Reviewerly/exHarmony huggingface dataset:
A Method for Calculating the Optical Efficiency of Solar Tower Heliostats

Solar tower heliostat is one of the highlights of China's new energy development in recent years, the Optical Efficiency is an important index for evaluating the field distribution of heliostat, but the calculation of Shadow Blocking Efficiency and Truncation Efficiency is more complicated. In this paper, through the ray tracing method, based on the idea of Monte Carlo algorithm, combined with the calculation method of spatial analytic geometry, a more complete and operable method of calculating Optical Efficiency is proposed.
Motion estimation and multi-stage association for tracking-by-detection

Abstract Multi-object tracking (MOT) aims to locate and identify objects in videos. As deep learning brings excellent performances to object detection, the tracking-by-detection (TBD) has gradually become a mainstream tracking framework. However, some drawbacks still exist in the current TBD framework: (1) inaccurate prediction of the bounding boxes would occur in the detection part, which is caused by overlooking the actual pedestrian ratio in the surveillance scene. (2) The width of the bounding boxes in the next frame might be indirectly predicted by the aspect ratio, which increases the error of width prediction in the motion prediction part. (3) Association is only performed for high-confidence detection boxes, and the low-confidence boxes caused by occlusion are discarded in the data association part, resulting in fragmentation of trajectories. To address the above issues, we propose a multi-target tracking model incorporating motion estimation and multi-stage association (MEMA). First, the aspect ratio of the ground-true bounding box is introduced to improve the fit of the detection and the ground-true bounding box, and we design the elliptical Gaussian kernel to improve the positioning accuracy of the object center point. Then, the prediction state vector of the Kalman filter is modified to predict the width and its corresponding velocity directly. It can reduce the width error of the prediction box and eliminate the velocity error of the motion estimation, which leads to a more pedestrian-friendly prediction bounding box. Finally, we propose a multi-stage association strategy to correlate different confidence boxes. Without using the appearance feature, the strategy can reduce the impact of occlusion and improve the tracking performance. On the MOT17 test set, the method proposed in this paper achieves a MOTA of 74.3% and an IDF1 of 72.4%, outperforming the current SOTA.
Test Grammars Spellings

The following is a partial link of scientific journals There are thousands of journals in publications and many more have been published at various levels in the history of articles The list given here has been far from exhaustive approach and follows the methodology of publishing over the growth of society of chemical Industry There are many science journals which are not scientific journals nowadays but there are several journals which are still famous over the world for the scientific approach and technology It consists of
Sunshine and solar power in the UK

Abstract Solar power is an increasingly important source of clean energy even for a relatively cloudy mid-latitude nation such as the UK. Using areal sunshine series published by the UK Met Office, this study describes the continuing brightening trend that has also been observed since the mid-1980s around the world. The use of the automated Lamb weather type system is explored, particularly the surface synoptic indices developed by Jenkinson and Collison. There is a strong association between sunshine duration (via cloudiness) and circulation features such as anticyclonicity; however, there is no surface-level circulation trend observed that can explain the brightening.
Finite Mixture MLE and EM Algorithm

The latent structure inherent in mixture models offers a fitting scenario for the renowned EM algorithm. In Chap. 7, we begin by offering a general overview and then get into comprehensive explanations of the EM algorithm’s application in computing the maximum likelihood estimate for finite mixture models. This chapter also addresses the critical matter of algorithm convergence, taking into consideration the global convergence theorem. Additionally, it provides specific insights into the workings of the EM algorithm.
Estimation Under Finite Normal Mixture Models

The finite normal mixture model stands out as the most frequently employed model in statistical applications. Nevertheless, it exhibits some peculiar characteristics. Notably, the general finite normal mixture model boasts an unbounded likelihood function, rendering the straightforward maximum likelihood estimator of the mixing distribution inconsistent. However, in the case of the univariate normal mixture with a structured scale parameter, the maximum likelihood estimator is consistent. To attain consistency in the likelihood-based approach, one can apply a penalty function to the likelihood. Chapter 4 charges into these issues and more, offering a comprehensive examination of the most crucial asymptotic properties.
Consistent Estimation Under Finite Gamma Mixture

The application of finite Gamma mixture models is prevalent when working with strictly positive observations. Surprisingly, the likelihood function within this framework is unbounded, theoretically leading to an inconsistent maximum likelihood estimator. However, it is worth noting that, in practice, this inconsistency rarely manifests in data analysis. Nevertheless, this chapter provides an in-depth exploration of the development of a consistent penalized maximum likelihood estimator for Gamma mixture models. In addition to this, it enriches the discussion with valuable insights gained through simulation experiments and real-world data examples.
Online Handwritten Signature Verification Method Based on Uni-Feature Correlation Coefficient between Signatures

Online handwritten signature verification is a crucial direction of research in the field of biometric recognition. Recently, many studies concerning online signature verification have attempted to improve performance using multi-feature fusion. However, few studies have provided the rationale for selecting a certain uni-feature to be fused, and few studies have investigated the contributions of a certain uni-feature in the multi-feature fusion process. This lack of research makes it challenging for future researchers in related fields to gain inspiration. Therefore, we use the uni-feature as the research object. In this paper, the uni-feature is one of the X and Y coordinates of the signature trajectory point, pen pressure, pen tilt, and pen azimuth feature. Aiming to solve the unequal length of feature vectors and the low accuracy of signature verification when using uni-features, we innovatively introduced the idea of correlation analysis and proposed a dynamic signature verification method based on the correlation coefficient of uni-features. Firstly, an alignment method of two feature vector lengths was proposed. Secondly, the correlation coefficient calculation formula was determined by analyzing the distribution type of the feature data, and then the correlation coefficient of the same uni-feature between the genuine signatures or between the genuine and forged signatures was calculated. Finally, the signature was verified by introducing a Gaussian density function model and combining it with the signature verification discrimination threshold. Experimental results showed that the proposed method could improve the performance of dynamic signature verification based on uni-features. In addition, the pen pressure feature had the best signature verification performance, with the highest signature verification accuracy of 93.46% on the SVC 2004 dataset.
On the Use of Breath in the Performance of Yangqin Song "Loess Sentiment"

The dulcimer's timbre is clear, the expressive force is rich, the smooth breath is the perfect work presents the premise. However, whether the breath is unblocked does not directly affect the playing effect, but indirectly through the player's physical coordination and psychological state to the player's playing effect. breath is unblocked does not directly affect the playing effect, but indirectly through the player's physical coordination and psychological state to However, whether the breath is unblocked does not directly affect the playing effect, but indirectly through the player's physical coordination and psychological state to affect the playing effect. the influence of breath in dulcimer performance, the embodiment of breath in dulcimer works, The advantages and disadvantages of breath in dulcimer performance and the ways to avoid the disadvantages performance and the ways to avoid the disadvantages of breath in dulcimer performance are expounded.
Analysis of the Path and Countermeasures for the Central Bank's Digital Currency to Boost the Internationalization of the RMB

In order to meet the needs of China's economic development and international trade, and to prevent potential risks arising from the international monetary system dominated by the US dollar, China officially began the process of RMB internationalization in 2009. However, in the process of development, it faces obstacles caused by factors such as US dollar hegemony and limited financial openness in China. In recent years, China has further developed the internationalization of the RMB and achieved significant results. Among them, the issuance of the Central Bank's Statutory Digital Currency (DC/EP) in 2020 has brought a new upgrade to the RMB. As an emerging circulation method, the digital RMB has the advantages of efficiency, convenience, centralized management, and information recording, bringing a new development to the internationalization of the RMB. It can be foreseen that with the development of China's economy and technology, the digital RMB will play an important role in future development. This article aims to analyze the current development status of RMB internationalization, explore the opportunities and challenges brought by the issuance of legal digital currency by the central bank to the development of RMB internationalization, and propose corresponding countermeasures and suggestions.
The Nobel and Back Again

Abstract This article re-evaluates the translation strategy of the Italian publisher Mondadori for Pearl S. Buck. From the first translations in the book series Medusa to the latest editions of the 2010s, the publisher’s literary assessment and marketing strategy for Buck’s oeuvre fluctuated towards and away the standing of a Nobel Prize laurate. By collecting and analysing a variety of records from the publisher’s archive at Fondazione Arnoldo and Alberto Mondadori (Milan, Italy) and the Deutsches Literaturarchiv (Marbach, Germany), this contribution challenges pre-existing narratives concerning this author’s Italian publication history. By identifying four phases in Mondadori’s programme for Pearl S. Buck, it argues that a rebranding that intentionally moved her public image away from the unwieldy shadow of the Nobel ultimately prolonged Buck’s success in the Italian language throughout the 20th and 21st centuries.
Indoor replication of outdoor climbing routes: fidelity analysis of digital manufacturing workflow

Abstract This study aims to evaluate the advantages and criticalities of applying additive manufacturing to produce climbing holds replicating real rocky surfaces. A sample of a rocky surface has been reproduced with a budget-friendly 3D scanner exploiting structured light and made in additive manufacturing. The methodology is designed to build a high-fidelity replica of the rocky surface using only minor geometry modifications to convert a 2D triangulated surface into a 3D watertight model optimised for additive manufacturing. In addition, the research uses a novel design and uncertainty estimation approach. The proposed methodology proved capable of replicating a rocky sample with sub-millimetre accuracy, which is more realistic than conventional screw-on plastic holds currently used in climbing gyms. The advantages can be addressed in terms of customisation, manufacturing cost and time reduction that could lead to real outdoor climbing experiences in indoor environments by coupling additive manufacturing techniques and reverse engineering (RE). However, operating the scanner in a rocky environment and the considerable size of the climbing routes suggest that further research is needed to extend the proposed methodology to real case studies. Further analysis should focus on selecting the best material and additive manufacturing technology to produce structural components for climbing environments.
Boosting Lightweight Sentence Embeddings with Knowledge Transfer from Advanced Models: A Model-Agnostic Approach

In this study, we investigate knowledge transfer between two distinct sentence embedding models: a computationally demanding, highly performant model and a lightweight model derived from word vector averaging. Our objective is to augment the representational power of the lightweight model by exploiting the sophisticated features of the robust model. Diverging from traditional knowledge distillation methods that align logits or hidden states of teacher and student models, our approach uses only the output sentence vectors of the teacher model for the alignment with the student models’s word vector representations. We implement two minimization techniques for this purpose: distance minimization and distance and perplexity minimization Our methodology uses WMT datasets for training, and the enhanced embeddings are validated via Google’s Analogy tasks and Meta’s SentEval datasets. We found that our proposed models intriguingly retained and conveyed information in a model-specific fashion.
What Types Are Needed for Typing Dynamic Objects? A Python-Based Empirical Study

Dynamic object-oriented languages, such as Python, Ruby, and Javascript are widely used nowadays. A distinguishing feature of dynamic object-oriented languages is that objects, the fundamental runtime data representation, are highly dynamic, meaning that a single constructor may create objects with different types and objects can evolve freely after their construction. While such dynamism facilitates fast prototyping, it brings many challenges to program understanding. Many type systems have been developed to aid programming understanding, and they adopt various types and techniques to represent and track dynamic objects. However, although many types and techniques have been proposed, it is unclear which one suits real dynamic object usages best. Motivated by this situation, we perform an empirical study on 50 mature Python programs with a focus on object dynamism and object type models. We found that (1) object dynamism is highly prevalent in Python programs, (2) class-based types are not precise to handle dynamic behaviors, as they introduce type errors for 52% of the evaluated polymorphic attributes, (3) typestate-based types, although mostly used in static languages, matches the behaviors of dynamic objects faithfully, and (4) some well-designed but still lightweight techniques for object-based types, such as argument type separation and recency abstraction can precisely characterize dynamic object behaviors. Those techniques are suitable for building precise but still concise object-based types.
Dual Siamese Anchor Points Adaptive Tracker with Transformer for RGBT Tracking

Abstract Due to environmental conditions, such as rainy days, foggy days, and dim lighting, objects in visible light images are not prominently displayed, leading to an easy loss of targets during tracking. In recent years, many RGB visible light trackers have achieved significant success in addressing visual tracking challenges. However, these trackers perform poorly when tracking targets under special conditions, such as occlusions and low-light scenarios. In contrast, objects in thermal infrared images are more distinct in poor lighting conditions. Given this characteristic, researchers have shown increased interest in the development of trackers that combine thermal infrared and visible light imagery. However, some mainstream RGBT (red–green–blue and thermal) algorithms, such as MANET and ADNET, are based on the anchor-based theory, requiring consideration of anchor box sizes and introducing a substantial number of hyperparameters. This can lead to suboptimal performance when tracking dynamically changing targets. Moreover, these models rely on convolutional neural networks for feature extraction, which have limitations in capturing global features. In this paper, we introduce a novel training network model called DAPAT, which combines the anchor-free concept with Transformer theory. DAPAT differs from previous models in several ways. Specifically, we have designed a straightforward model to extract precise global features from template and search images. We have also incorporated two enhancement modules into the model to improve template and search images of different sizes while suppressing the impact of non-target images. We employ a dual-stream feature fusion network to reduce the loss of image feature information due to feature correlation operations. Finally, we compare the performance of the tracking model proposed in this paper with some advanced RGBT trackers on three data sets (RGBT234, RGBT210, and GTOT). The test results demonstrate that our tracker exhibits improvements in robustness and success rate, among other performance aspects.
EFL UNDERGRADUATE STUDENTS’ DIFFICULTIES IN WRITING LITERATURE REVIEW OF THEIR THESIS

Writing a thesis is difficult for undergraduate students, especially in the writing literature review section. In the English study program at Jambi University, the students faced some difficulties in writing their literature reviews. Hence, this study aims to investigate EFL undergraduate students’ difficulties in writing the literature review of their thesis. There were two questions addressed. The first is why writing a literature review difficult for many English department students. The second is how do students overcome the difficulties in writing a literature review of their thesis. The method and design used in this research were descriptive qualitative. In-depth interviews were chosen as the instrument to collect the data. There were 8 participants of the academic years 2016 and 2017 who had been adjusted to the criteria. Based on the discussion, the students have difficulties writing a literature review such as selecting relevant references, restricted access to journals and textbooks, the language of the references was difficult to understand, lack of ability in writing a literature review, and lack of supervisor comment. However, the students have their own ways to overcome those problems.
STUDENTS’ PERCEPTION ON THE USE OF MIND MAPPING TECHNIQUE TO IMPROVE STUDENTS’ ABILITY IN WRITING DESCRIPTIVE TEXT

The objective of the research is to explore the students’ perception of using Mind Mapping in writing descriptive text. Also, this study aims to describe the advantages and disadvantages of using Mind Mapping in writing descriptive text. This research used mix-method design, in which the data were collected through questionnaire and interview. The participants of this study were the students of SMA Negeri 1 Muara Bungo and also interviewed an English teacher. The data obtained from interviews were analyzed. There were three major points, first students’ interest in using mind mapping in writing descriptive, second the difficulty in using mind mapping for students, third improve students’ writing skills. According to the data, mind mapping had a positive impact on students’ writing skills i.e. students’ better understanding and know what they are doing. In conclusion students think that mind mapping is interesting, and have advantages and disadvantages. The implication of this research is to increase students awareness in using mind mapping for writing.
Bode Integral Limitation For Irrational Systems

Bode integrals of sensitivity and sensitivity-like functions along with complementary sensitivity and complementary sensitivity-like functions are conventionally used for describing performance limitations of a feedback control system. In this paper, we investigate the Bode integral and evaluate what happens when a fractional order Proportional-Integral-Derivative (PID) controller is used in a feedback control system. We extend our analysis to when fractal PID controllers are applied to irrational systems. We split this into two cases: when the sequence of infinitely many right half plane open-loop poles doesn't have any limit points and when it does have a limit point. In both cases, we prove that the structure of the Bode Integral is analogous to the classical version under certain conditions of convergence. We also provide a sufficient condition for the controller to lower the Bode sensitivity integral.
A Control Barrier Function Approach for Observer-based Visually Safe Pursuit Control with Spherical Obstacles*

Pursuing a target in the presence of obstacles requires that an autonomous mobile robot keeps sight of the target in a way robust to the target's unknown behavior. This paper presents visually safe pursuit control, which keeps a target with the unknown motion inside the camera's field of view while preventing occlusion caused by spherical obstacles. Framed as forward invariance of sets in the SE(3) state space, visual safety is ensured by the Control Barrier Functions (CBFs) approach. Concretely, by showing the Input-to-State stability of the vision-based observer that estimates the target's motion, we design safety certificates for visual safety that accommodate uncertainties in the target's motion. This enables us to synthesize a safe controller as a Quadratic Programming problem. Finally, the theoretical results are verified via a simulation of a visual pursuit scenario.
Macroeconomics of Digitalization—Evolving Issues and Perspectives

Despite the rapid pace at which digitalization has permeated various sectors of the economy, the assessment of its macroeconomic implications remains scarce in extant literature. This exploratory article provides a generalized perspective on the impact of ongoing digitalization on key economic indicators related to productivity and economic growth, inflation dynamics, financial markets, and currency demand. Deriving insights from contemporary literature in the field, we posit that the unprecedented advancements in technology can contest various postulates of conventional macroeconomic theory, thereby warranting agile policymaking to recalibrate the economy for the new digital order. This synoptic piece aims to encourage theoretical and empirical research works on the evolving issues of digitalization from the context of developing and emerging market economies.
Software Tool for Distribution of Linear Temporal Logic Specifications

This work presents the implementation of a software tool that ensures the execution of a global Linear Temporal Logic (LTL) specification for a team of mobile agents that are evolving in a static and known environment cluttered with regions of interest. The software is build on formalisms that extend our previous work, with the main contribution of handling strictly more expressive missions that also allow negations (or temporal avoidance) of some regions of interest. An algorithm is provided for decomposing the global LTL mission into independent robots' tasks, together with a flow diagram of the entire method that solves the path planning problem. Simulations and comparative results are discussed for a case study, in order to support the usefulness of the software tool.