Reviewerly/exHarmony huggingface dataset:
A Dataset for Noun Compositionality Detection for a Slavic Language

This paper presents the first gold-standard resource for Russian annotated with compositionality information of noun compounds.The compound phrases are collected from the Universal Dependency treebanks according to part of speech patterns, such as ADJ+NOUN or NOUN+NOUN, using the gold-standard annotations.Each compound phrase is annotated by two experts and a moderator according to the following schema: the phrase can be either compositional, non-compositional, or ambiguous (i.e., depending on the context it can be interpreted both as compositional or noncompositional).We conduct an experimental evaluation of models and methods for predicting compositionality of noun compounds in unsupervised and supervised setups.We show that methods from previous work evaluated on the proposed Russian-language resource achieve the performance comparable with results on English corpora.
KONTRIBUSI KETERAMPILAN MEMBACA APRESIATIF TEKS CERITA FABEL TERHADAP KETERAMPILAN MEREPRODUKSI TEKS CERITA FABEL SISWA KELAS VIII SMPN 12 PADANG

ABSTRACT This article has written the contribution of appreciative reading skill of fable story text to the skills of producing fable story texts at students VIII class of SMPN 12 Padang. This research is quantitative research using the descriptive method and the contribution research design. The research data is the test result score of appreciative reading skill of fable story text and the test result score of reproducing fable story text. The data has obtained through two types of test that are the objective test which uses reproducing fable story text . Based on the result of data analysis and the discussion, the researcher concludes the three things follow; first, the average score of the student’ reading appreciative reading skill of fable story text at students VIII class of SMPN 12 Padang is in the good qualification (82.01). Second, the average score of the student’ reproducing fable story text students at VIII class of SMPN 12 Padang is in the good qualification (79,17). Third, there are the significant contributions between the appreciative reading skill of fable story text toward the students reproducing fable story text students at VIII class of SMPN 12 padang as much as 84,82%. Kata kunci: Kontribusi, Keterampilan, Membaca Apresiatif, Mereproduksi, Teks Cerita Fabel
Secure De-Duplication of Data on Hybrid Auditing

The amount of data stored in storage devices are increased rapidly, as the evolution of networking techniques emerges. While storing huge amount of data, the storage servers ,may want to reduce the volume of the stored data, and the clients may want to check the integrity of their own data through low cost, since the cost of the functions related to data storage increase in proportion to the size of the data. To achieve these functionalities, privacy preserved deduplication and auditing techniques have been studied, which can reduce the volume of data stored on the server by eliminating duplicated copies and allows clients to efficiently verify the integrity of the stored files by delegating costly operations to a trusted party, respectively. We design a technique which performs both secure deduplication of encrypted data and hybrid integrity auditing of data which is stored on the storage devices. We utilize a Third Party auditor(TPA) for performing dynamic audit, in order to help the clients. The proposed scheme provides all the fundamental security requirements through cloud storage server.
Water Treatment Biology Teaching Reform Based on Engineering Education Certification

The course teaching reforms of water treatment biology, based on engineering education certification, aims at cultivating the comprehensive abilities of students to analyze and solve the complex problems in water supply and sewerage science and engineering.The reforms were performed by optimizing and integrating teaching contents, establishing of a multi-level training system for innovation practice ability and guiding students to use the integrated knowledge in the training.The practice abilities and innovation consciousness of students have been evidently improved.Meanwhile, the students' abilities of exchange and cooperation with each other can be developed well.
Research on the Reform of Training Mode for Professional Degree Postgraduates

The reform of the training mode of professional degree postgraduates is an important link to adapt to the diversified needs of China's economic and social development, cultivate high-quality and comprehensive quality application oriented talents, and narrow down the advanced level of developed countries. At present, the training of professional degree postgraduates in China has problems such as lack of understanding, convergence of training modes, difficulties in joint training, and low quality of training. It is necessary to further clarify the training principles and ideas, improve the training guarantee conditions, reform the existing training modes, and constantly improve the practical ability of professional degree postgraduates.
Cloud Computing for Disaster Management

Cloud computing allows network access to a computing resources like servers, storage and applications. These shared resources can be increasingly use-full to the consumers on the basis of paying only for resources they use. Cloud provides the delivery of storage resources to the consumers over the Internet. Private cloud storage is to a particular organization and data security risks is more in cloud. Hence, private cloud storage is built by using the commodity machines within the organization and the important data is stored in it. When the use of cloud increases the problems also increase like performance & storage demand, privacy & security, data integrity. Increase in storage leads to extend the cloud storage with more storage nodes. During such expansion, the storage on the cloud needs to be managed In order to maintain the load across storage nodes, the data need to be move across the storage nodes. This data that is moved from one location to other, consumes more network bandwidth. The key idea behind this is to develop a dynamic load balancing algorithm based on de-duplication to balance the load across the storage nodes during the Extension of private cloud storage. For maintaining privacy, security & data integrity we will use AES algorithm & SHA algorithm. SHA algorithm also used to avoid duplication.
On Observability and Stability of Moving-Horizon Estimation in a Distributional Framework

In this work, we propose a unifying framework in the space of probability measures for gradient-based and sampling-based moving-horizon estimation methods. We begin with an investigation of the classical notion of strong local observability of nonlinear systems and its relationship to optimization-based state estimation. We then present a general moving-horizon estimation framework for strongly locally observable systems, as an iterative minimization scheme in the space of probability measures. This framework allows for the minimization of the estimation cost with respect to different metrics and divergences. In particular, we consider two variants, which we name W <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> -MHE and KL-MHE, where the minimization scheme uses the 2- Wasserstein distance and the KL-divergence respectively. The W <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> -MHE yields a gradient-based estimator whereas the KL-MHE yields a particle filter, for which we investigate asymptotic stability and robustness properties. Stability results for these moving-horizon estimators are derived in the distributional setting, against the backdrop of the classical notion of strong local observability which, to the best of our knowledge, differentiates it from other previous works. We also present results from numerical simulations to demonstrate the performance of these estimators.
Path Planning Based on the Method of Integrating Adjacent Obstacles

Path planning for an autonomous mobile robot refers to using various sensors to detect its surrounding and finding a suitable path from the initial position to the target. In the current research on path planning of autonomous mobile robots, the artificial potential field method is widely applied because it is simple and concise. However, it may cause the robot to stop or circular motion of the robot in the area where obstacles are dense, that is the local minimum problem. In order to solve this problem, this paper proposes a neighbor-obstacle unifying method. It is composed of three steps. First, the position of the obstacles is detected by the sensors of the robot, and some obstacle areas can be obtained according to the distances between the adjacent obstacles. Next, a circumscribed circle is determined according to the center of each area, this circle is regarded as the integration of the obstacles. Finally, the original obstacles are replaced by the integrated one. This method can not only avoid local minimum, but also improve the efficiency of path planning. The simulation results verify the efficiency of the method.
Measuring The Accuracy of The Facial Images Using Convolutional Neural Networks in Deep Learning

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
A Comprehensive Study about various Clustering Techniques

Clustering has been utilised in numerous kinds of research areas, which is one of the unsupervised learning method. This concept tries to discover some patterns and distributions in unlabelled data sets. This paper analysis the fundamental concepts of clustering techniques and its necessities. Some of the clustering techniques like k-means clustering technique, EMClustering technique and DBSCAN clustering techniques are discussed.Moreover the general kinds of clusters are also discussed.
UNSUR PEMBELAJARAN EDUTAINMENT DALAM QUANTUM LEARNING

Early childhood learning uses the principle of playing while learning so that it must be arranged so that it is fun, uplifting, and democratic. Quantum Learning is a learning method that is loaded with edutainment concepts. Based on the studies conducted, the following conclusions are obtained: (1) Quantum learning and edutainment both emphasize the urgency of a pleasant and easy atmosphere; (2) Equally starting from the world of non-education; (3) Both give primary attention to an exciting learning process, which involves physical-sensory, emotional, and suggestive beliefs; (4) Quantum learning and edutaintment are able to foster student confidence; (5) Quantum learning builds student learning skills through a variety of cutting-edge discoveries, and edutainment continually seeks to facilitate optimal learning processes; (6) Quantum learning and edutaintment simultaneously build effective communication to students.�Keywords: learning, quantum learning, edutaintmen
Evaluation of Indias Most Visited Websites in Aspects of Security and Structure

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
Research on Optimization of Training Program for Master's Degree in Pedagogy with Social Need Orientation

At present, the training of high quality applied talents in pedagogy should be oriented by the needs of society.From the perspective of social need orientation, there are some problems in the training program of master's degree in pedagogy, such as unclear training objectives, inflexible schooling system, imperfect curriculum, imperfect tutor system, insufficient practice links and low differentiation of assessment methods.Taking the social need as the orientation, this paper proposes to optimize the training program of master degree in pedagogy from the following six aspects: clear training objectives, flexible revision of the school system, improvement of the curriculum, establishment of "double tutors" system, construction of practice bases and improvement of assessment methods.
Object Tracking Based on Scale Estimation and Context-Aware Correlation Filter

Correlation filter (CF) based trackers have achieved great progress in recent research. Even in high speed rates, it can make good performance. We observed that it has a great impact on the tracking performance because of the surrounding environment and the object to be tracked. If the surrounding environment become very worse, this will make the tracker do not work well. So the context aware information of the objected is become more and more important. The correlation filter within context aware information can deal with the background of the object. When the object is moving, the scale variation is of importance to the tracker. Adaptive scale estimation can help the correlation filter tacker the object well. According to the analyse, this paper proposes the method within context aware correlation filter and adaptive scale estimation to deal with this problem. The experiment shows that the method makes good performance in the benchmark sequences.
PENINGKATAN MOTIVASI DAN HASIL BELAJAR PECAHAN DENGAN MENGGUNAKAN PENDEKATAN KOOPERATIF TIPE TGT DI KELAS V SDN 04 KAYU MANANG

The research was motivated by the low motivation and learning outcomes of mathematics in class V SDN 04 Kayu Manang Surian. The research objective is to increase motivation and learning outcomes of Mathematics by using the approach of cooperative type of TGT. This type of research is Classroom Action Research, which was carried out in 2 cycles in the second semester of 2015/2016 with the subject of teacher research and fifth grade students totaling 22 people. Research data were collected through observing student activities, learning motivation questionnaires and tests. The research findings show that the use of the TGT cooperative model approach can increase motivation and student learning outcomes in learning mathematics. Increased student motivation can be seen in the first cycle with a percentage of 20% of students expressed strongly agree, 51% of students agreed. Whereas in the second cycle, they got a score of 46%, the students strongly agreed, 30% of the students agreed. Improved student learning outcomes seen in cycle 1 with an average value of 68.55, in the second cycle to 7.32. Based on the findings of this study concluded that the approach model of learning cooperative tpe TGT can be used as an alternative to increase motivation and student learning outcomes in learning mathematics
Towards Gradually Typed Capabilities in the Pi-Calculus

Gradual typing is an approach to integrating static and dynamic typing within the same language, and puts the programmer in control of which regions of code are type checked at compile-time and which are type checked at run-time.In this paper, we focus on the π-calculus equipped with types for the modeling of input-output capabilities of channels.We present our preliminary work towards a gradually typed version of this calculus.We present a type system, a cast insertion procedure that automatically inserts run-time checks, and an operational semantics of a π-calculus that handles casts on channels.Although we do not claim any theoretical results on our formulations, we demonstrate our calculus with an example and discuss our future plans. IntroductionThis paper presents preliminary work on integrating dynamically typed features into a typed π-calculus.Pierce and Sangiorgi have defined a typed π-calculus in which channels can be assigned types that express input and output capabilities [16].Channels can be declared to be input-only, output-only, or that can be used for both input and output operations.As a consequence, this type system can detect unintended or malicious channel misuses at compile-time.The static typing nature of the type system prevents the modeling of scenarios in which the inputoutput discipline of a channel is discovered at run-time.In these scenarios, such a discipline must be enforced with run-time type checks in the style of dynamic typing.Gradual typing provides a natural solution to do just that, as it advocates the integration of dynamic typing and static typing [18,24].In gradual typing the programmer is in control of which regions of code are type checked at compile-time and which are given a pass, with the promise to perform checks at run-time when actual values are available.In this paper, we present our preliminary work to equip Pierce's and Sangiorgi's typed π-calculus with gradual typing.Our contributions are:• We present a formulation of a gradual type system for capabilities in π-calculus.This type system allows for channels to be declared dynamically typed, that is, their capabilities will be only known at run-time.Accordingly, the type system is permissive when dynamically typed channels occur, but still rejects processes if strong inconsistencies are found at compile-time.• We offer a cast insertion procedure: A run-time check is inserted at any spot in which the gradual type checker has been optimistic and gave a pass.We make use of casts on channels to perform run-time checks.• We present a formulation of a π-calculus with cast channels.This is an operational semantics that extends that of the π-calculus to handle casts on channels and detect when they fail or succeed.
Efficient and Secure Re-Encryption Data Model for Cloud

In the computer generation number of users were increasing greatly, as the number of users increases the usage of data also increase, as the usage of data increases data storage also increases gradually. When data increase there are number of chances to theft the data. So to increase the data storage a technology is playing vital role i.e. cloud computing. In this data can be stored and data can be accessed the same. Here, the data authorized person must concern about security of the data. This work is to provide more security to the data stored in cloud. Identification Based Encryption is introduced to provide encrypted key generation related operations to key update cloud service provider for key -issuing and key update processes. An encryption is used to provide security to data, for authenticating the user; encrypting the date again called re-encryption data storage model for security. This work proposes an outsourcing computation into IBE revocation formalizes the security.
Analysis of privacy profiles applying fuzzy clustering techniques

Unsolved roots of "privacy paradox" motivate researchers to extricate the underlying reasons of such phenomenon.In the field of privacy research, the majority of empirical studies lack the availability of the real data collected from the actual platform instead of data collected from the experimental lab setup.This paper uses the real-world data set of user privacy behavior.Different fuzzy clustering algorithms (such as Fuzzy C-means (FCM), Gustafson-Kessel (GK) algorithm, and Fuzzy Partitioning Around Medoids (PAM)) are applied to the given dataset, and their outfits are compared.The analysis provides the clustering validity procedures applied to the data and then produces the partitioning results of the given set of data in the form of graphical visualizations.This work demonstrates how differently clustering algorithms behave with a given dataset producing various shapes and properties of clusters.
Framework for Digital Data Access Control from Internal Threat in the Public Sector

Information management is one of the main challenges in the public sector because the information is often exposed to threat risks, particularly internal ones.Information theft or misuse, which is attributed to human factors, affects the reputation of public sector organizations due to the loss of public trust in the security and confidentiality of the information and personal data that are hacked by internal parties.Most studies focus on general problem solving related to internal threats instead of digital personal data protection.Therefore, this study identifies the main security control elements for personal data access in the public sector, including information security management, human resource security, operational security, access control, and compliance.A comprehensive framework is developed based on the identified security control elements and validated using a case study.Data are collected using interview, observation, and document analysis techniques.The findings contribute to the management of information system security through a systematic approach to controlling internal threats in the public sector.This framework can serve as a guideline for the public sector in managing internal threats to reduce security incidents involving unauthorized access to digital personal data.