Reviewerly/exHarmony huggingface dataset:
Research on the Construction and Application of Desktop Virtual Reality Teaching System

The new mode of combining desktop virtual reality teaching system with traditional teaching is a new means of teaching, which breaks through the limitation of traditional teaching in time and space. This paper analyzes the feasibility and key technologies of the desktop virtual reality teaching system, and proposes the technical scheme and modeling of the desktop virtual reality teaching system that is feasible in the modern computer course teaching, and discusses the design and implementation of a desktop virtual reality teaching system with three-dimensional object display, three-dimensional space display and virtual scene construction. In this paper, a new stereo image generation algorithm is proposed, which is used to realize the technical scheme of the system. The abstraction of the complete virtual reality system is summarized into the physical geometry module, the scene module and the function module, etc. The texture mapping technology and the tree-structured scene modeling technology are applied to the solid geometry modeling and scene modeling of the virtual environment, and the resource occupancy of the system is controlled to a lower level while creating the virtual environment realism.
Comparative Study of Different Types of CAPTCHA

A CAPTCHA may be a challenging turning test designed to get the safety for network applications and estimate the result supported the human prediction instead of the involvement of computer Complete Automated Public Turning Test to inform Computers and Human Apart (Captcha) is essentially a software to check where the entry is given by human o Verification issues are used for cybersecurity. the safety provided make sure that data can't be misused. Research in captchas implies advancement in AI making computers understand how human worries computer machine. it's a mechanism widely used nowadays for shielding web applications, interfaces, and services from malicious users and automatic spammers. every kind of Captcha are discussed during this paper and their advantages over each is given during a detailed approach. Captcha helps in blocking automated creations of email-accounts. Blocks Computers to vote automatically in online-polls.
Status Kadar Hemoglobin Dan Jenis Leukosit Pada Pasien TB Paru Di Surabaya

Abstract Tuberculosis (TB) is a global public health problem, the World Health Organization (WHO) stated when it occurred around 7-8 million TB cases with 1.3-1.6 million deaths each year (WHO, 2012). TB is a specific multi-systemic infection, which can cause diverse clinical manifestations in each organ system, so, the clinical presentation of this disease is also quite diverse. Hematologic findings in TB are not uncommon and usually occur due to non-immunological factors. Hematological disorders in the form of anemia, leukocytosis, neutrophilia, lymphopenia, lymphocytosis and increased blood slope rate (LED), thrombocytosis and thrombocytopenia. On blood tests, when TB starts to become active there is a slight leukocytosis with a slightly abnormal type of count. Anemia is reported in 16-94% of patients with pulmonary TB. One's anemia status can be assessed one of them through examination of hemoglobin. The purpose of this study was to analyze the levels of hemoglobin and types of leukocytes in pulmonary TB patients in Surabaya. This examination uses an automatic analyzer with the working principle of SLS (sodium lauryl sulfate). Samples of the blood of pulmonary TB patients in several hospitals in Surabaya .. From 30 samples obtained an average hemoglobin level of 11.5 gr / dl, as many as 10 (33.4%) samples whose levels were within normal limits and 20 (66.6%) sample levels were below normal values. Examination of leukocyte count showed that there were 8 samples (26.6%) of normal neutrophil cells, 22 samples (73.4%) abnormal, 5 lymphocytes of normal cells (16.6%), 25 samples (83% abnormal), abnormal 25 samples (83%) , 4%), normal monocyte cells were 17 samples (56.6%) and abnormal were 13 samples (43.4%). Keywords: haemoglobine, leukosit type, TB patients
An Effective Approach for Nonrigid Structure From Motion With Complex Deformation

In this article, an effective approach is proposed for nonrigid structure from motion to deal with the image sequence with a complex deformation. In the proposed method, a three-dimensional (3-D) structure is first divided into multiple local trajectory groups by utilizing the distance weights of the pairwise points. For each local trajectory group, a weak estimator is constructed by means of the kernel shape trajectory approach (KSTA) due to its good performance for complex deformation. In order to improve the estimation accuracy, a feature vector selection algorithm based adaptive rank selection strategy is designed to choose the approximately optimal rank parameter for KSTA. For each 3-D point, the final estimation is derived from the outputs of the weak estimators by solving a sparse optimization problem. The experimental results on several commonly used sequences demonstrate the effectiveness and feasibility of the proposed method.
Robust deep supervised hashing for image retrieval

Hashing is an important technique branch of image retrieval due to its satisfactory retrieval performance with high retrieval speed and low storage cost. Deep supervised hashing methods, which take advantage of the convolutional neural network and the supervised information, have shown better performance than other kinds of hashing methods. However, previous deep hashing methods do not consider the noisy data, which generally exist in large-scale labeled datasets and mislead the learning algorithm. In this paper, we propose a novel robust deep supervised hashing (RDSH) method, in which a robust pairwise loss and a quantitation loss are used to supervise the learning procedure. The quantitation loss guides the CNN to output binary codes. The robust pairwise loss for similarity-preserving learning is designed based on generalizations of the exponential and logarithmic functions. By adjusting its parameters, the robust pairwise loss can exhibit special properties, including tail-heaviness and boundedness, which results in the robustness of the learning procedure to noisy training data. To verify the robustness of the RDSH, we conduct experiments on CIFAR10 with different noisy levels, in which RDSH shows better robustness than other deep supervised hashing methods. Experiments on standard CIFAR-10 and NUS-WIDE datasets show that RDSH outperforms other baselines.
Fast and Efficient Collision Avoidance Algorithm for Autonomous Mobile Robot

An autonomous mobile robot or Unmanned Ground Vehicle (UGV) is a vehicle that operates remotely, without human on-board. UGVs are widely used for mission-based applications that are often hazardous or/and inconvenient for humankind regardless of its sizes. As to enable its autonomous capability, UGVs often equipped with artificial eyes e.g. sensors and on-board camera to assist navigation during mission. In this experiment, we utilized a sweeping technique using ultrasonic sensor (HC-SR04) as the ‘eye’ of the mobile robot to map the obstacle around it using distance measurement. Meanwhile, an Arduino based controller is used to execute the avoidance algorithm. The ultrasonic sensor is programmed to sweep at six different angles to cover about 150° field of views. Path planning algorithm in this project provides the decision to avoid the obstacle and create temporary new waypoints within split seconds using decision table. We observed that the algorithm that uses decimal method is easy to implement and provides faster decision as compared to the binary method.
Penerapan Algoritma AES 128-Bit dalam Pengamanan Data Kependudukan pada Dinas Dukcapil Kota Pematangsiantar

Population data is information about the existence of someone in a country. The data can be accepted as validity through management in one of the government agencies. The issue of security and confidentiality of the data is something that is very important because it concerns the identity of a person, in order to avoid theft and manipulation of data it is necessary to apply a data security system. Cryptography is the study of mathematical techniques related to aspects of data and information security such as data validity, integrity, and data authentication. The Advanced Encryption Standard (AES) is one method used in data / information safeguards. The implementation of the AES algorithm in securing population data of the Population and Civil Registration Service shows that the method can produce messages that cannot be read or understood by humans (encryption) and produce the same message as the initial plaintext that was imputed (decryption)
Memo, bibliomediateca partecipativa

The dossier “Innovative Libraries” presents a review of the experiences of libraries that have in common the search for solutions aimed at redefining their role, with particular attention to the social dimension and new paths of access to knowledge. From a library experience conceived as a community hub, we move on to examine a case of involvement of local businesses in a cultural welfare perspective. The case of Turin is original. Here libraries offer to citizens hospitality in their offices to meet with professionals (accountants, notaries, etc.) to obtain advice, while in Rome and Milan there is a growing commitment to the prison population. The case of proximity libraries and condominium libraries is unique, while the promotion of active citizenship and the practice of listening is growing. Innovating also means transferring skills to students that enable them to operate in a Wikimedian environment or use the collections as an opportunity for conversation with the community. Innovation for academic libraries also passes through their ability to present themselves as digital and participatory thanks to the opportunities offered by the Third Mission and the opportunities offered to academic libraries to respond to the strong drives towards open science. Finally in a short article is described the new alliance between a public library and a library for patients of an oncology institute.
Spatial Distribution of Toxicity Unit Index and Environmental Risk Assessment of Some Heavy Metals in Industrial Dust of Ardakan county Based on Geostatistical Analysis in 2018

Background & Aim: Heavy metals are including destructive pollutants of environment which important due to adverse physiological effects on living organisms at low concentrations. Aims of performance this study was to measure the concentration of some heavy metals in industrial dust, as well as evaluate and Spatial Distribution the Toxicity Unit indices and Environmental Risk of metals using kriging geostatistical techniques. Methods: This descriptive-analytical and cross-sectional study was carried out in winter of 2018 by installing 35 dust sampler stations around the some of industries in Ardakan county. To collect dust samples and measurement concentrations of cadmium, chromium, vanadium, manganese and aluminum by ICP-MS, Toxicity Unit and Environmental Risk indices of elements were evaluated. Considering the ratio of Nugget to Sill in spherical, Gaussian, stable and exponential semivariogram models and validation using criteria such as Root mean square, Root mean square standardized and Mean standardized, best method of Kriging was selected for preparing spatial distribution map of indices. Results: Mean concentrations of aluminum, manganese, vanadium, chromium and cadmium were 51109.11, 248.02, 152.74, 59.54 and 2.07 mg/kg, respectively. Environmental Risk of industrial dust was determined in very high class. Toxicity Unit index of industrial dust was less than 4. Results of investigation of semivariogram parameters and validation of criteria showed, best method for spatial distribution of indices was simple kriging method with spherical semivariogram models for Environmental Risk index and stable for Toxicity Unit index. Conclusion: In winter season, cadmium and chromium do not cause acute toxicity in dust. Results this study expressing impact of industrial in increasing environmental risk of heavy metals. Also, direction of local dominant wind has an important role in dispersion of heavy metals.
UPAYA MENINGKATKAN KETERAMPILAN SISWA TENTANG MENYUSUN LAPORAN KEUANGAN PADA SISWA KELAS XI IPS 5 SMAN 3 KETAPANG MELALUI METODE SIMULASI

Classroom Action Research is based on the fact that students' ability to understand financial statements is still low. Whereas with the mastery of Economics in general students do not have difficulty learning other subjects. This observation took place in January to May 2017, because in those months students have completed general semester examinations and are still at the beginning of the semester so that student conditions can be observed from the beginning. Simulation method is a learning method wherein the teaching and learning process the teacher invites students to group together in completing assignments in class and allows students to find information that is traditionally informed or disguised. From this study it can be concluded that with the motivation in learning simulation learning methods the ability of students to compile financial statements and learning outcomes will be optimal. The more precise the motivation given, the more successful the lesson will be. With high motivation, the intensity of student learning efforts will also be high. So motivation will always determine the intensity of student learning. This will improve student learning achievement.Keywords: Compiling Financial Statements, Simulation Methods
Research on Intelligent Path Planning Based on Transit Point

The general path planning algorithm can only solve the shortest path or the lowest cost path problem, and can not play a very good role in path planning with throttling transfer points. In order to deal with the problem of road traffic flow or material flow path planning in the transportation process, this paper constructs the joint transportation network structure model based on the transfer point and the genetic algorithm, which can solve the problem of road traffic flow or material flow path planning in the transportation process. The model includes two sets of transfer point and connecting arc segment. The throttling information contained in the transfer point of the model can well constrain the flow problem in the path planning. The joint transportation network structure based on the transfer point is planned by genetic algorithm. In this paper, nine transport particles with flow are used for planning, and the results show that the method is simple and effective.
A New Image Compression by Gradient Haar Wavelet

With the development of human communications, the usage of visual communications has also increased. The advancement of image compression methods is one of the main reasons for the enhancement. This paper first presents main modes of image compression methods such as JPEG and JPEG2000 without mathematical details. Also, the paper describes gradient Haar wavelet transforms in order to construct a priliminary image compression algorithm so that sub images inherit the same amount of original image information. Then, a new image compression method is proposed based on the preliminary image compression algorithm that can improve standards of image compression. The new method is compared with original modes of JPEG and JPEG2000 (based on Haar wavelet) by image quality measures such as MAE, PSNAR, and SSIM. The image quality and statistical results confirm that can boost image compression standards. It is suggested that the new method is used in a part or all of an image compression standard.
Improving data handling and analysis in the study of rhyme patterns

Abstract By reviewing a recent quantitative study of rhyme patterns in Mandarin Chinese, this study shows how data handling and data analysis in the study of rhyme patterns can be improved. Suggestions for improvement include (a) a consistent annotation of rhyme data, which is exhaustive and facilitates data reuse, and (b) emphasizes the importance of automated approaches for exploratory data analysis, which can help to analyze rhyme data in an improved way, prior to applying statistical frameworks for hypothesis testing.
NLP Questions Answering Using DBpedia and YAGO

In this paper, we present results of employing DBpedia and YAGO as lexical databases for answering questions formulated in the natural language. The proposed solution has been evaluated for answering class 1 and class 2 questions (out of 5 classes defined by Moldovan for TREC conference). Our method uses dependency trees generated from the user query. The trees are browsed for paths leading from the root of the tree to the question subject. We call those paths fibers and they represent the user intention. The question analysis consists of three stages: query analysis, query breakdown and information retrieval. The aim of those stages is the detection of the entities of interest and its attributes, indicating the users’ domain of interest. The user query is then converted into a SPARQL query and sent to the DBpedia and YAGO databases. The baseline and the extended methods are presented and the quality of the solution is evaluated and discussed.
PENGEMBANGAN FRAMEWORK MOBILE LEARNING PADA PERTANIAN SAYURAN

In vegetable production, farmers face many obstacles, such as the problems related to seeds, pest and disease control, commodity prices, and marketing of produces. There is almost no useful information and technology easily accessible to improve the situation. With the better penetration of the Internet to the villages and the wide availability of inexpensive mobile devices, mobile learning provides a good solution. This study is aimed to create a mobile learning framework that provides information and interactive communication about vegetable production needed by farmers. The method used was instructional design of ADDIE (Analysis, Design, Development, Implementation, and Evaluation). Usability surveys of the proposed prototype to farmers, extension agents (field technical assistants), and researchers, result in 79.4%, 87.3%, and 87% satisfaction testing, respectively, in information needs fulfillment. Summative Testing in the aspect of User Acceptance Testing of validity and reliability indicated that the prototype could be used by farmers. Based on the assessment by experts, 87.3% of them agreed that the mobile learning framework for vegetable farming could provide learning information about vegetable production . Keywords: Mobile Learning, Mobile Learning Framework, Mobile Learning Agriculture, ADDIE (Analysis, Design, Development, Implementation, Evaluation) DOI : http://doi.org/10.5281/zenodo.3631040
Applying Natural Language Processing Techniques to Generate Open Data Web APIs Documentation

Information access globalisation has resulted in the continuous growing of online available data on the Web, especially open data portals. However, in current open data portals, data is difficult to understand and access. One of the reasons of such difficulty is the lack of suitable mechanisms to extract and learn valuable information from existing open data, such as Web Application Programming Interfaces (APIs) with proper documentation. Actually, in most cases, open data Web APIs documentation is very rudimentary, hard to follow, and sometimes incomplete or even inaccurate. To solve these data management problems, this paper proposes an approach to automatically generate Web API’s documentation which is both machine and user readable. Our approach consists of applying natural language processing techniques to create OpenAPI documentations. This manner, the access to data is facilitated because of the improvement on the comprehension of the APIs, thus promoting the reusability of data. The feasibility of our approach is presented through a case study that shows and compares the benefits of using our OpenAPI documentation process within an open data web API.
Quando la biblioteca diventa un hub di comunità

The dossier “Innovative Libraries” presents a review of the experiences of libraries that have in common the search for solutions aimed at redefining their role, with particular attention to the social dimension and new paths of access to knowledge. From a library experience conceived as a community hub, we move on to examine a case of involvement of local businesses in a cultural welfare perspective. The case of Turin is original. Here libraries offer to citizens hospitality in their offices to meet with professionals (accountants, notaries, etc.) to obtain advice, while in Rome and Milan there is a growing commitment to the prison population. The case of proximity libraries and condominium libraries is unique, while the promotion of active citizenship and the practice of listening is growing. Innovating also means transferring skills to students that enable them to operate in a Wikimedian environment or use the collections as an opportunity for conversation with the community. Innovation for academic libraries also passes through their ability to present themselves as digital and participatory thanks to the opportunities offered by the Third Mission and the opportunities offered to academic libraries to respond to the strong drives towards open science. Finally in a short article is described the new alliance between a public library and a library for patients of an oncology institute.
A semi-supervised trace lasso norm regularized image classification method

Since the cost of labeling data is getting higher and higher, it is essential to develop some algorithms for practical applications especially when only a small number of labeled images are available. We deal with this by designing a novel model and show that with a small amount of unlabeled samples added to the training set the classification result can be effectively promoted. In our method the query image is collaboratively represented by the whole training samples, whether they are labeled or unlabeled. There are two regularization terms. Rather than getting the sample sparsity, the first regularization term, a variant Trace Lasso norm, forces the group sparsity, which means the query image is presented by a small number of groups, say one or two groups, and in each group the training samples are fully used. This sparsity between groups and density within a group is preferred to the aim of face classification. The similarity matrix is used in the second term to obtain the pseudo-labels for the unlabeled training samples, thus the whole samples are classified into different groups, each one corresponding to a class. Augmented Lagrange Multiplier scheme and Alternating Direction Method of Multiplier are given to solve the problem numerically. Some experiments are conducted to show the performance of the proposed work.