Reviewerly/exHarmony huggingface dataset:
IDENTIFIKASI JENIS CACING SOIL TRANSMITTED HELMINTH (STH) PADA FESES PEKERJA PENGANGKUT SAMPAH KOTA KENDARI DENGAN METODE MODIFIKASI HARADA MORI DAN METODE MODIFIKASI KATO KATZ

Background: helminthiasis is classified as negleted disease, which is an infection that is not considered and is chronic without causing clear clinical symptoms and its effects can only be seen in the long term. Objective: to identify the types of worms in the feces of Kendari garbage transportation workers. Methods: uses laboratory observation methods to identify the type of Soil that is Contagious. Using 42 stool samples that have been stored for ± 2 months were taken from the stools of Kendari municipal waste workers and examined using the modified kato-katz, Harada Mori and Direct slide methods. Results: the results of various inspection methods namely, direct slide, Kato-katz modification and Harada Mori modification. Identification of the egg stage, the p-value is 0.002 &lt;α = 0.05. This shows that the Kato-katz method is far better than the direct shear method in the examination of STH worm eggs. The p-value results in the examination of Harada mori larvae and the direct shear value were 0.001 &lt;α = 0.05. This shows that the Harada mori method is better at identifying fecal larvae than the direct glide method. The Kato-Katz modification method is more effective in identifying the type of worm egg than the direct slide method. The most common type of Transmitted Helminth earthworm identified in this study is hookworm. Conclusion: The Kato Katz method is a better method used than the direct slide method in identifying the type of Soil transmitted Helminth (STH) in the egg phase. Harada mori is a better method used than the direct slide method in identifying the type of Soil transmitted Helminth (STH) worm in the larval phase. The type of STH worm most identified in this study is the hookworm.
Generating Trees for Comparison

Tree comparisons are used in various areas with various statistical or dissimilarity measures. Given that data in various domains are diverse, and a particular comparison approach could be more appropriate for specific applications, there is a need to evaluate different comparison approaches. As gathering real data is often an extensive task, using generated trees provides a faster evaluation of the proposed solutions. This paper presents three algorithms for generating random trees: parametrized by tree size, shape based on the node distribution and the amount of difference between generated trees. The motivation for the algorithms came from unordered trees that are created from class hierarchies in object-oriented programs. The presented algorithms are evaluated by statistical and dissimilarity measures to observe stability, behavior, and impact on node distribution. The results in the case of dissimilarity measures evaluation show that the algorithms are suitable for tree comparison.
Vaccini obbligatori e ruolo del diritto. Un tentativo di (ri)composizione della materia partendo dalla più recente giurisprudenza costituzionale

Science-based laws are more and more common, due to the scientific and technical progress. This phenomenon imposes to (re)think the role of the legislator as well as the judge. The law establishing mandatory vaccinations is one example of this complex debate: starting from the important decision n. 5/2018 of the Constitutional Court, this paper aims at analyzing the different and challenging issues connected to the regulation of mandatory vaccinations, concerning the balance between individual and collective dimension of the right to health, the competence of Regions but also the importance of science-based data in the legislative and judicial process.
A Methodology in the implementation of International Standards in Software Development Centers in Universities

The importance of software development in organizations, especially in small and medium-sized enterprises (SMEs) and in very small entities (Very Small Entities, VSE), has grown, as well as the need to improve their software development process to develop quality products and services. Therefore, providing qualified professionals that meet this need and strengthen the software industry represents a main challenge for universities. To achieve this, the present paper presents a methodology in the implementation of the standard ISO / IEC 29110 basic profile in Software Development Centers at the universities, in order to achieve the certification in this standard and to provide professionals with the knowledge and abilities regarding the use of software engineering best practices, expected in SME and VSE using ISO/IEC 29110.
Generating Tuples of Integers Modulo n

In this paper, p 2 Z Z p p + - @ for n ≥ 3, where p=2n-1 and Zp-1 p =e (e is the multiplicative identity). The diagonal elements of Z+ 2n+1 can generate Z2k-2 2n-1; k=2, 3,… n-1 by simple algorithm.
Level Set Segmentation Algorithm for Cyst Images with Intensity Inhomogeneity

A new improved Chan-Vese model is given. We introduce local grayscale information to ensure better localization effect and extract target edge. Compared with the typical active contour models, the improved model can better segment cyst image with intensity inhomogeneity, the Dice Similarity Coefficient (DSC) values are higher than 0.9.
FAKTOR-FAKTOR YANG MEMPENGARUHI PELAKSANAAN KEBIJAKAN AKSES TERBUKA REPOSITORI DIGITAL SEBAGAI UPAYA KETERBUKAAN INFORMASI DALAM EKOSISTEM DIGITAL PERPUSTAKAAN PERGURUAN TINGGI NEGERI SE JAWATENGAH

The aim of the study is viewing the policy making, related to supporting ofthe existence of digital ecosystems in the use of repositories while protecting intellectual property rights. The sample taken was State University Library (PTN) in Central Java. The research method used is descriptive qualitative. Retrieval of the data was taken by questionnaires that distributed to all PTN libraries in Central Java and study documents that support the research. Results of the study indicate that all PTN libraries in Central Java have used a repository. Meanwhile the average software that used by the librarywere E-prints, with the rest of its using Slims (Senayan Library Information Management System) and a software that they make their own for library applications. The contentsin the repository are scientific academic papers such as Final Project Report(TA), Thesis, dissertation, journals, and scientific magazines. The access policy applied by the informant wereopen access, partial and close access policy. The legal formalthatused in implementing the repository access policy at the institutions is by issuing a Rector's Decree (SK), Standard Operating Procedure (SOP), and university policies. While the head library role’s in implementing the repository is become a facilitator in compilingthe legal formal and repository content access policy.
LIE IN MARK HADDON’S NOVEL THE CURIOUS INCIDENT OF THE DOG IN THE NIGHT-TIME

This research aims to analyze lie and types of lie in Mark Haddon’s novel entitled The Curious Incident of The Dog in the Night-Time. The fifteen-year-old narrator of the story, Christopher John Francis Boone discovers the slain body of his neighbor’s Poodle Wellington, on the neighbor front lawn, one evening and sets out to uncover the murderer. His investigation is at times aided, and at other times hampered, by the mild form of Autism he lives with. Christopher has a certain character. He finds difficulty in his social interaction; be it in his appearance, language attitude, or thinking. In addition, Christopher has an intelligent ability. He is able to interpret objects around him well. The novel ends with Christopher planning to take A-level exams in physics and further math, and then attend a university in another town. The method of the data analysis in this research uses descriptive qualitative method, and the theory applied in this research was following Bryant (2008) who divided lie into 3 types, i.e. real lies, white lies, and gray lies. The research result shows that all the three types of lie proposed by Bryant are vividly reflected by Christopher in the novel.
Discussion on “Horseshoe‐based Bayesian nonparametric estimation of effective population size trajectories” by James R. Faulkner, Andrew F. Magee, Beth Shapiro, and Vladimir N. Minin

BiometricsVolume 76, Issue 3 p. 691-694 DISCUSION Discussion on “Horseshoe-based Bayesian nonparametric estimation of effective population size trajectories” by James R. Faulkner, Andrew F. Magee, Beth Shapiro, and Vladimir N. Minin Lorenzo Cappello, Lorenzo Cappello orcid.org/0000-0001-6682-908X Department of Statistics, Stanford University, Stanford, CaliforniaSearch for more papers by this authorSwarnadip Ghosh, Swarnadip Ghosh Department of Statistics, Stanford University, Stanford, CaliforniaSearch for more papers by this authorJulia A. Palacios, Corresponding Author Julia A. Palacios juliapr@stanford.edu orcid.org/0000-0003-4501-7378 Department of Statistics, Stanford University, Stanford, California Correspondence Julia A. Palacios, Department of Statistics, Stanford University, Stanford, CA 94305. Email: juliapr@stanford.eduSearch for more papers by this author Lorenzo Cappello, Lorenzo Cappello orcid.org/0000-0001-6682-908X Department of Statistics, Stanford University, Stanford, CaliforniaSearch for more papers by this authorSwarnadip Ghosh, Swarnadip Ghosh Department of Statistics, Stanford University, Stanford, CaliforniaSearch for more papers by this authorJulia A. Palacios, Corresponding Author Julia A. Palacios juliapr@stanford.edu orcid.org/0000-0003-4501-7378 Department of Statistics, Stanford University, Stanford, California Correspondence Julia A. Palacios, Department of Statistics, Stanford University, Stanford, CA 94305. Email: juliapr@stanford.eduSearch for more papers by this author First published: 07 May 2020 https://doi.org/10.1111/biom.13275Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Volume76, Issue3September 2020Pages 691-694 RelatedInformation
Responsive infrastructure with cybersecurity for automated high availability DevSecOps processes

Nowadays the importance of the DevSecOps (Developer Security Operations) term has been increasing all over the world, and Mexico is not the exception. This article describes the implementation of responsive-infrastructure strategies with cybersecurity and risk management, as part of the operation of a Data Center in a Government Organization in Mexico. The strategies aim to establish a high availability scenario for automated processes in controlled scenarios, with fault tolerance during their operation, which uses information technologies based on containers and microservices and allowing automated scalability for high availability service levels.
Lightweight and efficient approach for multi-secret steganography

This paper compares an efficiency of two approaches of multi-secret steganography in lightweight systems: interlacing and multi-level. The study was conducted for two and three secrets with use of F5 algorithm for both approaches. The embedding times were measured with and without I/O operations. At the end the application of these techniques in lightweight solutions is discussed.
EFFECT OF BANDELITATION OF IMMAGES ON COMPRESSION BY ALGORITHM SPECK

The bandelets representation (the bandelitation) effectively gives the contours of the images thanks to the orthogonal bases of bandelets as well as the zones of homogeneous regularity in the form of a residue decomposed in wavelets. The orthonormal framework makes it possible to obtain theoretical results on the approximation capabilities of this representation showing their interest with respect to the two-dimensional separable wavelet bases. However, it remains to confirm these elements by numerical results of compression.We propose in this work a new approach based on the bandelitation effect on the SPECK algorithm Set Partionning Embedded bloCK. The proposed approach manipulates the coefficients less because it is characterized by additional decorrelations in the exploitation of the geometry of the image.
Approaching Obstacle Detection by a Vehicle Fisheye Camera

The fisheye camera can get rich information, and the fisheye camera has a lower installation cost. Therefore, it has an irreplaceable role in the assisted driving system. This paper proposes a detection method based on the fisheye camera. Firstly, a method of feature block filtering based on gradient maxima is proposed, which makes it possible to distribute the features as much as possible on the outer and inner edges of the obstacle and on the edge of the texture, while limiting the number of selected features. Much of the integrity of the obstacle area is preserved. The feature block classes are then clustered to obtain a complete obstacle region. Compared with the current popular moving target detection methods, the proposed algorithm can preserve the integrity of the obstacle area more effectively, and can effectively reduce the feature matching error rate. Moreover, the method can effectively judge the relative distance between the obstacle and the vehicle. Change the situation to detect proximity to obstacles. Experiments show that the proposed method is effective in many scenarios and has stronger accuracy and robustness.
Embedding the Scientific Record on the Web: Towards Automating Scientific Discoveries

Future AI systems will be key contributors to science, but this is unlikely to happen unless we reinvent our current publications and embed our scientific records in the Web as structured Web objects. This implies that our scientific papers of the future will be complemented with explicit, structured descriptions of the experiments, software, data, and workflows used to reach new findings. These scientific papers of the future will not only culminate the promise of open science and reproducible research, but also enable the creation of AI systems that can ingest and organize scientific methods and processes, re-run experiments and re-analyze results, and explore their own hypothesis in systematic and unbiased ways. In this talk, I will describe guidelines for writing scientific papers of the future that embed the scientific record on the Web, and our progress on AI systems capable of using them to systematically explore experiments. I will also outline a research agenda with seven key characteristics for creating AI scientists that will exploit the Web to independently make new discoveries [1]. AI scientists have the potential to transform science and the processes of scientific discovery [2, 3].
MsFcNET: Multi-scale Feature-Crossing Attention Network for Multi-field Sparse Data

Feature engineering usually needs to excavate dense-and-implicit cross features from multi-filed sparse data. Recently, many state-of-the-art models have been proposed to achieve low-order and high-order feature interactions. However, most of them ignore the importance of cross features and fail to suppress the negative impact of useless features. In this paper, a novel multi-scale feature-crossing attention network (MsFcNET) is proposed to extract dense-and-implicit cross features and learn their importance in the different scales. The model adopts the DIA-LSTM units to construct a new attention calibration architecture, which can adaptively adjust the weights of features in the process of feature interactions. On the other hand, it also integrates a multi-scale feature-crossing module to strengthen the representation ability of cross features from multi-field sparse data. The extensive experimental results on three real-world prediction datasets demonstrate that our proposed model yields superior performance compared with the other state-of-the-art models.
Control of Stochastic Quantum Systems with Decomposable Target State

We propose a Lyapunov-based control method for stochastic quantum systems. The method can make the quantum state converge to a separable mixed target state from an arbitrary initial state. Specifically, the target state can be written as the tensor product of two matrices. Based on a well designed virtual mechanical quantity, a Lyapunov function and two control laws are presented: one can make the system equilibria in the largest invariant set stable according to LaSalle's invariance principle, and the other one can make the target state globally asymptotically stable.
IMPLEMENTING DIRECT METHOD BY USING GAMES TO IMPROVE EFL STUDENTS' READING COMPREHENSION

Reading skill is one of the aspects of the foreign language which need to be master by the students. Thus it needed an appropriate method to improve the students' reading skills, especially reading comprehension. Therefore, the researchers conducted the study by using the Direct Method to improve reading comprehension. The purpose of this study was to find out whether the Direct Method by using games can improve the students' reading comprehension. The sample was taken from the second-year students of MAN Sibreh consisted of 25 students. The experiment was conducted in four meetings. In collecting the data, this study used pre-test and post-test as the research instruments. The pre-test was given in the first meeting while the post-test was given in the last meeting. After analyzing the data, the obtained t-score is 3,92. It indicates that there are significant differences between pre-test and post-test. Moreover, the critical value of t for the degree of freedom was 2,06 at the level significance of 5% (0,05). Thus, the t-score (3,92) is higher than the t-table (2,06). Therefore, the hypothesis is accepted.
What makes Britons trust police to enforce the lockdown fairly

What do people think about pandemic policing? Should the police get extra powers to enforce the lockdown? A survey by Krisztian Posch (LSE), Julia Yesberg (UCL), Jonathan Jackson (LSE), Ben Bradford (UCL), Arabella Kyprianides (UCL) and Zoe Hobson (UCL) found some measures (such as checkpoints and issuing fines) are much more popular than others (like mobile phone and facial recognition tracking). Importantly, people’s perception of the legitimacy of the police is crucial in establishing public consent for enhanced police powers. In turn, legitimacy is rooted in people’s experience of everyday policing.
Privacy preserving anomaly detection based on local density estimation

&lt;abstract&gt; &lt;p&gt;Anomaly detection has been widely researched in financial, biomedical and other areas. However, most existing algorithms have high time complexity. Another important problem is how to efficiently detect anomalies while protecting data privacy. In this paper, we propose a fast anomaly detection algorithm based on local density estimation (LDEM). The key insight of LDEM is a fast local density estimator, which estimates the local density of instances by the average density of all features. The local density of each feature can be estimated by the defined mapping function. Furthermore, we propose an efficient scheme named PPLDEM based on the proposed scheme and homomorphic encryption to detect anomaly instances in the case of multi-party participation. Compared with existing schemes with privacy preserving, our scheme needs less communication cost and less calculation cost. From security analysis, our scheme will not leak privacy information of participants. And experiments results show that our proposed scheme PPLDEM can detect anomaly instances effectively and efficiently, for example, the recognition of activities in clinical environments for healthy older people aged 66 to 86 years old using the wearable sensors.&lt;/p&gt; &lt;/abstract&gt;
Improved user-based collaborative filtering algorithm with topic model and time tag

Collaborative filtering algorithms make use of interaction rates between users and items for generating recommendations. Similarity among users is calculated based on rating mostly, without considering explicit properties of users involved. Considering the number of tags of a user can direct response the user preference to some extent, we propose a collaborative filtering algorithm using topic model called user-item-tag latent Dirichlet allocation (UITLDA) in this paper. UITLDA model consists of two parts. The first part is active user with its item. The second part is active user with its tag. We form topic model from these two parts respectively. The two topics constrain each other and integrate into a new topic distribution. This model not only increases the user's similarity, but also reduces the density of the matrix. In prediction computation, we also introduce time delay function to increase the precision. The experiments showed that the proposed algorithm achieved better performance compared with baseline on MovieLens datasets.
Rancang Bangun Edugame "History of Shodanco Supriyadi": Sejarah Perlawanan Pasukan PETA Blitar Terhadap Jepang

Games are not only for entertainment but games can be a means of learning. Historical subjects are often considered boring and uninteresting lessons because there are no innovations to attract students' curiosity. Therefore, a learning media was created and an introduction to the history of the resistance of the Blitar PETA forces through an adventure edugame. The methodology used is an iteration with three increments, each of which consists of the analysis, design, code, and test phases. The game design uses Unity 3D as a tool. Tests carried out include integration testing, system testing, and acceptance testing. From the results of these tests it was found that the edugame application that had been developed was able to assist students in introducing the history of the resistance figure PETA Blitar named Supriyadi.
A Heuristic Method to Recommendation Systems

Recommendation systems are a subclass of information filtering systems that seek to predict which items are most likely interesting to the user. Content-based recommendation systems recommend items that are similar to the previously liked items. Context-aware recommendation systems are a type of content-based recommendation systems, where the items are filtered based on the value of their attributes. In this paper, a general mathematical model was developed for context-aware recommendation systems using a heuristic method. This method was implemented as a multiuser demo application, a movie recommendation system. The application was tested and the results have been evaluated with different metrics. It could be declared that the developed method is more precise than the existing methods.
Target Recognition Method Utilizing Super-Resolution Processing for Drone Automatic Flights

Research on autonomous driving for mobile objects and development of applications are widely conducted. GPS can be used to move drones to specified positions, however the accuracy of GPS will cause an error of up to 15m. Furthermore, in order to operate them, it is expensive in terms of camera devices.In this study, we use the total variation regularization method to generate super-resolution images. The aim is to increase the recognition rate even if a marker is far away from the camera device.