Reviewerly/exHarmony huggingface dataset:
A Computational Account of Tone Sandhi Interaction

This paper presents a computational account of three tone sandhi rules in Tianjin Chinese that have received a lot of attention in the literature due to the seemingly complex way in which they interact. Two of the rules apply right-to-left while the third applies left-to-right, making it difficult for both rule- and constraint-based formalisms to account for the interaction in a unified way. In the computational framework advocated for in this paper, the apparent difference in directionality of the three rules amounts to a subtle difference in computational classification: the left-to-right rule has the property of input strict locality (ISL) while the right-to-left rules share the property of output strict locality (OSL). However, the fact that the direction of rules with the ISL property doesn’t actually matter, a unified account becomes possible in that all three rules can be modeled as a single input-output strictly local function.
Strategi Tua Tuo Untuk Meningkatkan Ketrampilan Berbicara (Tembang Macapat)

This article was to increase the students speaking skills on the course material (Tembang Macapat) through Tua Tuo Strategy. The research subject was 27 students of PGMI STAINU Temanggung. The researcher used Participation Action Research to anayze their aspects of speaking skill on the course material (Tembang Macapat) through Tua Tuo Strategy. The result showed that Tua Tuo strategy was effectively to increase the students’ completeness and the aspects of speaking skill (Tembang Macapat) of students’ PGMI of STAINU Temanggung.&#x0D; Key words: Tua Tuo Strategy, Speaking Skill in Tembang Macapat, Course Material Tembang Macapat
Guest Editors Introduction: Special Section on Emerging Technologies in Computer Design

The papers in this special section were presented at the IEEE International Conference on Computer Design (ICCD).
A SYNTHETIC 3D SCENE FOR THE VALIDATION OF PHOTOGRAMMETRIC ALGORITHMS

Abstract. This paper describes the construction and composition of a synthetic test world for the validation of photogrammetric algorithms. Since its 3D objects are entirely generated by software, the geometric accuracy of the scene does not suffer from measurement errors which existing real-world ground truth is inherently afflicted with. The resulting data set covers an area of 13188 by 6144 length units and exposes positional residuals as small as the machine epsilon of the double-precision floating point numbers used exclusively for the coordinates. It is colored with high-resolution textures to accommodate the simulation of virtual flight campaigns with large optical sensors and laser scanners in both aerial and close-range scenarios. To specifically support the derivation of image samples and point clouds, the synthetic scene gets stored in the human-readable Alias/Wavefront OBJ and POV-Ray data formats. While conventional rasterization remains possible, using the open-source ray tracer as a render tool facilitates the creation of ideal pinhole bitmaps, consistent digital surface models (DSMs), true ortho-mosaics (TOMs) and orientation metadata without programming knowledge. To demonstrate the application of the constructed 3D scene, example validation recipes are discussed in detail for a state-of-the-art implementation of semi-global matching and a perspective-correct multi-source texture mapper. For the latter, beyond the visual assessment, a statistical evaluation of the achieved texture quality is given.
Biometric data security using joint encryption and watermarking

Confidentiality and content ownership are considered to be an important aspect of security applications and therefore a joint watermarking and encryption scheme is developed. This work addresses the issue of authenticity and integrity of watermark or ownership identification by embedding biometric iris template as a watermark in a fingerprint host image. The proposed approach is a two-step approach which includes encryption and watermarking. During the encryption, iris features are encrypted using combination of FRWT with Arnold cat map while watermark embedding is done by using dual DWT-SVD scheme to improve robustness and protection of biometric security systems. Experimental results demonstrate that the proposed joint encryption and watermarking introduces efficiency, security and robustness against image processing attacks.
E-LEARNING EQUIPMENT IN LEARNING PROCESSAT VOCATIONAL HIGH SCHOOL

&lt;p&gt;&lt;em&gt;The problem in the world of education at this time is the quality and quantity of education in the field of information and communication technology. The quality of education can be seen from the quality of education desired by the community and for the quality of education related to the equitable access to education without any gap. One way to overcome these problems is by optimizing the role of information and communication technology in the learning process by using e-learning. E-learning used is using online learning based on Schoology. In this application there are several features that can be used by the teacher in the learning process including uploading material, assignments, discussions and giving test questions using the online quiz system. In the use of E-Learning in the learning process can increase students' learning motivation and can create enjoyable learning so that students in participating in learning activities can be active and achieve maximum learning outcomes.&lt;/em&gt;&lt;/p&gt;
Mining Students Outcomes: An Empirical Study

The purpose of the research presented in this paper is to extract students' individualized learning achievements from course information and assessments results for student groups and predict expected performance in future courses based on existing achievements in a set of student outcomes at the program level.Data mining techniques are used to process course information and extract students' achievements in a set of student outcomes.Two prediction algorithms namely single linear regression and multiple linear regression are applied to determine students' expected performance in future courses.Specialized programs have been designed, implemented and processed in stages to achieve the results as described in this paper.The results show that by using data mining techniques individualized students' performance information can successfully be extracted to provide formative feedback.This information is further processed by applying prediction algorithms to determine expected students' performance in future courses depending on the available historical records for courses.
Model Matematika Penyakti Diabetes Melitus

Diabetes mellitus (DM) or often known as diabetes mellitus, is a disease that can be caused by heredity, one of the factors caused by patterns of human life patterns. In the paper a model and mathematical analysis of DM disease are introduced. To simplify the analysis, the Runge Kutta method was used to complete the model. Based on the results of the analysis, it is known that the population of patients with DM disease tends to increase for a long period of time.
Output-Sensitive Information Flow Analysis

Constant-time programming is a countermeasure to prevent cache based attacks where programs should not perform memory accesses that depend on secrets. In some cases this policy can be safely relaxed if one can prove that the program does not leak more information than the public outputs of the computation. We propose a novel approach for verifying constant-time programming based on a new information flow property, called output-sensitive noninterference. Noninterference states that a public observer cannot learn anything about the private data. Since real systems need to intentionally declassify some information, this property is too strong in practice. In order to take into account public outputs we proceed as follows: instead of using complex explicit declassification policies, we partition variables in three sets: input, output and leakage variables. Then, we propose a typing system to statically check that leakage variables do not leak more information about the secret inputs than the public normal output. The novelty of our approach is that we track the dependence of leakage variables with respect not only to the initial values of input variables (as in classical approaches for noninterference), but taking also into account the final values of output variables. We adapted this approach to LLVM IR and we developed a prototype to verify LLVM implementations.
A new Leach protocol based on ICH-Leach for adaptive image transferring using DWT

Nowadays, the rapid development and the miniaturization of CMOS image sensors in the last years allowed the creation of WMSN (Wireless Multimedia Sensor Network). Therefore, transferring images through the network becomes an important field of research. The main goal is to transmit the data from a sensor node to another to reach finally the Sink node. Thus, routing protocols play an important role in managing and optimizing the node's resources particularly the energy consumption. Therefore, some routing protocols are known by their ability to save energy and extend the lifetime of the network such as Leach protocol and derived variants. However, multimedia content transferring was not a priority for these protocols. In this paper, the main idea is to adapt ICH-Leach [1], for image transferring. This protocol was tested in a previous work and has given good performances against Leach [2], balanced Leach [3] and MLD-Leach [4]. In fact, the Haar wavelet transform is used, in the application layer, to extract the resolution level to be used in image transmission, depending on the rate flow between the sensor node and the sink node. This paper provides statistics concerning the lifetime of the network, the energy consumption and statistics related to receive images using the peak signal-to-noise ratio (PSNR). The Castalia framework is used for simulation, obtained results show the efficiency of the proposed approach by network lifetime extending and more images transmitting with better quality compared to other protocols.
LEVANTAMENTOS DA VARIAÇÃO LINGUÍSTICA EM TRÊS DOMÍNIOS DO COMPLEXO DIALETAL APURINÃ (ARÚAK)

This work aims to present a survey of the most representative types of linguistic variation attested in the Apurinã language (Arawák) in three domains of the language: phonology, morphology and lexicon. We will discuss the linguistic processes involved in the variation, the direction of the changes and some extralinguistic correlators. We will show that the vowel variations involve vowel raising or vowel syncope, that the consonantal variation involves the glottal fricative deletion and the liquid consonants alternatios, that the morphological variation consists mainly of morphemes with semantically redundant meanings, and that the cases of lexical variation are motivated by a network of semantic relations built from a sociocultural and cognitive system that underlies the phenomenon of the "double vocabulary" in Apurinã.
Reference Management Tools: EndNote, Mendeley, RefWorks and Zotero

Referencing provides information about resources used in research work by researcher. A reference manager supports researchers in performing three basic research steps: searching, storing and writing. Plagiarism is a term that describes the unacknowledged use of someone’s work. Plagiarism is a very serious academic offence. References given as per standard reference style manual avoid plagiarism. The online reference management tools helps the researchers to import and export citations, organize citations, and produce the citations in a variety of reference management style manuals or formats. This paper describes four popular online reference management tools viz. EndNote, Mendeley, Refworks and Zotero. Keywords: Reference Management Tools, EndNote, Mendeley, RefWorks, Zotero Cite this Article V. P. Yadav. Reference Management Tools: EndNote, Mendeley, RefWorks and Zotero. Journal of Advancements in Library Sciences . 2019; 6(Special Issue 1): 315s–319s.
The Case for Physical Memory Pools: A Vision Paper

The cloud is a rapidly expanding and increasingly prominent component of modern computing. Monolithic servers limit the flexibility of cloud-based systems, however, due to static memory limitations. Developments in OS design, distributed memory systems, and address translation have been crucial in aiding the progress of the cloud. In this paper, we discuss recent developments in virtualization, OS design and distributed memory structures with regards to their current impact and relevance to future work on eliminating memory limits in cloud computing. We argue that creating physical memory pools is essential for cheaper and more efficient cloud computing infrastructures, and we identify research challenges to implement these structures.
Placement of M-Sequences over the Field &amp;lt;i&amp;gt;Fp&amp;lt;/i&amp;gt; in the Space &amp;lt;i&amp;gt;R&amp;lt;sup&amp;gt;n&amp;lt;/sup&amp;gt;&amp;lt;/i&amp;gt;

Spread spectrum communication systems are widely used today in a variety of applications for different purposes such as access of same radio spectrum by multiple users (multiple access), anti-jamming capability (so that signal transmission cannot be interrupted or blocked by spurious transmission from enemy), interference rejection, secure communications, multipath protection, etc.Several spreading codes are popular for use in practical spread spectrum systems.one of these important codes is Maximal Sequence (M-sequence) length codes, These are the longest codes that can be generated by a shift register of a specific length, The number of 1-s in the complete sequence and the number of 0-s will differ by one, Further, the autocorrelation of an m-sequence is -1, another interesting property of an M-sequence is that the sequence, when added (modulo-2) with a cyclically shifted version of itself, results in another shifted version of the original sequence.Hence, the M-sequences are also known as, pseudo-noise or PN sequences.Current article study placement M-Sequences over the finite field Fp or Mp-Sequences (where p is a prime number) in the space R n , these sequences can be generated as a closed set under the addition.These sequences form additive groups with the corresponding null sequence that was generated by the feedback shift registers.Such Mp-Sequences see a great application in the forward links of communication channels.Furthermore, they form coders and decoders that combine the information by p during the connection process with the backward links of these channels.These sequences scrutinize the transmitted information to enable it to reach the receivers in an accurate form.This study has defined eminent surfaces in the vector space 'R' having dimensions of 'n' as quadratic forms, spheres, and planes that contain these sequences.
Javanese Document Image Recognition Using Multiclass Support Vector Machine

Some ancient documents in Indonesia are written in the Javanese script. Those documents contain the knowledge of history and culture of Indonesia, especially about Java. However, only a few people understand the Javanese script. Thus, the automation system is needed to translate the document written in the Javanese script. In this study, the researchers use the classification method to recognize the Javanese script written in the document. The method used is the Multiclass Support Vector Machine (SVM) using One Against One (OAO) strategy. The researchers use seven variations of Javanese script from the different document for this study. There are 31 classes and 182 data for training and testing data. The result shows good performance in the evaluation. The recognition system successfully resolves the problem of color variation from the dataset. The accuracy of the study is 81.3%.
K-way Fast Approximate Spectral Clustering

In recent years, k-way spectral clustering is one of the most popular clustering algorithms. Due to its computational complexity of O(n <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> ), with n the number of data points it is a challenging task to apply traditional spectral clustering algorithms for large-scale data sets. In this paper, we propose a novel algorithm called k-way Fast Spectral Clustering (KFSC) based on kd-tree. This algorithm is based on a theoretical analysis that provides a statistical characterization of the effect of local distortion on the mis-clustering rate. The computational complexity is O(ndl) + O(m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> ) + O(m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ), where l is the depth of kd-tree, m is the number of representative sets (set of similar data points) and d is the dimension of data. Extensive experimental results on real data sets and synthetic data sets demonstrate that the proposed methodology outperforms Normalized cut (Ncut) in terms of computation, while achieving comparable clustering accuracy.
A Mobile-Assisted Learning Application of Mother Tongue for Grade 3

Department of Education, Philippines stated that starting school year (SY 2012-2013) the Mother Tongue-Based-Multilingual Education (MTB-MLE) must be implemented in public schools especially in Kindergarten, Grades 1, 2 and 3 as the part of K-12 Basic Education Program.In this generation, mobile application is rapidly growing in importance and can be used in different purposes and it is widely used in education.Students are more driven towards using mobile application for various purpose.Every mobile application has a unique feature which offers its own set of services.This study proposes A Mobile-Assisted Learning Application of Mother Tongue for Grade 3.This mobile application adopted the content of the mother tongue books and curriculum guide in 3rd grading period that will act as supplement material in Bolosan-Caingal Elementary School for Grade 3. It is interactive and has a feature such as dictionary, flashcards, lesson and quiz.This feature will help the pupils to widen their vocabulary in mother tongue, and enhance their skills in pronouncing pangasinense term.Thus, it also has a quiz to test their knowledge.This mobile application is an android based.
Effective detection of strong maneuvers of object in noisy measurements conditions.

In this paper coordinate measurements of the object, which trajectory includes strong maneuvers, are used as input data.Strong maneuvers described here as fast turns of the object in sharp angles.Measurement data are very noisy, and standard filtration methods (Kalman filter) don't give satisfactory results.In this paper an improved filtration method that is capable to detect strong maneuvers effectively was implemented.The filtration algorithm was applied to multirotor UAV's tracking task.
Elastic Regression-Tree Learning in a Heterogeneous Computing Environment

Embedded intelligence demands sensor functions with minimal operator interference. While computing resources in close proximity to a device are sometimes limited, more capable computing units suffer from latency in long-range data transmission. Here, we demonstrate a workflow on optimizing sensor performance for individual samples, in which we utilize an elastic regression-tree method to distribute computing tasks between an embedded chipset and a full-fledged workstation. A reconciliation of computing resources of different nature enables an efficient data acquisition in a completely automated manner, crucial to the deployment of edge intelligence in a broad context.
Simulation of the influence of imperfections on dynamical decoupling of a superconducting qubit*

Dynamical decoupling is widely used in many quantum computing systems to combat decoherence. In a practical superconducting quantum system, imperfections can plague decoupling performance. In this work, imperfections in a superconducting qubit and its control system are modeled via modified Hamiltonian and collapse operator. A master equation simulation is carried out on the qubit under 1/ f environment noise spectrum. The average dephasing rate of qubit is extracted to characterize the impact of different imperfections on the decoupling from dephasing. We find that the precision of pulse position, on–off ratio, and filtering effect are most critical. Bounded pulses have weaker impact, while variation in pulse width and qubit relaxation are insignificant. Consequently, alternative decoupling protocols, jitter mitigation, cascaded mixers, and pulse shaping can be conducive to the performance of decoupling. This work may assist the analysis and optimization of dynamical decoupling on noisy superconducting quantum systems.
The Implementation of The Neuro Fuzzy Method Using Information Gain for Improving Accuracy in Determination of Landslide Prone Areas

The accuracy of information is increasing rapidly as technological development. For the example, the information in determination of disaster severity. The disasters that can be determined is landslide. This determination can be conducted using the fuzzy method. One of method is neuro fuzzy. Neuro fuzzy is a combined method of two systems, fuzzy logic and artificial neural network. The accuracy of neuro fuzzy method can be increased by applying the information gain. The purpose of this study is to implement and to know the accuracy of the implementation of information gain as the selection of landslide data features. It conducted to the neuro fuzzy method in determining landslide prone areas. The distribution of training data and testing data was using 20 k-fold cross validation. The implementation of the neuro fuzzy method on landslide data was obtained an accuracy of 81.9231%. In the implementation of the neuro fuzzy method with information gain was conducted in classification process. The process will stop when the accuracy has decreased. The highest accuracy result was obtained of 88.489% by removing an attribute. So, it can be concluded the accuracy increase of 6.5659% in the implementation of the neuro fuzzy method and information gain in determination of landslide prone areas.
Understanding the Benefits and Drawbacks of Shape Change in Contrast or Addition to other Modalities

Shape changing interfaces enable exciting new ways to interact with devices, to communicate information, meaning and affect, and provide dynamic affordance. Such interfaces are often complex and more expensive to fabricate compared to tangible, screen-based and voice interfaces. The research field has yet to explore the advantages and drawbacks of shape change in contrast to other modalities. The research outlined in this paper aims to evaluate shape changing interfaces for different purposes in contrast to interfaces that rely on tangible, screen-based or voice interaction. Shape change will be explored in the context of explainable AI to examine how it affects aspects like usability, user experience, user engagement and trust. The aim of this research is to generate an understanding about the conditions under which shape changing interfaces are beneficial and when traditional or multimodal interfaces are more appropriate.
Dataset Characteristics Identification for Federated SPARQL Query

Nowadays, the amount of data published in the RDF format is increasing. Federated SPARQL query engines that can query from multiple distributed SPARQL endpoints have been developed recently. A federated query engine usually has different performance compared to the others. One of the factors that affect the performance of the query engine is the characteristic of the accessed RDF dataset, such as the number of triples, the number of classes, the number of properties, the number of subjects, the number of entities, the number of objects, and the spreading factor of a dataset. The aim of this work is to identify the characteristic of RDF dataset and create a query set for evaluating a federated engine. The study was conducted by identifying 16 datasets that used by ten research papers in Linked Data area.