Miracle-dz/UniFAR-FTUs huggingface dataset:
An Overview of Image Recognition and Retrieval of Clothing Items

Clothing is important to daily life. As on-line fashions retail industry has been growing recognition and retrieval of relevant clothing items have huge potentials, because of the highly increasing earnings of the online clothing sale. This involves acquiring relatable clothing data from a huge number of databases available online. Extracting knowledge and important insights from fashion data still presents challenges due to the essential subjectivity needed and lack of influence to effectively model the domain. There have been many researches about clothing retrieval which are assisted by automated system. In fashion industry, various techniques are suggested and implemented for the classification, recognition and extraction of relevant images from huge databases. The success rates of these techniques are judged on various parameters like their accuracy rate, time taken to generate the outputs, etc. The paper presents a brief analysis of the various retrieval techniques used for clothing retrieval in the fashion industry. Along with this a complete summary on the existing techniques of retrieval based on different scenarios is explained which is expected to be helpful to the researchers who are working in fashion domains for image retrieval.
Modeling the Impact of R Packages Using Dependency and Contributor Networks

This paper aims to identify the factors that affect the impact of Open Source Software (OSS), measured by number of downloads and citations, with a case study of R packages. We generate the dependency and contributor networks of the packages using data collected from Depsy.org, and develop statistical models that use the network characteristics, as well as author and package attributes. We find that there are common network and package attributes that are important in determining both the number of downloads and citations of a package, including degree, closeness and betweenness centralities, as well as package attributes such as number of authors and number of commits.
Feasibility of Endoscopic Thyroidectomy via Axilla and Breast Approaches for Larger Goiters: Widening the Horizons

Scarless (in the neck) endoscopic thyroidectomy (SET) has evolved into a cosmetically preferred alternative to conventional thyroidectomy (ConT). Recently many of our patients are demanding SET; however their goitres are larger than the recommended size of 4–6 cm. Our aim was to compare the outcomes of ET for small (<6 cm) vs large (≥6 cm) goitres and determine its feasibility in such cases. This is a retrospective analysis of prospectively maintained database of patients undergoing ET. Patients were divided into 2 groups: I, small (<6 cm) and II, large goitres (≥6 cm). Their demographic and clinicopathological profiles, operation time, conversion and complication rates, and hospital stay were compared. 99 patients (101 procedures) were included: group I, 60 patients (61 procedures), and group II, 39 patients (40 procedures). Mean tumor size (± SD) was 4.4 ± 0.9 cm and 6.7 ± 1.1 cm in groups I and II, respectively. The groups were comparable with respect to demographic and clinical profile except for mean duration of goiter [30.1 ± 32.6 months (group I) vs 60.5 ± 102.4 months (group I), p = 0.03] and gland weight [21.5 ± 15.3 grams (group I) vs 62.3 ± 51.3 grams (group II), p = 0.001]. Although there was no significant difference between mean operating times, long term perioperative outcomes, and conversion rates, temporary hypocalcaemia and length of stay were longer in group II. One patient had permanent vocal cord palsy (~1%, 1/101); none had permanent hypoparathyroidism. Our results indicate that ET can be offered to a subset of patients with larger goitres desirous of SET with no significant difference in mean operation time, conversions, and long term postoperative complications in experienced hands.
SiNA: A Scalable Iterative Network Aligner

Given two graphs, network alignment asks for a potentially partial mapping between the vertices of the two graphs. This arises in many applications where data from different sources need to be integrated. Recent graph aligners use the global structure of input graphs and additional information given for the edges and vertices. We present SINA, an efficient, shared memory parallel implementation of such an aligner. Our experimental evaluations on a 32-core shared memory machine showed that SINA scales well for aligning large real-world graphs: SINA can achieve up to 28.5x speedup, and can reduce the total execution time of a graph alignment problem with 2M vertices and 100M edges from 4.5 hours to under 10 minutes. To the best of our knowledge, SINA is the first parallel aligner that uses global structure and vertex and edge attributes to handle large graphs.
This Paper is About Lexical Propagation on Twitter. H*ckin Smart. 12/10. Would Accept!

This paper presents an observational study of lexical propagation across online social networking platforms. By focusing on the highly followed @dog_rates Twitter account, we explore how a popular account's unique style of language propagates outside of the account's immediate follower community within Twitter. Initial results show a strong relationship between the prevalence of this account's language-specific features and the account's followership and popularity. Expanding this research across platforms, we demonstrate consistency in these results outside Twitter, as the @dog_rates vernacular shows a similarly strong relationship between use on Reddit and the account's followership over time.
Investigation of Synchronous Generator Underexcited Operation in Isolated Systems

In this paper the actual limits of underexcited operation of an isolated synchronous generator feeding a capacitive network are investigated and compared with the usual settings of the loss-of-field relay. It is shown that in the operating conditions considered the activation of the underexcitation limiter is undesired causing voltage instability. The possible adverse effect of underfrequecny load shedding in such cases is also discussed.
Initial Results of Millimeter Wave Outdoor Propagation Measurements in a Campus Environment

This paper presents results of outdoor measurements for a range of frequencies from 27 GHz to 40 GHz with steps of 1 GHz. Measurements were performed in PUC-RIO campus. Using a signal generator, a CW at 0 dBm was transmitted. Received power was measured with a spectrum analyzer which allows a maximum path loss measurement of 140 dB. Two 20 dBi horn antennas were used, one at transmitter and one at receiver. The transmitter was positioned at Leme Building’s roof with an elevation of 50 meters from ground. 23 receiver points were selected for measurements and received power level at each point and each frequency was obtained. Results indicates that foliage caused weak signals in some points. As expected, lower frequencies have better coverage range.
A Numerical Study of KPZ Equation Based on Changing its Parameters

In this article we investigate the behaviour of the scaling exponentsof KPZ equation through changing three parameters of the equation. Inother words we would like to know how the growth exponent β and theroughness exponent α will change if the surface tension ν , the averagevelocity λ and the noise strength γchange. Using the discrete form of theequation , first we come to the results α = 0.5 and β = 0.33 , then wechange the parameters in the range of 0 to 3 by small amounts , we observethat the exponents change smoothly. In some limit states KPZ equationtransforms to RD and RDSR equations. Fortunately this is obvious inthe figures. As the parameters change and approach the limit states, theKPZ universality class evolves to RD and RDSR regimes.
AirDialogue: An Environment for Goal-Oriented Dialogue Research

Recent progress in dialogue generation has inspired a number of studies on dialogue systems that are capable of accomplishing tasks through natural language interactions. A promising direction among these studies is the use of reinforcement learning techniques, such as self-play, for training dialogue agents. However, current datasets are limited in size, and the environment for training agents and evaluating progress is relatively unsophisticated. We present AirDialogue, a large dataset that contains 301,427 goal-oriented conversations. To collect this dataset, we create a context-generator which provides travel and flight restrictions. We then ask human annotators to play the role of a customer or an agent and interact with the goal of successfully booking a trip given the restrictions. Key to our environment is the ease of evaluating the success of the dialogue, which is achieved by using ground-truth states (e.g., the flight being booked) generated by the restrictions. Any dialogue agent that does not generate the correct states is considered to fail. Our experimental results indicate that state-of-the-art dialogue models can only achieve a score of 0.17 while humans can reach a score of 0.91, which suggests significant opportunities for future improvement.
Energy Efficient Adiabatic FRAM with 0.99 PJ/Bit Write for IoT Applications

Low access energy embedded non-volatile memory is critical for low power sensing systems. This paper proposes a charge-recycling FRAM design that uses resonance between the FRAM array capacitance and an off-chip inductor to perform both write and read functions. In 130 nm, the 256×80 FRAM increases energy efficiency by 3× compared to standard operation, achieves 0.99pJ/bit write energy, 0.4pJ/bit read energy and 102Mbps at 1V.
Harmonic Current Cancellation Method for PMSM Drive System using Resonant Controllers

In a permanent magnet synchronous motor (PMSM) drive system, many nonlinear effects in both the inverter and motor have a negative impact on the motor current and result in current distortion. In this paper, to reduce the current distortion, a resonant controller (RC) is used in parallel with a proportional and integral (PI) regulator in the current controller in the synchronous reference frame. To improve the stability of the RC, a modified transfer function is used. To avoid the interaction between the two types of controllers, a low-pass filter (LPF) is added to suppress the influence of a sudden change of reference. As a result, the harmonic components of the motor current can be reduced greatly, and the dynamic response can be kept the same as that of a PI regulator. Experimental results show that the proposed control method is effective.
Triggering and Control Codesign in Self-Triggered Model Predictive Control of Constrained Systems: With Guaranteed Performance

This note studies the self-triggered MPC problem for constrained discrete-time nonlinear systems. A novel self-triggered MPC algorithm enabling the codesign of triggering and control is proposed, in which the communication cost is explicitly considered in the total cost function, and both the control and triggering intervals can be optimally designed. For constrained nonlinear systems, the theoretical conditions on ensuring feasibility and closed-loop stability are developed, and the achieved control and communication performance is proved to be guaranteed. In particular, the parameter design approaches for satisfying feasibility and stability conditions are further presented in the case of quadratic cost functions. Furthermore, stronger results are provided for linear case. Finally, the effectiveness and advantages are verified via simulation and comparison studies.
A Comparative Analysis of Telecommunication Network Traffic Forecasting: A Three Model Approach

The uplink traffic demand is rising due to the recent high demand of internet traffic, upsurge of social media networking and the increase of the smartphone usage. However, most of the existing works on traffic prediction have concentrated on the downlink with minimal attention on the uplink. Secondly, in the literature ensemble models have been found to generate better prediction values in general than the individual models. This study therefore investigates telecommunication network uplink traffic through the application of three individual forecasting models. In this approach, hourly, daily and weekly uplink traffic of 3G mobile networks as measured from an operator were analysed and forecasted using ARIMA, Elman Neural Network (ENN) and Multilayer Perceptron (MLP) models. With hourly 3G uplink traffic ARIMA (0,1,5), ENN (1–25-1) and MLP (1–25-1) models were selected as the most effective model for prediction, ARIMA (4,1,1), ENN (1–24-1) and MLP (1–24-1) were the best for daily traffic while ARIMA (2, 1,2), ENN (1–10-1) and MLP (1–35-1) are the best models for weekly traffic. The model selection was based on the minimum values of prediction accuracy measures. The comparative results indicated that ARIMA, ENN and MLP models can be applied to predict hourly, daily and weekly 3G uplink traffic effectively.
Weeding out Conventionalized Metaphors: A Corpus of Novel Metaphor Annotations

We encounter metaphors every day, but only a few jump out on us and make us stumble. However, little effort has been devoted to investigating more novel metaphors in comparison to general metaphor detection efforts. We attribute this gap primarily to the lack of larger datasets that distinguish between conventionalized, i.e., very common, and novel metaphors. The goal of this paper is to alleviate this situation by introducing a crowdsourced novel metaphor annotation layer for an existing metaphor corpus. Further, we analyze our corpus and investigate correlations between novelty and features that are typically used in metaphor detection, such as concreteness ratings and more semantic features like the Potential for Metaphoricity. Finally, we present a baseline approach to assess novelty in metaphors based on our annotations.
Substrate Integrated Waveguide with Tapered Electromagnetic Bandgap Structures for Bandpass Filter Design

A planar filter is proposed, designed, and implemented through a structure of substrate integrated waveguide (SIW) and half mode SIW with Tapered Electromagnetic Bandgap structure (TEBG). These bandpass filters are designed using many tapering windows. Through the appropriate design three rows of tapered periodic structures, which are characterized by different central frequency of the passband are used. Numerical simulations show a satisfactory agreement with experiments. The proposed SIW filter is a promising element for the design of high-performance telecommunication systems.
A Compound 10kV DVR System based on Solid State Transformer Structure

A new simplified dynamic voltage restorer (DVR) topology is proposed to compensate for voltage abnormality in this paper. Inspired by the general three-stage solid state transformer (SST) structure, the proposed DVR structure can not only realize voltage compensation for medium voltage grid, but also possess a smaller volume compared to the conventional DVR system by replacing all the line frequency transformers with high frequency transformers. Compensation criteria and control strategies on system level and stage level are given and analyzed. Finally, simulations are carried out and verify the feasibility and validity of the proposed topology and control method.
Analysis of Eddy Current System using Equivalent Multi-Branch Foster Circuit and Edge Element Method

The paper deals with the synthesis of the equivalent model of the systems with an electromagnetic field, using the Foster Circuit (FC). The way of determining the lumped parameters of the FC of the considered system, using a time-harmonic field model, has been discussed. In order to develop the field model, the edge element method (EEM) has been applied. Moreover, the way of determining the lumped parameters of the FC has been illustrated on the example of the studied system, consisting of a solenoid coil and a conductive core. The obtained results of the calculations have been compared with the results, using the transient field model of the phenomena of the considered system.
Current Simulation of a Controlled PMSM Including Skew and Torsional Rotor Vibrations

For the simulation of permanent magnet synchronous machines many models at different levels of complexity are described in literature. In basic cases, the common equations lead to good and quick results, but do omit nonlinear and transient effects such as slotting, saturation, rotor movement and production deviations. In this paper, a transient model based on look-up table data from non-linear finite element analysis (FEA) is applied to a traction drive motor and extended to represent multiple rotor slices. The FEA is done in advance in parallel leading to a fast transient model. The derivation of the machine equations for multiple slices and the model are presented. Simulated currents are validated with measurement. Following the model is used to show the impact of different influence factors like skew, rotor torsion and pulse width modulation (PWM).
An Insight into the Voltage Rising Behavior during Turn-off Process of Series Connected SiC MOSFETs on Circuit Level

Current commercial available SiC MOSFET can hardly meet the requirement of high-voltage electrical application. Connecting SiC MOSFETs in series is a feasible solution. In order to utilize series connected SiC MOSFETs better, a comprehensive understanding of its switching process is of great necessity, especially turn-off process when huge different voltage sharing may occur. This paper focus on two factors, the nonlinearity of SiC MOSFET junction capacitance Cj and the existence of freewheeling diode junction capacitance Cf. A circuit analysis of series connected SiC MOSFETs is proposed. This paper analyzes the turn-off process of series connected SiC MOSFETs qualitatively and mathematically, and the expressions of key parameters, such as dvds/dt during turn-off process, are derived. The characteristics of series connected SiC MOSFETs during turn-off process are revealed. Finally, the accuracy of the analysis is verified by experimental results.
Performance of OLTP via Intelligent Scheduling

Current architectures for main-memory online transaction processing (OLTP) database management systems (DBMS) typically use random scheduling to assign transactions to threads. This approach achieves uniform load across threads but it ignores the likelihood of conflicts between transactions. If the DBMS could estimate the potential for transaction conflict and then intelligently schedule transactions to avoid conflicts, then the system could improve its performance. Such estimation of transaction conflict, however, is non-trivial for several reasons. First, conflicts occur under complex conditions that are far removed in time from the scheduling decision. Second, transactions must be represented in a compact and efficient manner to allow for fast conflict detection. Third, given some evidence of potential conflict, the DBMS must schedule transactions in such a way that minimizes this conflict. In this paper, we systematically explore the design decisions for solving these problems. We then empirically measure the performance impact of different representations on a standard OLTP benchmark.
Query Independent Scholarly Article Ranking

Ranking query independent scholarly articles is a practical and difficult task, due to the heterogeneous, evolving and dynamic nature of entities involved in scholarly articles. To do this, we first propose a scholarly article ranking model by assembling the importance of involved entities (i.e., articles, venues and authors) such that the importance is a combination of prestige and popularity to capture the evolving nature of entities. To compute the prestige of articles and venues, we propose a novel Time-Weighted PageRank that extends traditional PageRank with a time decaying factor. We then develop a batch algorithm for scholarly article ranking, in which we propose a block-wise method for Time-Weighted PageRank in terms of an analysis of the citation characteristics of scholarly articles. We further develop an incremental algorithm for dynamic scholarly article ranking, which partitions graphs into affected and unaffected areas, and employs different updating strategies for nodes in different areas. Using real-life data, we finally conduct an extensive experimental study, and show that our approach is both effective and efficient for ranking scholarly articles.
Comparison of Spectral and Energy Efficiency Metrics Using Measurements in a LTE-A Network

Energy and spectral efficiencies are key metrics to assess the performance of networks and compare different configurations or techniques. There are many ways to define those metrics, and the performance indicators used in their calculation can also be measured in different ways. Using an LTE-A network, we measure different performance indicators and the metrics' outputs are compared. Modifying the transmitted output power, the bandwidth, and the number of base stations, different network configurations are also compared. As expected, the measurements show that increasing the bandwidth increases the throughput more than it increases the energy consumption. Results clearly show that using inappropriate indicators can be misleading. The power indicator should include all energy consumed and the throughput should be dependent on the traffic, taking into account the idle time of the network, if any. There is a need to include more performance indicators into the metrics, especially those related to quality of service.
FE-Based Application for the Evaluation of Core-Losses in Distribution Transformers

This paper describes a finite-element (FE) based application for the numerical evaluation of core-losses in distribution transformer. The specific application is centered around a method that permits the generation of software applications for a variety of user/customer defined problems and makes use of the FE method in order to solve them. A variety of problems are considered such as electromagnetic or thermal, steady state or transient, linear or non-linear, and two-dimensional (2-D) or three-dimensional (3-D). The present manuscript focuses on one such application and more specifically on the problem of core-losses evaluation in oil-immersed, wound core, distribution transformers, both single-phase and three-phase. Finally, the core-losses of a single-phase wound core transformer are computed using the “CORELOSS” application and they are compared with results obtained with a commercial FE package.
Using Linguistic Features to Improve the Generalization Capability of Neural Coreference Resolvers

Coreference resolution is an intermediate step for text understanding. It is used in tasks and domains for which we do not necessarily have coreference annotated corpora. Therefore, generalization is of special importance for coreference resolution. However, while recent coreference resolvers have notable improvements on the CoNLL dataset, they struggle to generalize properly to new domains or datasets. In this paper, we investigate the role of linguistic features in building more generalizable coreference resolvers. We show that generalization improves only slightly by merely using a set of additional linguistic features. However, employing features and subsets of their values that are informative for coreference resolution, considerably improves generalization. Thanks to better generalization, our system achieves state-of-the-art results in out-of-domain evaluations, e.g., on WikiCoref, our system, which is trained on CoNLL, achieves on-par performance with a system designed for this dataset.