Reviewerly/exHarmony huggingface dataset:
Time Optimal Trajectory Planning of Elevating Fire Truck Based on Convex Optimization

Abstract：In order to improve the timeliness, reliability and security of elevating fire truck, a time optimal trajectory planning algorithm is proposed, considering the stability and non-impact of motions.Pseudo-displacement s is introduced, to fit discrete points of joints motion and construct continuous geometric path with B-spline.A convex optimization model is established, which is based on the continuous path, time optimal objective function that is formulated with s and its derivatives of time, as well as joint velocity and acceleration constraints.B-spline is utilized to parameterize trajectories with finite-dimensional vector x, and interior point method is used to solvethe convex optimization model, to get optimal trajectories of joints, while guaranteeing that velocities, accelerations and jerks are continuous.The proposed algorithm is simulated on a high elevating fire truck, and the results demonstrate that time optimal trajectory is obtained while the stability of motion is satisfied.
ELM-Based AFL–SLFN Modeling and Multiscale Model-Modification Strategy for Online Prediction

Online prediction of key parameters (e.g., process indices) is essential in many industrial processes because online measurement is not available. Data-based modeling is widely used for parameter prediction. However, model mismatch usually occurs owing to the variation of the feed properties, which changes the process dynamics. The current neural network online prediction models usually use fixed activation functions, and it is not easy to perform dynamic modification. Therefore, a few methods are proposed here. Firstly, an extreme learning machine (ELM)-based single-layer feedforward neural network with activation-function learning (AFL–SLFN) is proposed. The activation functions of the ELM are adjusted to enhance the ELM network structure and accuracy. Then, a hybrid model with adaptive weights is established by using the AFL–SLFN as a sub-model, which improves the prediction accuracy. To track the process dynamics and maintain the generalization ability of the model, a multiscale model-modification strategy is proposed. Here, small-, medium-, and large-scale modification is performed in accordance with the degree and the causes of the decrease in model accuracy. In the small-scale modification, an improved just-in-time local modeling method is used to update the parameters of the hybrid model. In the medium-scale modification, an improved elementary effect (EE)-based Morris pruning method is proposed for optimizing the sub-model structure. Remodeling is adopted in the large-scale modification. Finally, a simulation using industrial process data for tailings grade prediction in a flotation process reveals that the proposed method has better performance than some state-of-the-art methods. The proposed method can achieve rapid online training and allows optimization of the model parameters and structure for improving the model accuracy.
Mineralogy, alteration, and sulfur isotope geochemistry of the Zehabad intermediate-sulfidation epithermal deposit, NW Iran

The Zehabad Pb-Zn-Au-Ag (Cu) deposit lies in the Alborz magmatic arc of northwestern Iran. Ore-bearing breccia veins hosted by Eocene tuffs emplaced along the 80?130° trending fault and fracture zone. Mineralization occurs in the contact of the late Eocene igneous bodies and the Eocene volcanic and volcanosedimentary Karaj Formation. Mineralization formed in five stages: 1) disseminated framboidal pyrite and minor chalcopyrite and sphalerite; 2) quartz veins containing chalcopyrite, bornite, pyrite, and sphalerite; 3) deposition of specularite and gold grains hosted in quartz veins that crosscut chalcopyrite; 4) the main stage of mineralization that contains galena, sphalerite, tennantite-tetrahedrite, pyrite, sulfosalts, and gold; 5) barren quartz-calcite veins with sulfide mineral fragments of earlier stages. The hydrothermal alteration from closest to the veins outwards includes: a) silicification; b) phyllic with quartz, pyrite, sericite, and calcite; c) argillic with illite, kaolinite, and montmorillonite; d) propylitic containing epidote, calcite, chlorite, and sericite and; e) carbonatization that crosscuts all previous alteration types. Quartz and calcite are the most important gangue minerals at the deposit and show a close relationship with mineralization. Sulfur isotope compositions (0.8‰ to -10.1‰) suggest that the ore-forming fluids derived from magmatic sources with a temperature range of 276-288 °C. According to the field (macroscopic), microscopic, alteration, and sulfur isotope studies, the Zehabad base and precious metal mineralization is considered an intermediate-sulfidation epithermal deposit.
Intelligent Car Parking System Based on Blockchain Processing Reengineering

Due to guide the industries or enterprises leveraging new technologies and witnessing reengineering, we propose a scheme based on Business Process Reengineering and Blockchain Technology named Blockchain Process Reengineering (BCPR). Different from the technical push mechanisms that generally improve the development of blockchain, BCPR is a new solution from a business perspective that can address the pain points of industry. We aim to provide a detail theoretical method of BCPR and draw support from it to reengineer the parking industry. In contrast with the existing methods, it is proved that BCPR is a feasible solution to solve the problem of pain points in industry. It is also conducive to the development of the industry and blockchain technology with the realization of resource integration while taking into account the issue of trust.
The Use of Codenames Game to Help Students in Learning Vocabulary

English department students of IAIN Pekalongan have many shortcomings in memorizing vocabulary. This is evidenced by our observations when students are speaking in front of the class. Sometimes, students are confused about conveying information they want to deliver because they are constrained by a lack of memorization of vocabulary. The situation happens when students must use English in active discussions. So far, the students tend to memorize vocabulary. Besides that, vocabulary books are less effective and less interesting because it only relies on the use of language skills. One way to learn vocabulary in a simple way is through codenames game. This game provides many vocabularies that must be guessed by the players in a team. Then, another player should describe the word to be guessed. So, this research’s questions are how the codenames game is implemented due to learning English in a fun way. By reflecting the question, the purpose of this research is to provide information on the implementation of codenames game which helps English department students of IAIN Pekalongan enrich and build their vocabulary through a fun way using game cards. Based on our observation, the result showed that applying the codenames game could enrich the students’ vocabularies, be an alternative entertainer so that the students do not easily get bored, and strengthen the students’ memory. Thus, it can be concluded that playing codenames game promotes a helping way to enrich and build the students’ vocabulary.
A malicious URLs detection system using optimization and machine learning classifiers

&lt;span&gt;The openness of the World Wide Web (Web) has become more exposed to cyber-attacks. An attacker performs the cyber-attacks on Web using malware Uniform Resource Locators (URLs) since it widely used by internet users. Therefore, a significant approach is required to detect malicious URLs and identify their nature attack. This study aims to assess the efficiency of the machine learning approach to detect and identify malicious URLs. In this study, we applied features optimization approaches by using a bio-inspired algorithm for selecting significant URL features which able to detect malicious URLs applications. By using machine learning approach with static analysis technique is used for detecting malicious URLs applications. Based on this combination as well as significant features, this paper shows promising results with higher detection accuracy. The bio-inspired algorithm: particle swarm optimization (PSO) is used to optimized URLs features. In detecting malicious URLs, it shows that naïve Bayes and support vector machine (SVM) are able to achieve high detection accuracy with rate value of 99%, using URL as a feature.&lt;/span&gt;
Dependence Level and Quality of Life of Older Adults Living in Nursing Home

The older adults, in particular, care more about quality of life than longevity. Therefore, initiatives for the elderly should focus on increasing the quality of their life. Many factors affect the older adults' quality of life, but their dependence level is the most important. This study examined the effect of dependence level on quality of life for older adults living in nursing homes.
New classes of strictly optimal low hit zone frequency hopping sequence sets

<p style='text-indent:20px;'>Low hit zone frequency hopping sequences (LHZ FHSs) with favorable partial Hamming correlation properties are desirable in quasi-synchronous frequency hopping multiple-access systems. An LHZ FHS set is considered to be strictly optimal when it has optimal partial Hamming correlation for all correlation windows. In this study, an interleaved construction of new sets of strictly optimal LHZ FHSs is proposed. Strictly optimal LHZ FHS sets with new and flexible parameters are obtained by selecting suitable known optimal FHSs and appropriate shift sequences.
Correction to: Medical Image Watermarking in Transform Domain

In the original version of the book, the following belated correction has been incorporated: The affiliation of Ankur Rai has been changed from “Kamla Nehru Institute of Technology, Sultanpur 228118, India” to “Assistant Professor, Electronics and Communication Engineering, Invertis University, Bareilly 243123, Uttar Pradesh, India”. The erratum chapter and the book have been updated with the change.
Developing An Effective Model In Teaching Reading: What Would Work Best In A Large English Class?

&lt;p class="abstrak"&gt;This article discusses the preliminary process of developing a suitable model for teaching reading in large English classes. The large English classes that are referred in this piece of scientific writing is the English classes at Universitas Negeri Padang which consist up to fifty to sixty students. Not only it is large, but the students in the class also come from various study programs and different cultural background. The diversity of their background of knowledge and culture leads to possible problems regarding their study. The condition requires the lecturer to be able to apply an effective model in the teaching and learning process. The article focuses on the development of a reading model since enriching the students' abilities in reading is one of the objectives of the course. The development process includes the planning of the reading lesson, the learning process, and the evaluation. Various methods of teaching are applied to find the one that works best for the atmosphere of the large classes. However, it was found that none of the common teaching reading strategies used worked well in the large English class at Universitas Negeri Padang.&lt;em&gt;&lt;/em&gt;&lt;/p&gt;&lt;p class="abstrak"&gt; &lt;/p&gt;&lt;p class="abstrak"&gt;Artikel ini ditulis sebagai hasil penelitian pemula tentang usaha pengembangan model mengajar &lt;em&gt;reading&lt;/em&gt; di kelas bahasa Inggris berkapasitas besar. Kelas berkapasitas besar yang dimaksud dalam tulisan ilmiah adalah kelas bahasa Inggris mata kuliah umum di Universitas Negeri Padang yang terdiri dari lima puluh hingga enam puluh mahasiswa. Tidak hanya berkapasitas besar, tetapi mahasiswa dikelas ini berasal dari jurusan yang berbeda-beda. Perbedaan ini menyebabkan terjadinya beberapa masalah terkait proses belajar mengahar dikelas. Kondisi semacam ini mengharuskan dosen untuk mampu mengplikasikan model belajar mengajar yang efektif. Fokus dari tulisan ini adalah dasar pengembangan model mengajar &lt;em&gt;reading &lt;/em&gt;yang mampu membantu mahasiswa mencapai tujuan pembelajaran. Pengembangan yang dimaksud mencakup merencanakan pembelajaran, proses pembelajaran termasuk contoh strategi dan teknik yang mungkin dapat digunakan serta evaluasi. Akan tetapi, ditemukan bahwa hampir tidak ada dari satu strategi mengajar &lt;em&gt;reading&lt;/em&gt; yang umum digunakan mampu membantu mahasiswa dikelas-kelas berkapasitas besar ini untuk mencapai tujuan pembelajaran yang diharapkan.&lt;/p&gt;
Resolving Pronouns for a Resource-Poor Language, Malayalam Using Resource-Rich Language, Tamil

In this paper we give in detail how a resource rich language can be used for resolving pronouns for a less resource language.The source language, which is resource rich language in this study, is Tamil and the resource poor language is Malayalam, both belonging to the same language family, Dravidian.The Pronominal resolution developed for Tamil uses CRFs.Our approach is to leverage the Tamil language model to test Malayalam data and the processing required for Malayalam data is detailed.The similarity at the syntactic level between the languages is exploited in identifying the features for developing the Tamil language model.The word form or the lexical item is not considered as a feature for training the CRFs.Evaluation on Malayalam Wikipedia data shows that our approach is correct and the results, though not as good as Tamil, but comparable.
PENGARUH PENGGUNAAN MEDIA PEMBELAJARAN BERBASIS ICT DAN GAYA BELAJAR TERHADAP HASIL BELAJAR IPA DAN KETERAMPILAN BERTANYA SISWA SD NEGERI 060798 MEDAN AREA

This research aims to find out: (1) Differences in student learning outcomes taught using Camtasia media with conventional media; (2) Differences in student learning outcomes that have visual, auditory and kinesthetic learning styles taught by Camtasia media; and (3) Differences in student learning outcomes that have visual, auditory and kinesthetic learning styles that are learned with conventional media. The population in this study was grade V students of SD Negeri 060798 Medan Area, amounting to 82 students consisting of 3 classes. While the study sample is all 3 classes. The research instrument was in the form of a science learning outcomes test, and a learning style questionnaire. This research method is quasi-experimental hypothesis analysis technique t test; and analysis of variance. The results showed that: (1) Student learning outcomes taught with Media Camtasia 85.26 ± 5.45 (± SD) were higher than learning with conventional media 75.52 ± 5.86 (tcount = 8.147; p = 0.000); (2) There are differences in student learning outcomes that have visual, auditory and kinesthetic learning styles that are learned with Media Camtasia (Fcount = 24,964; p = 0,000); (5) there are differences in student learning outcomes that have visual, auditory and kinesthetic learning styles that are learned with Conventional media (Fcount = 6.770; p = 0.002).
Analytic quantum weak coin flipping protocols with arbitrarily small bias

Weak coin flipping (WCF) is a fundamental cryptographic primitive for two-party secure computation, where two distrustful parties need to remotely establish a shared random bit whilst having opposite preferred outcomes. It is the strongest known primitive with arbitrarily close to perfect security quantumly while classically, its security is completely compromised (unless one makes further assumptions, such as computational hardness). A WCF protocol is said to have bias ∊ if neither party can force their preferred outcome with probability greater than 1/2 + ∊. Classical WCF protocols are shown to have bias 1/2, i.e., a cheating party can always force their preferred outcome. On the other hand, there exist quantum WCF protocols with arbitrarily small bias, as Mochon showed in his seminal work in 2007 [arXiv:0711.4114]. In particular, he proved the existence of a family of WCF protocols approaching bias ∊(k) = 1/(4k +2) for arbitrarily large k and proposed a protocol with bias 1/6. Last year, Arora, Roland and Weis presented a protocol with bias 1/10 and to go below this bias, they designed an algorithm that numerically constructs unitary matrices corresponding to WCF protocols with arbitrarily small bias [STOC'19, p. 205–216]. In this work, we present new techniques which yield a fully analytical construction of WCF protocols with bias arbitrarily close to zero, thus achieving a solution that has been missing for more than a decade. Furthermore, our new techniques lead to a simplified proof of existence of WCF protocols by circumventing the non-constructive part of Mochon's proof. As an example, we illustrate the construction of a WCF protocol with bias 1/14.
Analys is and Creation of Free Sentiment Analysis Programs

This paper analyzes free online programs for sentiment analysis which can, on the bases of their algorithm, give a positive, negative or neutral opinion of a text. At the beginning of the paper sentiment analysis programs and techniques they use such as Naive Bayes and Recurrent Neural Networks are presented. The programs are divided into two categories for analysis. The fi rst category consists of sentiment analysis programs which analyze texts written or copied inside the user interface. The second category consists of programs for analyzing opinions posted on social networks, blogs, and other media sites. Programs from both categories were chosen for this research on the bases of positive reviews on computer science portals and their popularity on web search engin es such as Google and Bing. The accuracy of the programs from the fi rst category was checked by inserting the same sentence from movie reviews and comparing the results. Their additional options have also been analyzed. For the second category of programs, it was determined which social networks, blogs, and other social media they cover on the internet. The purpose of this analysis was to check the overall quality and options that free sentiment analysis programs provide. An example of how to create one’s own custom sentiment analyzer by using the available Python code and libraries found online is also given. Two simple programs were created using Python. The fi rst program belongs to the fi rst category of programs for analyzing an input text. This program serves as a pilot program for Croatian which gives only the basic analysis of sentences. The second program collects recent tweets from Twitter containing certain words and creates a pie chart based on the analysis of the results.
Efficient 3D Depthwise and Separable Convolutions with Dilation for Brain Tumor Segmentation

In this paper, we propose a 3D convolutional neural network targeting at the segmentation of brain tumor. There are different types of brain tumors and our focus is one common type named glioma. The proposed network is efficient and balances the tradeoff between the number of parameters and accuracy of segmentation. It consists of Anisotropic Block, Dilated Parallel Residual Block, and Feature Refinement Module. The Anisotropic Block applies anisotropic convolutional kernels on different branches. In addition, the Dilated Parallel Residual Block incorporates 3D depthwise and separable convolutions to reduce the amount of required parameters dramatically, while multiscale dilated convolutions enlarge the receptive field. The Feature Refinement Module prevents global contextual information loss. Our method is evaluated on the BRATS 2017 dataset. The results show that our method achieved competitive performance among all compared methods, with a reduced number of parameters. The ablation study also proves that each individual block or module is effective.
Implementing a Cloud Based Method for Protected Clinical Trial Data Sharing

Clinical trials generate a large amount of data that have been underutilized due to obstacles that prevent data sharing including risking patient privacy, data misrepresentation, and invalid secondary analyses. In order to address these obstacles, we developed a novel data sharing method which ensures patient privacy while also protecting the interests of clinical trial investigators. Our flexible and robust approach involves two components: (1) an advanced cloud-based querying language that allows users to test hypotheses without direct access to the real clinical trial data and (2) corresponding synthetic data for the query of interest that allows for exploratory research and model development. Both components can be modified by the clinical trial investigator depending on factors such as the type of trial or number of patients enrolled. To test the effectiveness of our system, we first implement a simple and robust permutation based synthetic data generator. We then use the synthetic data generator coupled with our querying language to identify significant relationships among variables in a realistic clinical trial dataset.
Approaches to solving the problem of search of scenarios of lessons on informatics for basic school in the Moscow E-School library

Problem and goal. The article deals with the problem of search of scenarios of lessons on informatics for basic school in the Moscow E-School (MESH) Library. The goal is to identify the features of the MESH search engine and possible approaches to improving the process of scenarios of informatics lessons for basic school. Methodology. In the process of research was used a set of methods: analysis of the resources of the MESH library and normative documents; reﬂection of the content of knowledge obtained; searching for approaches to improving the process of ﬁnding scenarios of informatics lessons for basic schools in the MESH library; local pedagogical experiment. Results. Revealed the diﬀerence of the classiﬁcation of sections and themes of the school informatics course provided by the Approximate Basic Educational Program [16] (in accordance with General Educational Standards [20]) and the MESH library classiﬁcation [3], as well as the presence of a large number of controlled elements of MESH library content, indicated by the creators of the scenarios of lessons on informatics for basic school, what determines the problem of ﬁnding the right resources. The results of the study allowed to ﬁnd approaches to solving the identiﬁed problem. Conclusion. The approaches to solving the identiﬁed problem of search of scenarios of lessons on informatics for basic school in the MESH library are proposed, their implementation can have a positive impact on the ability to ﬁnd the necessary digital resource and, as a result, increase the eﬀectiveness of professional activity of basic school informatics teacher.