Reviewerly/exHarmony huggingface dataset:
“PERSONAL SELLING” PADA JASA LAYANAN PERPUSTAKAAN ISI SURAKARTA

The main objective of research was to describe whatContext, Input,Process and Product frompersonal selling at the user education program inLibrary Technical Service Unit.This research was intended to find out whether ornot the condition of Context, Input, Process and Product in personal selling in theuser education program was consistent with CIPPNorm. This study wasconducted in Indonesian Art Institute (ISI) of Surakarta. The research methodologyapplied was qualitative descriptive. Data of Context, Input,Process and Product wascollected using qualitative approach. The informants consisted of a headlibrary,librarians and students.Context aspect declared that in the implementation of program was exposedclearly throughbackground and objective. User education program aimed to introduceservice and productof ISI Surakarta’s library. Input aspect in program implementationcould run well. User education wasimplemented by librarians with public speaking andinformation tracing skills. Resistance from this program was declared by unclear screenand the room is too spacious, so thatt communicationbetween communicator andcommunicant was less effective. Product aspect in some promotion mixes wassufficientlysatisfactory. User education program could be measured from the increase oflibrarymember number. The questionnaire response also stated that used educationprogram wasneeded by new students to make them familiar with service and facility oflibrary in ISISurakarta.
Perancangan Sistem Data Mining Market Basket Analysis Terhadap Data Penjualan Toko Elektronik

Website data mining is a system that useful for digging data information as an information and marketing media. The author conducts the research on sales transaction data to make a system, that can make the system easier to use in extracting data information by doing processing sales transaction data using data mining market basketball analysis. Development in website data mining market basket analysis is carried out by analyzing the need, to know what is needed from development, the author do it by collecting the data that consists of primary and secondary data. The method of data collection are interviews and documentation. The form of this research is study case. Research method that used by author is Research and Development, as we know the result of this method is produces certain products and tests the effectiveness of the product. Data collection techniques that used in this research are observation, interview and documentation study. The process of creating a website data mining market basket analysis on this sales data is uses the PHP programming language using Sublimetext 3, while the database that used in this research is MySQL.  The method software design that used is Rapid Application Development (RAD) in the application of a system. With this website data mining creation can support work efficiency and effectiveness, facilitate data processing and get combination information of sales data in order to increase competition in marketing.
English Teaching Design Based on the New College Entrance Examination Reform Environment

According to the latest information on the reform of the college entrance examination in 2014, the number of college entrance examination subjects and examination methods are appropriately reduced, and English is gradually transformed into social examination. In this paper, under the background of the new college entrance examination reform, what problems exist in the current English teaching and how to carry out the English teaching are analyzed.
Building Your First Cloud Application

This chapter shows how to create simple cloud infrastructure and run two instances of a custom REST API behind a load balancer. The API implementation presented in this chapter will only serve as an example. The main goal is to guide you through the process of building your first cloud-based solution from scratch. Later, in the course of the book, you will also learn how to provision autoscaled instance pools, deploy your apps in Docker containers to Oracle Kubernetes Engine, and execute serverless functions on Oracle Functions. At this stage, however, let’s focus on the foundations and use standard virtual machines.
Analysis of Modified Shell Sort for Fully Homomorphic Encryption.

The Shell sort algorithm is one of the most practically effective in-place sorting algorithms. However, it is difficult to execute this algorithm with its intended running time complexity on data encrypted using fully homomorphic encryption (FHE), because the insertion sort in Shell sort has to be performed by considering the worst-case input data. In this paper, in order for the sorting algorithm to be used on the FHE data, we modify the Shell sort with an additional parameter $\alpha $ , allowing exponentially small sorting failure probability. For a gap sequence of powers of two, the modified Shell sort with input array length $n$ is found to have the trade-off between the running time complexity of $O(n^{3/2}\sqrt {\alpha +\log \log n})$ and the sorting failure probability of $2^{-\alpha }$ . Its running time complexity is close to the intended running time complexity of $O(n^{3/2})$ and the sorting failure probability can be made very low with slightly increased running time. Further, the near-optimal window length of the modified Shell sort is also derived via convex optimization. The proposed analysis of the modified Shell sort is numerically confirmed by using randomly generated arrays. For the practical aspect, our modification can be applied to any gap sequence, and we show that Ciura’s gap sequence, which is known to have good practical performance, is also practically effective when our modified Shell sort is applied. We compare our modified Shell sort with other sorting algorithms with the FHE over the torus (TFHE) library, and it is shown that this modified Shell sort has the best performance in running time among in-place sorting algorithms on homomorphic encryption scheme.
Traffic Sign Identification Using a Partially Cooperative Strategy in a Convolutional Neural Network

Recently, deep learning has introduced new prospects to numerous practical applications such as image recognition, robot navigation, gene engineering, language processing, and traffic sign identification. Several network models including AlexNet, VGGNet, GoogLenet and ResNet, have achieved milestone contributions while relying on massive computing resources. However, when faced with a small number of labeled examples, especially in the case of unbalanced datasets, the cumulative error and time-consuming convergence reduce their efficacy. Inspired by the convolutional output layer with a [Formula: see text] kernel, a convolutional nonlinear transfer approach with partial cooperating (CNN-COL) is proposed to address this challenge. Meanwhile, a novel method for data augmented balance can enhance the influence of small and unbalanced samples in the CNN-COL. Related experiments show that the proposed CNN-COL can effectively improve the quality of a dataset and achieve superior performance with respect to traffic sign identification based on a small and type-unbalanced dataset.
Development of Learning Materials Based on Local Culture in Basic School Using Waterfall Methods

Development of Learning Materials is a process that will be carried out on devices that will be used in the learning process. Education is rooted in national culture and regional culture as a pillar of national culture.This study aims to produce local culture-based learning material in Class IV Elementary School (SD). Local culture is a habit that grows and develops and is owned and recognized by local tribal communities. This culture will later be used as the basis for developing learning materials. The steps for developing teaching materials follow the ADDIE development model (Analysis, Design, Development, Implementation, Evaluation) with the Research and Development method. The product of development research is the Nosarara Nosabatutu Module with expert validity test results. The Waterfall method is a model that is often called the classic life cycle, which describes a systematic and sequential approach to software development that can be implemented in various developments. The results showed that the module-shaped learning material nosarara nosabatutu is suitable for use in elementary school learning in Palu City as evidenced by the results of language expert validation of 3.9 (good), design experts validation of 4,3 (very good), mater expert validation of 4.5 (very good), teacher validation of 4.5 (very good). This data is reinforced by the validation of the readability of one to one learners by 86.8%, the effectiveness of learning materials through completeness testing in small groups with 100% classical completion results and an increase in the learning outcomes of pretest and posttest by 81.08% (criteria sufficient 29.73% ; good criteria 32.43%; very good criteria 18, 92%). Nosarara nosabatutu module-shaped learning material has been integrated with a communication technology-based learning system by including barcodes from online learning sources that can be operated with QR Scanner Nosarara Nosabatutu (QR. NN Scanner).
LibGuides: E-Resources: HyRead

E- Resources in LRC HyRead mainly offers books and journals published in Taiwan, including children books for paired reading, literature and fiction, and books on business and economics, household knowledge, social sciences, technology and medicines, language learning, educa
Hubungan Open Access Institutional Repository (OAIR) dengan Produktivitas Ilmiah pada Dosen di Perguruan Tinggi

OA becomes a new model in the scientific communication process. In various studies show that OA gives the impact of increasing research by giving free access to articles for all who are interested. The OA movement is not only limited to the process of disseminating and promoting work from the research community, but has evolved into individual institutional repositories, electronic archives of research results of staff working on these institutions. Some academic libraries have begun to develop Open Access Institutional Repositories (OAIR). Along with the development of OAIR, the academic community is demanded to be productive in conducting scientific publications. The development of OAIR and scientific publications are very important components in scientific communication. This study aims to determine whether there is a relationship between the availability and accessibility of OAIR with the scientific productivity of lecturers. The method used in this research is descriptive quantitative. The number of respondents was 70 lecturers from 3 universities who presented the 2018 SINTA Awards, namely the University of Indonesia, UIN Sunan Gunung Djati and the Ministry of Health II Jakarta Poltekkes. Data collection is done by using questionnaires in the form of online and offline. The results of this study indicate that the availability and accessibility of the OAIR system has a multiple correlation coefficient of 0.812 and a significance value of 0,000, so there is a positive influence and has a very strong relationship on scientific productivity among lecturers.
Framework for ontology-driven threat modelling of modern computer systems

Threat modelling of a computer system is based on the system analysis of its architecture on early development stages (requirements, design) and creation of a threat model that represents security aspects of the system (threats and mitigations). Used in this field means, like data flow diagrams (DFD) and Application threat modelling approach (OWASP, Microsoft), are mainly informal and hard to involve automation. In order to overcome these restrictions, we have created the ontology-driven threat modelling (OdTM) framework, which allows to use graphical notation of DFD diagrams and semantic domain-specific threat models to build threat models for different computer systems. Each domain-specific threat model has a set of typical components of some subject area and threats/countermeasures associated with these components. An end user can describe a computer system with DFD diagram(s), then reasoning procedures are able to build a threat model for that system. The OdTM framework consists of a common approach of the architectural security analysis and method of semantic interpretation of DFD diagrams and automatic reasoning of relevant threats and countermeasures. We have developed the base threat model as OWL (Web ontology language) ontology that enables creation of domain-specific threat models as OWL ontologies and extension them with different external knowledge sources (knowledge “mining”, the Linked Open Data etc.). To illustrate proposed approach, we have used a semantic version of a model that depicts common threats against cloud computer systems.
Two-party Private Set Intersection with an Untrusted Third Party.

We construct new protocols for two parties to securely compute on the items in their intersection. Our protocols make use of an untrusted third party that has no input. The use of this party allows us to construct highly efficient protocols that are secure against a single malicious corruption.
Augmented Reality Application Supporting On-Site Secondary Building Assets Management

Secondary building assets management requires a large amount of information related to them.Nevertheless, building assets surveys are cost and time demanding, especially because they need long post-processing efforts in order to systematize collected data.Furthermore, with the recent transition towards the BIM methodology for building management also modeling building objects both in their geometric features and in their related information is a long process and error-prone task.Under these circumstances the possibility of performing the majority of operation on-site would definitely make the process more efficient and it would reduce errors.Augmented Reality (AR) with its capability of overlapping digital data to the real scene is the right tool to support operators on-site.The proposed system has the aim of reducing the time of secondary building assets survey and provide a tool for the automatic enrichment of BIM models.An AR device (Hololens) with an embedded computer and a neural compute stick constitute the portable on-site system for the automatic recognition of assets objects, removing the necessity of reworking data off site.A trained Deep Learning Neural Network inside the neural compute stick performs the recognition providing the operator with objects features and position.The AR application inside the Hololens operates as an interface between the user and the digital information just created.Finally, data is stored in a NoSQL database linked to the BIM model so as to be available for further operations.The visually supporting information provided by the AR tool, the possibility of working on data directly on site and the portability of the system represent means for increasing efficiency in survey operations.First tests have been conducted so as to prove the feasibility of the system and its use on site without further equipment.
ICT-Based, Fast-Reading Learning

This research proposes a learning method based on ICT (information and communication technologies) with the aim of promoting best practices in the context of education and which allowed to improve the performance of students of a school in the field of education. quick and comprehensive reading. The method was implemented in a web application with an interactive and didactic environment that tested the skills and knowledge that students acquire in the classroom. The intention was to verify by means of an implantation test in an educational environment if the method is really effective and if it fosters the interest of including didactic learning strategies in the classroom.
Fast LSTM Inference by Dynamic Decomposition on Cloud Systems

LSTM (long short-term memory) is a powerful deep learning technique that has been widely used in many real-world data-mining applications such as language modeling and machine translation. In this paper we aim to minimize the latency of LSTM inference on cloud systems without losing accuracy. If an LSTM model does not fit in cache, the latency due to data movement will likely be greater than that due to computation. In this case we reduce model parameters. If, as in most applications we consider, the LSTM models are able to fit the cache of cloud server processors, we focus on reducing the number of floating point operations, which has a corresponding linear impact on the latency of the inference calculation. Thus, in our system, we dynamically reduce model parameters or flops depending on which most impacts latency. Our inference system is based on Singular Value Decomposition (SVD) and Canonical Polyadic Decomposition (CPD). We evaluate our system based on models from a series of real-world applications like language modeling, computer vision, question answering, and sentiment analysis. Users of our system can use either pre-trained models or start from scratch. Our system achieves 15X average speedup for six real-world applications without losing accuracy in inference.
Analysis of Fans’ Cyberwords From the Perspective of Memetics

With the development of internet, network is more and more important in people’s daily life. Among the huge network user groups, fans as a unique group gradually come to people’s vision, meanwhile cyberwords used by fans group also becomes one of the research topics of scholars. As far as memetics is concerned, language itself is a kind of meme, and memes also reside in language. From this point, linguistic memes are widely spread among fans group. In this paper, five types of fans’ cyberwords and their functions are analyzed from the perspective of memetics, and specific phenomena which influence the generation and spread of linguistic memes are also explored.
Auktorisering i system för digitalt bevarande

The purpose is to investigate, analyze and clarify the relationship between authorization and security policy for digital preservation system. Information security comes into focus when digital pre ...
Analysis of TSP Model Adapted to Transdisciplinary Teams: Quality Application Development for Impairment People

The technology development, both hardware and software, has a constant increase, so that for the development of this one, various processes are used, in most of them focused on production limited by three restrictions: quality, time and requirements, since if it is developed in a shorter time without considering the implicit and explicit requirements, there is a lack of product quality. If this lack occurs with the construction of products for average people, with greater reason the development of those products focused on people with disabilities, who need them to be built without fragmentation and inconsistency [1]. This article analyzes the TSP model adapted to transdisciplinary teams in the quality applications development for people with disabilities (TIA-TSP) using the results of the experimentation. This article is structured as follows: The introduction defines the TSP model [2] adapted to transdisciplinary team (TIA-TSP). The development describes the experimentation with the TIA-TSP, an example of its use and its products obtained in each of its phases, the results explain the quality of the applications generated and the TIA-TSP verification, and finally in conclusions the analysis is carried out and the advantages and deficiencies found when using this model are exposed.
Elliptic-Curve Cryptosystems

This chapter consists of short descriptions of a few elliptic-curve cryptosystems. Examples of three types of cryptosystem are given: message encryption, key agreement, and digital signatures. The descriptions are intended to provide no more than a context for the arithmetic, and the reader who wishes to properly learn about the systems should consult the relevant literature.
Modelling of Parameters of a Precision Surface Texture Using a Correlation Algorithm

The paper describes a new method for texture analysis of precision machined surfaces which is based on the use of computer optics and an autocorrelation method for processing the obtained images of the textures of the studied microreliefs. The method is based on a probabilistic comparative estimate of the unknown texture of the surfaces under study with known reference micro-reliefs; the parameters are predefined according to GOST R ISO 25178-2-2014.
Deformable 3D registration with PWC-net optical flow and textured node correspondences

In this paper, we present an approach for the deformable registration of 3D data via an RGB-D camera to reduce depth distortions in featureless regions. We employ the established PWC-Net based Optical Flow algorithm to identify pixel correspondence between nearby frames and then densely and uniformly select transformation nodes. Color correspondence of the transformation nodes is used in both global and local deformations. Several experimental results show that the proposed method results in low distortion during the non-rigid registration of multiple RGB-D images.
Survey of Load Balancing Algorithms in Cloud Environment Using Advanced Proficiency

Cloud computing has turned out to be well known because of its appealing highlights. The heap on the cloud is expanding hugely with the improvement of modern applications. Burden Adjusting is a crucial a piece of cloud domain setting that protects that each processor or devices execute equal quantity of labor in same quantity of your duration. Various types’ calculations to the burden adjusting in distributed computing with the created intend to create cloud assets open end of the clients easily, intrigue. In this paper, we mean to give an organized, extensive diagram of the examination on burden adjusting algorithms in distributed computing. This paper reviews the cutting-edge burden adjusting apparatuses and systems. We gathering existing methodologies planned for give load balancing in a reasonable way. With this arrangement we give a simple and succinct perspective on the basic model embraced by every approach.
Leakage-free ID-Based Signature, Revisited

Abstract Recently, Tseng et al. proposed a new notion for identity-based signature (IBS) scheme to resist ephemeral secret leakage (ESL) attacks, called leakage-free identity-based signature (leakage-free IBS), and devised the first secure leakage-free IBS scheme. However, they only considered the situation of the leakage of ephemeral secrets used for generating the signatures. Notice that the private key extraction procedure is probabilistic as well in their scheme, that is, there are ephemeral secrets used by the key generation center to generate the signers’ private keys. It is practical to consider that if the adversary comprises these ephemeral secrets, then he can reveal the master key of the system. Therefore, it is desired to introduce a new security notion for the leakage-free IBS schemes to consider the ESL attacks on both private key extraction and signing procedures. In this paper, we present such security notion. Moreover, we propose two IBS schemes that are proved to be secure under the new security notion.