3σ sensing accuracy of ±0.4 °C from 0 °C to 125 °C.
A 1.2 Gbps failsafe low jitter LVDS transmitter-receiver applied in CMOS image sensor

A 1.2 Gbps low-voltage differential signaling (LVDS) transmitter with only 40 ps rms jitter peak-to-peak (2UI, with a capacitive load of 12 pF) and a 1.2 Gbps receiver with a pre-amplifier of high speed and wide input range were designed. The design of the transmitter-receiver are both compliant with TIA-644-A and IEEE 1596.3 standard. This chip was fabricated in a 3.3-V 0.18-μm CMOS process. The total area of single transmitter-receiver is 0.464 mm2 and the transmitter and receiver exhibit a power consumption of 12.7 mW and 2.4 mW respectively. A receiver for receiving data clock and 14 parallel transmitters for transmitting data were fully integrated into a high speed CMOS image sensor (CIS) chip.
Chinese metaphor sentiment analysis based on attention-based LSTM

The metaphor is a kind of frequently used figurative language. Metaphor computing is helpful in many natural language processing tasks, such as opinion mining, discourse understanding, and dialogue system. This article presents a Chinese metaphor sentiment analysis approach based on an attention-based Long Short-Term Memory (LSTM) network. Our hypothesis is that the target and the context are important in metaphor sentiment analysis, and their interaction provides reliable sentiment-related classification features. The experimental results agree with our hypothesis and justify the effectiveness of the model.
A unity power factor converter with isolation for electric vehicle battery charger

This paper deals with a unity power factor (UPF) Cuk converter EV (Electric Vehicle) battery charger having a high frequency transformer isolation instead of only a single phase front end converter used in vehicle's conventional battery chargers. The operation of the proposed converter is defined in various modes of the converter components i.e. DCM (Discontinuous Conduction Mode) or CCM (Continuous Conduction Mode) along with the optimum design equations. In this way, this isolated PFC converter makes the input current sinusoidal in shape and improves input power factor to unity. Simulation results for the proposed converter are shown for charging a lead acid EV battery in constant current constant voltage (CC-CV) mode. The rated full load and varying input supply conditions have been considered to show the improved power quality indices as compared to conventional battery chargers. These indices follow the international IEC 61000-3-2 standard to give harmonic free input parameters for the proposed circuit.
Data-Driven Charging Strategy of PEVs Under Transformer Aging Risk

Big data analytics and plug-in electric vehicle (PEV) are the important elements of smart grids in the future. This paper introduces a data-driven charging strategy for PEV-based taxis, where driving behaviors of taxis and load profiles of buildings are characterized by data analysis to make the risk-averse decision on PEV charging. First, the framework of data driven risk-averse PEV charging is introduced, where a stochastic game model is proposed. Specifically, the pricing mechanism-based charging cost and the conditional value-at-risk (CVaR) measurement are used to determine the objective function for each PEV. Then, the existence of a generalized Nash equilibrium and its seeking algorithm is studied. The convergence analysis of the algorithm is also given. Second, the big data analysis of the statistical information about PEV-based taxis and the load profile of buildings are presented by applying various data process techniques. Finally, the performance of the method is numerically illustrated by the case study via real global positioning system information of 490 PEV-based taxis and the smart meter data from local commercial buildings.