Reviewerly/exHarmony huggingface dataset:
An Improved B-spline Extended Object Tracking Model using the Iterative Closest Point Method

A star-convex shape based on Cartesian B-splines provides a good model for detailed extended target tracking, suited for, e.g., high resolution automotive sensors. Motivated by real-world sensor data from traffic scenarios, we present an extended object tracking filter that (i) solves the problem of bad object initialization for contour tracking of mixed-size vehicles in a range of common traffic scenarios; (ii) enables accurate tracking of objects such as motorcycles, that generates detections distributed on the surface, rather than on the contour. Our approach is based on star-convex Cartesian B-spline polynomials, iterative closest point (ICP) and the convex hull. In particular, we implement the ICP algorithm to find the translation and rotation of the contour that best fit the sensor point cloud. We show that, while the original B-spline filter with a “second-time-step-initialization-procedure” fails to robustly track the object, our approach performs on par to the original B-spline filter with ground truth initialization. Furthermore, for targets generating detections on the surface, we utilize the convex hull algorithm on the point cloud. We show that our algorithm successfully tracks the object, while the original B-spline filter fails to robustly track the contour of a motorcycle.
A Fast Poisson Multi-Bernoulli Filter for Multiple Target Tracking

This paper presents the Poisson Multi-Bernoulli filters for reducing the complexity. This technique is derived based on Poisson Multi-Bernoulli Mixture (PMBM) filters and Poisson Multi-Bernoulli (PMB) filters for multiple target tracking. The complexity of PMB is increased exponentially with the number of propagated Bernoulli components. There are many cases in which this expansion of complexity is an obstacle blocking incorporation into consumer products. FMB dramatically lower the complexity by using approximation for the data association, which is a bottleneck in PMB processing. Also, under conditions in which tracking has a high degree of difficulty and much clutter is generated, FMB showed performance equivalent to PMB.
The PHD Filter for Target Swarms and Its Gaussian Mixture Implementation

The swarm is used to describe a set of individual targets which are very close together in the measurement space (relative to the resolution of the sensor). In this paper, we consider to estimate the number, shape and density of target swarms in addition to their motion states. In order to deal with the uncertain number of measurement origins, we use amplitude information (AI) to construct hypotheses about the number of individual target source of the merged measurement in the probability hypothesis density (PHD) update step. On this basis, we propose the PHD filter for target swarms (S-PHD filter) and develop Gaussian mixture (GM) implementation to the resulting filter. The performance of this algorithm is demonstrated by a multi swarms scenario with merged measurements, and the results highlight the significant improvement in the estimates of the number of individuals and the density of swarms.
Fusion of sentence embeddings for news retrieval

The availability of a vast quantity of information from news channels and social media, make it often difficult to find and follow specific events. This applies to both casual readers and to intelligence and emergency response analysts. In particular, the latter need to find and process relevant information within sense-making, situation and impact assessment processes. The automatic retrieval and tracking of news has been addressed by a good number of works in the information retrieval literature. However, there is a strong potential for introducing automatic systems employing information fusion methods and techniques to assist decision makers. In the field of deep learning, several techniques for text encoding have been proposed, which have allowed significant progress also in the field of news retrieval and ranking. The objective of this paper is to explore the usage and combination of different pre-trained sentence embeddings, including multimodal ones, obtained from different parts of text that compose a news story. This in order to understand which type of technique is best for encoding the different information available in online news.
Multi-Frame Track-Before-Detect for Scalable Extended Target Tracking

This paper mainly addresses the scalable detection and tracking of the extended target in the low signal-to-noise(SNR) environment. As the appearance and shape of the extended target are constantly varied, it is challenging to achieve robust detection and tracking. For this, a novel adaptive scale (AS) kernelized correlation filter (KCF) based on multi-frame track-before-detect (MF-TBD) framework is proposed. By embedding scaling pools into the response map to handle the scale variation and accumulating target energy overall feasible trajectories, AS-MF-TBD estimates the kinematic state and geometric shapes simultaneously. Both simulation data and real radar data are used to demonstrate the superiority of the proposed method in terms of detection performance and estimation accuracy.
Universality and Real Data

This chapter exploits concentration-of-measure approach for real data modeling, via the recent advance of deep generative adversarial networks (GANs). This assessment theoretically supports the surprisingly good match between theory and practice observed on real-world data in previous chapters. Conclusion on the universality of large-dimensional machine learning is drawn at the end of the chapter.
Ambiguous Definite Pronoun Resolution via Lambek Calculus with Soft Sub-Exponentials and Machine Learning

We propose a mathematical framework for a unification of the distributional theory of meaning in terms of vector space models, and a compositional theory for grammatical types, namely Lambek's pregroup semantics.A key observation is that the monoidal category of (finite dimensional) vector spaces, linear maps and the tensor product, as well as any pregroup, are examples of compact closed categories.Since, by definition, a pregroup is a compact closed category with trivial morphisms, its compositional content is reflected within the compositional structure of any non-degenerate compact closed category.The (slightly refined) category of vector spaces enables us to compute the meaning of a compound well-typed sentence from the meaning of its constituents, by 'lifting' the type reduction mechanisms of pregroup semantics to the whole category.These sentence meanings live in a single space, independent of the grammatical structure of the sentence.Hence we can use the inner-product to compare meanings of arbitrary sentences.A variation of this procedure which involves constraining the scalars of the vector spaces to the semiring of Booleans results in the well-known Montague semantics.
Building System To Improve The Quality Of Digital Educational Images Used In The Production Of Electronic Courses

&#x0D; The aim of the research is to build a system to improve the quality of digital images used in the production of electronic courses, as this proposed system relied on digital image processing using recursive curve modification histogram techniques (through a set of stages including the stage of converting the color image to a gray scale image, then the stage Removing noise from the image, then the stage of resetting the contrast of the image Histogram Equalization Technique, with a judgment or decision on the importance of the improved image resulting from the system automatically, by comparing the (SSIM) value between the original image and the enhanced image and coming up with a decision before outputting The image on the screen and how useful it is, or keep the original image.
Scientific Articles and Publication Training for English Teachers of SMP and SMA in Rokan Hulu

In writing and publication of scientific articles, lecturers need to be present to train teachers. This is in line with the task of lecturers in implementing the Tridharma of higher education and the main performance indicators; lecturers work outside the campus. Therefore, all lecturers of the English department of Universitas Pasir Pengaraian contributed to help English teachers in Rokan Hulu in writing and publishing scientific articles. The objectives of the service activities are:(1)to increase teachers’ understanding and competence in writing scientific articles;(2)to provide assistance to teachers in writing scientific articles;(3)to increase teachers' understanding of how to publish scientific articles. The number of participants for the first activity were 25 English teachers SMP and 80 English teachers for the second activity. The results of the activities were that the teacher can write articles starting from writing article identities, abstracts, introductions, citations and references, methods, presentation of results and discussions, understanding of using the Mandeley application. Although it had not been proven that articles had been published, the teachers already known and understood the procedures for publication on journals and proceedings.&#x0D; Abstrak&#x0D; Dalam penulisan dan publikasi artikel ilmiah, dosen perlu hadir untuk melatih guru. Hal ini sejalan dengan tugas dosen dalam pelaksanaaan tridarma perguruan tinggi dan indicator kinerja utama; dosen berkegiatan diluar kampus. Maka, semua dosen prodi Pendidikan Bahasa Inggris Universitas pasir pengaraian berkontribusi membantu guru Bahasa inggris di Rokan Hulu dalam penulisan dan publiksai artikel ilmiah. Tujuan kegiatan pengabdian adalah:(1) meningkatkan pemahaman dan kompetensi guru dalam penulisan artikel ilmiah;(2) melakukan pendampingan kepada guru dalam menulis artikel ilmiah;(3) meningkatkan pemahaman guru tentang cara publikasi artikel ilmiah. Jumlah Peserta kegiatan pertama yaitu 25 guru Bahasa inggris SMP dan peserta kegiatan kedua 80 guru Bahasa inggris SMA. Hasil kegiatan yaitu guru sudah bisa menulis artikel dimulai dari penulisan identitas artikel, abstrak, pendahuluan, pengutipan dan referensi, metode, penyajian hasil dan diskusi, paham menggunakan aplikasi mandeley. Meskipun belum terbukti sudah publikasi artikel, para guru sudah mengetahui dan memahami tata cara publikasi pada jurnal maupun prosiding.
Deployment of automated teller machinery for e-polling

Voting plays a significant role in electing a suitable person by the public to rule the country. In this modern age of digitalization, we still use electronic voting machine (EVM), which is not entirely automated and has got many limitations. This machine replaces the traditional way of collecting votes through boxes consisting of voting papers. This method is called as the paper ballot. This system has slowly changed or altered into a new technical and mechanical system that uses EVMs to avoid misconceptions. Even though this voting machine is fast and accurate, this system needs more work-force and also it is not much more reliable. Most of the eligible voters cannot cast their vote due to immigration for a job, education, etc. Also, the government spends a lot of money arranging the vote booths and maintaining the decorum of the election.This chapter proposes a framework that changes the automated teller machine (ATM) framework to function as EVM. One of the fundamental advantages of utilizing ATMs as EVM is encouraging the political decision process for everybody and letting immigrants vote for their constituency. One of the main benefits of using ATMs as EVM is to facilitate the election process for everyone. Also, using ATMs as EVM will save time for all voters and eliminate the waste of your time in the long queue for the regular election process. Any voter needs just to hit for the closest ATM in his\her area and afterward utilizing electronic virtual card (EVC) embeddings it into the ATM picks the choice political decision.
Dollar Sanctions, the Digital Yuan, and Regulating FinTech

Speculation has been mounting that the digital yuan will be used to displace the US dollar and circumvent sanctions. In retaliation, financial institutions can be targeted whereby US dollar payment or financial system access can be sanctioned. If the United States weaponizes the dollar, the digital yuan will not provide sanction protection beyond the status quo. The digital yuan’s true innovation is the ability to manage capital controls and facilitate financial liberalization. Being a programmable currency, the digital yuan enables Mainland China to open its economy more expeditiously than would normally be possible, while providing the regulatory levers to manage monetary and financial stability. Mainland technology companies are instrumental in the circulation of the digital yuan through electronic payment platforms. These same technology companies have recently established virtual banks and stored value facility payment platforms in Hong Kong. This chapter argues that technology is introducing new risks into Hong Kong’s banking system which pose a material risk to financial stability. To manage these risks, financial data supervision and infrastructure is required which currently does not exist. With the recent growth surge and volatility in cryptocurrency markets, the current approach of neglecting financial stability supervision is erroneous and reckless.
Propositional Logic Semantics

The semantics of propositional formulas: models and truth tables, tautologies and contradictions. Disjunctive Normal Form and the DNF Theorem. Optional: Conjunctive Normal Form and the CNF Theorem, computational search problems, satisfiability, P and NP.
Proof by Deduction

An introduction to deductive proofs. Inference rules and their specializations. Implementation of a “Proof” object in Python. The Soundness Theorem.
An Essay on Quantum Processors

Abstract: Fundamentally we need a processor to carryout computations and intelligent jobs. A CPU in a computer based on Intel technology has been common. As is time getting advanced researchers continued working on large problems for solutions with in minimum time. They expect quantum computers could give good answer in minimum time. This article tried to understand the quantum processors.
Review Paper on a Study on SQL Attacks and Defense

In today's era, every person is utilizing websites and so many different web applications for online administrations, for example booking of railway tickets, movie ticketing, shopping, communication, and so forth. These websites consist sensitive and confidential information. With the linearity of web applications in the last decade, the unconstructive crash of security has also matured either. SQL injection attack is one such attack where the anonymous user can append SQL code to the input query. This research paper starts with developing criteria for a systematic literature review based on research questions, quality assessment, and data samples. The paper presents various SQL injection techniques with their intended attacks. Further studies explore different techniques to prevent attacks. Existing vulnerabilities of Web systems threaten the regular work of information systems. The most common Web system vulnerability is SQL injection. There are known approaches to protect Web applications against SQL injection attacks in the article. To improve the Web software security is developed defense mechanism that protects Web resources from SQL injection performing. To implement this software it is used PHP, JavaScript, and formal language theory known as regular expressions. As a result, it is received a software tool that allows protecting Web software from SQL injection vulnerability. The developed software tool allows users to protect their Web applications from an attack using SQL.
Studi Perbandingan Prestasi Belajar Matematika Menggunakan Model Pembelajaran Discovery Learning dan The Power of Two

This study aims to find out the differences in the learning achievements of students who are taught using the Discovery Learning learning model with students who are taught using the Power of Two learning model. This type of research is Quasi Eksperiment. Sampling techniques use Probability Sampling by means of Cluster Random Sampling so that class VIII B is obtained as a Discovery Learning class and class VIII C as the Power of two class. Data collection techniques are carried out by means of obervasi and write tests. The data was analyzed using a normality test, a homogeneity test and an independent sample t test. From the results of the study obtained (i) The average cognitive learning outcome (post-test) of class VIII B students with discovery learning model of 79.22 and the average cognitive learning results (post-test) of class VIII C students with the learning model of the Power of Two of 79.11. (ii) there is no significant difference between a student's mathematical learning achievement after being taught using the Dicovery Learning model and the Power of Two.
Research on the Application of Information-Based Big Data Fusion Technology in College English Education Design

English is the most widely used language in the world, and China’s economic development has become the second largest country in the world. Therefore, popularizing English in China is the need of national conditions and the desire for talents who are good at English majors. In the current traditional college English education mode and in the external environment, college students’ English knowledge has not been substantially expanded, which has seriously caused the social needs not being met and students not being able to show their self-worth. Based on the deficiency of traditional college English teaching mode, this paper designs an efficient and perfect college English education mode by combining information big data fusion technology, so as to ensure that students can really love English and learn English more easily. The results of the experiment are as follows: (1) college English education and students’ English learning are analyzed, and the research direction of the experiment is approved, and the functional has been investigated, which lays a foundation for the experimental research of this paper; (2) old-fashioned college English education mode: intelligent big data technology is applied to English education. By using the information big data fusion algorithm to ensure the qualified English teaching effect, it not only helps teachers effectively combine big data resources but also changes the atmosphere of teaching classes, constructs modern language education mode, and promotes students’ thinking mode of exploring language learning.
MoG-DS: model-guided deep convolutional network for joint denoising and super-resolution of a single-photon counting image

Single-photon counting (SPC) imaging has attracted considerable research attention in recent years due to its capability to detect targets under extremely low-light conditions. However, the spatial quality of SPC images is always unsatisfactory because they typically suffer from considerable effects of noise and their spatial resolution is low. Most traditional methods are dedicated to solving the noise problem while ignoring the improvement of spatial resolution. To address these challenging issues, we propose a novel model-guided deep convolutional network for joint denoising and super-resolution (SR) of SPC images. First, we introduce a model-based iterative optimization algorithm with deep regularizer to unify denoising and SR into one problem. Second, we construct a model-guided deep convolutional network by unfolding the aforementioned model-based iterative algorithm to achieve an optimal solution. All modules in the proposed network are interpretable due to the special model-guided design, and they enable good generalization in real situations. In addition, the deep regularizer and other parameters in the proposed network are jointly optimized in an end-to-end manner, which efficiently reduces the difficulty of parameter design. Extensive simulation and real experimental results are reported to demonstrate the superiority of the proposed method in terms of visual comparison and quantitative analysis, respectively.
An Empirical Study on Architecture and Efficiency of Dalvik VM and Android Runtime (ART)

Abstract: Many mobile platforms have developed as a result of the development of mobile technology. Rapid technological advancement has led to the widespread adoption of mobile devices with excellent graphics. Since its inception, the Open Handset Alliance project known as Android has undergone numerous revisions. Being centred on efficiency and pace, it's development. Android OS is driven by the Dalvik microkernel. The Android OS is sluggish due to the runtime as it is a virtual system. Android's multitasking capability leads to its latency. Earlier, there have been efforts to speed up Dalvik, but they were inefficacious. Increasing Android's speed and optimization was severely hampered by this. The Android Runtime (ART), which takes the role of the Dalvik Virtual Machine, made its debut when Android 4.4 was released by Google. A fast gadget was made possible by ART, which skillfully blends portability and performance, which eventually enhanced graphics optimization. A pre-compiled program was maintained for the Android applications by ART, which was not feasible with Dalvik Virtual machine. A speed of double has been observed on the Android Operating system, in several experiments. This paper discloses the architecture of android virtual machines (Dalvik and ART), memory optimization and efficiency of both in various devices. Also lists out the for and against of the latter one over the former and the basic functions of the runtimes
Grammatical Cohesion in SHS Students’ Research Introductions

Of the four language macro language skills, writing is considered the hardest to master (Berowa, 2017). For ESL (English as Second Language) users, writing needs a good command of the target language and strategic rhetorical techniques like the use of cohesive devices (Hyland, 2003). Using Halliday and Hasan’s (1976) cohesion taxonomy, 15 research introductions from Senior High School students were investigated using a mixed-method approach. This study identified the grammatical cohesive devices (GCDs) found in the research introductions its implications to the students’ challenges in establishing and maintaining cohesion in their writing. Results revealed that reference, conjunction, and substitution devices appeared in the analysis of the corpus, but reference devices comprised the majority of the GCDs. The excerpts taken from the corpus and the rigid content analysis found traces of overusing it by using certain devices repeatedly, misusing it because of the wrong application of certain cohesive devices, and underusing as when needed, these GCDs are not present in the sentence. This inappropriate use of devices can reduce the quality of students’ writing. Hence, further research is needed to identify the best teaching practices to improve students’ cohesion in writing Keywords: cohesion, grammatical cohesive devices, research introductions, writing, challenges