Miracle-dz/UniFAR-FTUs huggingface dataset:
A New Approach of Template Matching and Localization Based on the Guidance of Feature Points*

Template matching is the most basic and commonly used matching method in image processing. On account of different selections in matching, there are mainly two approaches: gray information matching and feature matching. The former method is accurate, but might be easily influenced by interferences such as illumination and other noises. In addition, the method is limited by its high time complexity. For the latter method, the anti-interference ability is relatively strong due to the extraction of image feature. However, most of feature extraction are very complex, which result in long computation time. In this paper, a novel approach of template matching and object localization based on the feature points in the edges of image is proposed. Firstly, the intersection points of principal axis and vice axis with the image edges are selected as the feature points; Secondly, the transformation parameters between the points set of template and object image edges are computed by using the feature points gotten in last step; Then, the points set of template contour is transformed and the Hausdorff distance of the transformed template and target points set are calculated as the similarity measure; Lastly, the minimum Hausdorff distance is searched by changing the transformation parameters in their respective neighborhoods, and the parameters corresponding are required. The experiment results indicate that this approach has a good performance both on not processing speed and accuracy.
Antiglycation and antioxidant activity of a rare medicinal orchid Dendrobium aqueum Lindl

Oxidative stress and glycation plays an important role in manifesting of diabetes and vascular complications. Agents with antiglycation and antioxidant properties may retard these pathological alterations. Aqueous extract of aseptically regenerated Dendrobium aqueum was used for in vitro estimation of antioxidant and antiglycation potential. Antioxidant activity was evaluated as DPPH radical scavenging activity, whereas the protein glycation inhibitory potential was evaluated using invitro albumin/fructose glycation model. Glycation inhibition was estimated by different biochemical parameters i.e. fructosamine, protein carbonyl group, thiol content and Congo red binding; indicators of various glycation modification of albumin. D. aqueum extract showed a dose dependent DPPH free-radical scavenging potential and exhibited a significant antiglycation potential. Our finding might open a new arena of research in traditional herbal medicine with D. aqueum orchid which could be utilized in diabetes due to its antiglycation and antioxidant properties
Results of the WMT19 Metrics Shared Task: Segment-Level and Strong MT Systems Pose Big Challenges

This paper presents the results of the WMT19 Metrics Shared Task. Participants were asked to score the outputs of the translations systems competing in the WMT19 News Translation Task with automatic metrics. 13 research groups submitted 24 metrics, 10 of which are reference-less “metrics” and constitute submissions to the joint task with WMT19 Quality Estimation Task, “QE as a Metric”. In addition, we computed 11 baseline metrics, with 8 commonly applied baselines (BLEU, SentBLEU, NIST, WER, PER, TER, CDER, and chrF) and 3 reimplementations (chrF+, sacreBLEU-BLEU, and sacreBLEU-chrF). Metrics were evaluated on the system level, how well a given metric correlates with the WMT19 official manual ranking, and segment level, how well the metric correlates with human judgements of segment quality. This year, we use direct assessment (DA) as our only form of manual evaluation.
A Hybrid Robust-Stochastic Approach for the Day-Ahead Scheduling of an EV Aggregator

Electric Vehicles (EVs) are emerging among the Distributed Energy Resources (DERs) as a promising flexibility source. The small-scale of DERs still constitutes a barrier to their direct participation in electricity markets. Aggregators can exploit EV smart charging to lower the energy procurement cost in the day-ahead (DA) scheduling phase. This cost minimization should consider the uncertainty stemming from the availability of EVs, the DA and the imbalance market prices. To catch all these uncertainties, a novel approach combining robust optimization and stochastic programming is proposed to define the DA charging schedule for an EV fleet, considering the DA market prices and the possible imbalance realizations in real-time. This method is compared with a two-stage stochastic (TSS) programming approach and with the EV uncontrolled charging. Two weeks of data from the DA spot market in the Netherlands have been used for comparing the methods with different fleet sizes: 100, 200 and 400 EVs. The results show that the hybrid robust-stochastic method, while keeping approximately the same average DA energy cost, can estimate better than the TSS method the actual daily energy cost with reduced computational time.
Implementation of Vocabulary Based Summarization of Graph (VoG) on the Web Graph

Increasing data of the web graph make it difficult to identify the data structure and get the information from that large graph. To identify the structure and get the information, some method needed to summarize the large graph into smaller subgraphs, so data structure identification can be conducted on the subgraph. This will make structure identification easier. Vocabulary based Summarization of Graph (VoG) is a method that can be used to summarize the large graph and identify the subgraph structure. In the process of structure identification, a maximum number of node in $GCC\ (k)$ affects the generated subgraph. More and more $k$ generates less of subgraph with clique and star structures but generates more subgraphs with chain structures. The $k$ also affects the execution time of VoG. More and more $k$ make the execution time of VoG faster. From generated and identified subgraph structure, information that can be obtained is clique subgraph represent there is a user network that polls on a question link and star subgraph represent there is one user contribute an answer on some question link on quora.com.
Gait Phase Recognition Based on A Wearable Depth Camera*

Gait phase recognition is fundamental for the control of assistive lower-limb exoskeletons or prostheses. In this paper, we have proposed an innovative strategy to estimate the human walking gait phase by means of a wearable depth camera. The proposed system is composed by two subsystems: periodic depth signal extraction and adaptive oscillator-based gait phase estimation. Validation experiments have been implemented with four subjects. Each subject performed three free ground-level walking trials at his/her preferred speed. Results showed that the proposed system could provide an accurate gait phase estimation based on a stable and periodic gait-related depth signal. The promising performance is expected to enable a lower-limb wearable robot to provide more stable and effective assistance for daily walking tasks.
Teaching Models in Rattaphumwittaya School Thailand

Received : October 2017 Accepted : December 2017 Published : January 2018 Science and technology has been included in all aspects of life not as well as education. Rapid changes of science and technology encourages the development and the use of effective teaching model. Thailand, one of the big countries in Southeast Asia, has developed a new curriculum and education system in 2008. This new curriculum and educational system impact on teaching models used. The purpose of this study was to describe the Biology teaching model applied in Rattaphumwittaya School Thailand. This study was a case study by qualitative research. Data were collected by observation, interviews, and documentation. Data were organized in five elements of the teaching model includes syntax, the social system, the principle of reaction, support systems, and the effect of teaching. It was found that the teaching models used includes direct instruction, group investigation, and inquiry training. The selected models for each level Mattayom depend on the student's character. Also, the higher grade , the less teacher dominance during learning.
Hybrid Approach for Large Size FC-BGA to Enhance Thermal and Electrical Performance Including Power Delivery

A new approach to flip chip package with hybrid packaging technologies is presented, which will be pretty much promising package solution as a large size FC-BGA (flip chip ball grid array) for SOC (system on a chip). The proposed new approach can be utilized to enhance power integrity and heat spreading and to reduce the FC-BGA package height with keeping and not degrading the mechanical property of conventional FC-BGA. The presented new package based on hybrid approach is implemented by the combination of thick-core based substrate and thin-core (or coreless) substrate. While most of area in package is mechanically supported by 800um thick core, SOC die is mounted on thin substrate by proper flip chip bonding. The interconnection between thick-core based substrate and thin-core (or coreless) substrate is achieved by wire bonding by conventional packaging process or RDL (redistribution layer) by fan-out package technology. Comparative study on the proposed new structure with conventional FCBGA is presented in terms of power integrity, signal integrity, and thermal resistance. Through several case studies, it is demonstrated that the presented hybrid approach is an adequate package solution for cost-effective thin FCBGA enhancing power integrity and thermal performance.
Grid-forming inverters replacing Diesel generators in small-scale islanded power systems

This paper addresses the stability analysis of a real island power system following the transformation occurring in the generation portfolio: from a 100 % synchronous-generation-based system (associated to a fleet of diesel generators) to a hybrid power system dominated by power electronics converters. The integration of a battery-wind-photovoltaic power plant in the island creates the necessary conditions for operating the system without synchronous units-scenarios with a system dominated by power electronics - or, at least to minimize its use–scenarios with a reduced number of synchronous units in operation. The possibility of operating the system under these conditions is assured by grid-forming inverters connected to battery energy storage systems, that are responsible for performing frequency and voltage control tasks either in parallel with synchronous units or when synchronous units are disconnected. The resulting transient stability issues for the aforementioned operational scenarios are discussed and evaluated through dynamic simulations.
Comprehensive Investigation on Warpage Management of FOPLP with Multi Embedded Ring Designs

On the urgent multi-function requirements of mobile products and internet of things, a more than Moore's rule becomes a major concern in accordance with the scaling limitation of advanced devices. Accordingly, the architecture of fan out panel-level packaging (FOPLP) grows into the mainstream to meet the essentials of three-dimensional chip stacking and heterogeneous integration. Nevertheless, unfavorable warpage and residual stress issues resulted from the reconstruction and assembly processes of FOPLP are introduced, decreasing the assembly yield and subsequently long-term packaging reliability. To resolve the above-mentioned problem, this research proposes a 370 × 470 mm2 carrier size FOPLP vehicle combined the novel designs of double embedded metal rings. The major geometrical characteristics of the foregoing metal rings are separately embedded in the multi-redistribution layers (RDLs) and epoxy molding compound (EMC) regions to control the process-induced warpage. On the basis of simulation-based factorial design, the key material selections, such as RDLs composed of photoimagable dielectric (PID) and EMC within the embedded metal rings, is investigated to significant restrain the induced warpage. Notably, a stiffer and a lower coefficient of thermal expansion (CTE) for PID are indicated to be an effective solution of miniaturizing the induced warp during the corresponding curing step. Consequently, a superior capability in warpage reduction after debonding process of panel level vehicles is acquired by means of the present simulation methodology and experimental validation.
Monocular Vision-Based Obstacle Detection Technique using Projected Grid Deformation

In this research, a novel technique for obstacle detection has been proposed. Typical obstacle avoidance and autonomous system applications make use of large number of different expensive active sensing equipment (LIDAR, RADAR, laser scanners and other sensors). While, this paper attempts to tackle the issue of obstacle detection using a relatively cost-effective set of active and passive sensors, namely a projector and monocular vision system. The proposed method makes use of grid projection on the surface for detection of stationary and moving obstacles on road with the help of assessing the deformation in grid line transformation. A host of different computer vision techniques have been utilized for grid line segmentation and detection to successfully detect obstacles and its distance from a fixed reference point. This paper examines the results of the grid projection on the object detection using different obstacle configurations to test the effectiveness of the proposed obstacle detection system.
econstor Make Your Publications Visible . A Service of zbw

Purpose: Political parties spend significant amounts of resources during their election campaigns, which are usually designed in a sub-optimal and informal way. This study aims to provide a mathematical framework for political parties to optimize their election campaigns, so that they can maximize their performance in the elections. Design/methodology/approach: In this work, we provide certain mathematical relations to determine the minimum necessary number of votes to gain additional seats in an election region under the D’hondt election rule. Also we develop a convenient mathematical model that optimizes the resource allocation scheme of a political party to maximize the potential seats won. We test our models on Turkish Parliamentary elections data Findings: Our results show that with various basic assumptions, which are suitable for real life cases, one can obtain significant gains in the election outcomes even with small budgets. We also provide the relations among swing vote rates, unit vote costs and budget with the number seats won in a parliament. Originality/value: This study provides useful insights for both political party management teams as well as researchers. Political parties need to conduct more market research to collect and work on election data to increase their performances. From the research perspective, to the best of our knowledge, this is one of first studies that approaches to the election campaigns for the D’hondt system with mathematical optimization tools.
Aalborg Universitet Step by Step Design of a High Order Power Filter for Three-Phase Three-Wire Grid-connected Inverter in Renewable Energy System

Traditionally, when designing an LCL-filter, a three-phase inverter is simplified as a single-phase inverter for analysis and the output phase voltage is used to calculate the inverter-side current harmonics and to design inverter-side inductor. However, for a three-phase three-wire grid-tied system, the output current harmonics of inverter are directly affected by the output line to line voltage. Hence, this paper proposes a new method to analyze the inverter output current harmonics by using the equivalent phase voltage of the three phase inverter. Based on this, a step by step design method of the high order power filter is introduced. Simulations are carried out to verify the accuracy and the validity of the proposed methods through a 6 kW, 380V/50 Hz grid-connected inverter model with three different types of high order power filters. Keywords—LLCL-filter; LCL-filter; current harmonics; voltage harmonics; equivalent phase voltage; design procedure; three-phase grid-tied inverter; SPWM
Weighted Sparse Representation and Gradient Domain Guided Filter Pyramid Image Fusion Based on Low-Light-Level Dual-Channel Camera

Generally, the dynamic range of night vision scenes is large. Owing to the limited dynamic range of traditional low light imaging technology, the captured images are always partially overexposed or underexposed. Multi-exposure fusion is the most effective method of overcoming the dynamic range limitation of sensor, and multi-frame low dynamic range (LDR) image fusion is a key consideration. However, existing fusion methods have problems such as image detail blurring and image aliasing. This paper proposes an image multi-scale decomposition method based on gradient domain guided filter (GDGF), which can better extract image details. The fusion algorithm adopts different fusion strategies for different scales. The low-frequency layer of the image uses a new weighted sparse representation (wSR) method, which can eliminate the image boundary problems and more adequately retain the image edges.
Performance of Discrete Wavelet Transform ( DWT ) Based Speech Denoising in Impulsive and Gaussian Noise

The aim of this paper is to investigate the effect of impulsive noise on the performance of the speech denoising using Discrete Wavelet Transform (DWT). The employed model of impulsive noise consists of Bernoulli distributed impulse arrivals and Gaussian distributed amplitudes of the impulses. In this study DWT algorithm has been applied for the suppression of ambient noise. This method is based on thresholding the wavelet coefficients, that can be done by standard deviation method for each frame by level dependent thresholding using different types of threshold (semisoft, hard soft and super soft) in channel contains impulsive and Gaussian noise together. The results of simulation indicate that using discrete wavelet transform in speech denoising application provides a good quality and semisoft threshold gives the best performance. خلا ـ صلا ـــــــ ة أوبضلا ا أووولا رريثأت ةسارد وه ثحبلا اذه نم فدهلا (Impulsive) ادختأس ب ا أووولا تأرليت تأريمت ألع رأرعوت رأم ودراوألا ا أوبضلل لوأضرب رأرعوت ادختأسا أت . ةعطيملا ةجروملا تروحت (Gaussian) تأريمتل ةرأوبضلا أميلل . وبضلا ا ووولل تردوملا ةساردلا هذه ف ت ألع ةأرمعراوخلا هذأه دأمتعت . ا أووولا رأليتل ةأعطيملا ةأجروملا تأروحت ةرمعراوخ ادختسا ةجروملا تماوع رليت سوب هع جض أ نكمر تلاو رطيم تكل ير رعملا فارحضلاا ةيررط ةط (Frame) ت ادختأس ب ي تأكل رأل ةلحرم (Level Dependent Thresholding) اوأضأ ادختأسا ت ثرح رليتلا نم ةفلتخم (Semisoft, Hard soft and Super soft) ا ووولا و وبضلا ا ووولا نم فلثتت و ضق ف (Gaussian) . ًعم اذه ف ةلصحملا جئ تضلا ررشت ثحبلا لإ نإ ةأجروملا تروحت ادختسا ةأعطيملا نأم ا أووولا ةألاعإ ا أيربطت أف ودرج جئ تض طعأ دق اوصلا رليتلاو (Semisoft) . جئ تضلا توفأ طعأ
Selected Methods for Modern Optimization in Data Analysis

In this lecture, we first state the mathematical formulation of an optimization problem, both in unconstrained and constrained settings. Next, we recall some fundamental concepts used in mathematical optimization problems. After that we classify optimization problems into different classes based on structures of the problem components, and briefly discuss the aim of solution methods. Finally, we provide several optimization models in practice including convex and nonconvex models.
Why Users Habituate to Security Warnings : Insights from fMRI

Warning messages are one of the last lines of defense in computer security, and are fundamental to users’ security interactions with technology. A key contributor to pervasive user disregard of security warnings is habituation, the diminishing of attention due to frequent exposure to a warning. Research that has examined habituation and security warnings has done so indirectly, by observing the influence of habituation on security behavior, rather than measuring habituation itself. This study seeks to contribute by using neuroscience to open the “black box” of the brain to observe habituation as it occurs. Specifically, we point to the repetition suppression (RS) effect, the reduction of neural responses to stimuli that are viewed repeatedly, a phenomenon directly antecedent to the process of habituation. By investigating how repetition suppression occurs in the brain, we can make a more precise approach to designing security warnings that are resistant to, or possibly can even reverse the effects of habituation. We propose a series of three laboratory experiments using functional magnetic resonance imaging (fMRI) to observe brain data and improve user interaction with security warnings.
CLOUD COMPUTING MESH MODEL FOR DECISION SUPPORT SYSTEMS

This paper introduces the use of service science to enhance decision-making capability by providing service transparency to information from diverse knowledge sources in a complex operating environment. The concept of a live collector that runs in the cloud is developed. The collector gives information visibility, context mediation, and presentation facilities on a dynamic basis by employing the principles of cloud computing. The subject of cloud computing is introduced in the paper, and a case study from decision support is presented.
Do Significant Stock Price Drops Signal Red Flag for Financial Statement Fraud ?

Stock price drops are regular occurrences in capital markets. However, when such drops are significant or occur more frequently, they can be of great concern to management. The significance and frequency of such drops, however, could signal potential problems. How management reacts to the prevention of such stock price drops is particularly important to a number of stakeholders, especially if these firms fit the description of firms that engage in financial statement fraud. The Statement on Auditing Standards No. 99 define financial statement fraud: Consideration of Fraud in a Financial Statement Audit (SAS 99), as an intentional act that results in a material misstatement in financial statements. There are two types of fraud considered in this definition: misstatements arising from fraudulent financial reporting (e.g., falsification of accounting records) and misstatements arising from misappropriation of assets (e.g., theft of assets or fraudulent expenditures). Often, management do feel some pressure to manipulate the company's accounting practices and, consequently, its financial reports to meet these expectations and keep the company's stock price up and from dropping in the future. While there are several reasons companies experience stock price drops, an earnings announcement that falls short of expectations is a good example. As stakeholder expectations do reflect firms’ earnings expectations, management may adopt a more aggressive earnings management style in reaction to stock price drops in order to prevent future drops. While earnings management may not necessarily be fraudulent, aggressive or excessive earnings management has the potential to be considered fraudulent rather than simply an earnings management. Earnings management is where management carefully applies selected accounting choices and estimates, within the confines of the U.S. Generally Accepted Accounting Principles (GAAP), towards a desired outcome. That is, when firms use earnings management to smooth out fluctuations in earnings and/or to meet stock analysts’ earnings projections, is not considered illegal or fraudulent. However, a deliberate, intentional, or reckless conduct by management in applying excessive or aggressive GAAP rules in order to mislead or deceive investors through financial misstatement is illegal and therefore fraudulent.