Reviewerly/exHarmony huggingface dataset:
ОТРАЖЕНИЕ ПРОФЕССИОНАЛЬНЫХ ЧИТАТЕЛЬСКИХ ИНТЕРЕСОВ БИБЛИОТЕКАРЕЙ: РЕЗУЛЬТАТЫ АНАЛИЗА БИБЛИОТЕЧНОЙ БЛОГОСФЕРЫ И СОЦИАЛЬНОЙ СЕТИ

The article is devoted to the study of professional reader’s interests of library specialists, based on the method of analysis of library blogs and social network Facebook. The author notes the high communication potential of blogs, but emphasizes the instability of this online genre. With the advent of social networks – the author states – blogging as a tool of the Internet communication has faded into the background. At the same time, both library blogs and social networks are good sources of information about the reader’s interests of library professionals. The author distinguishes two blocks of professional reader’s interests, reflecting information needs of this professional group: general professional, caused by belonging to the professional community, and specific caused by private factors. Analysis of library blogs and social networks is the method that allows getting sufficiently objective data that is associated with psychological peculiarities of the network communication, the main of which is its informal nature, predetermined by trust relationships between the participants.
The Construction Method of Geographic Knowledge Graph Ontology Model Based on GML

Geographic ontology model is the conceptual model of geographic knowledge graph and the logical basis for constructing the pattern layer of geographic knowledge graph. In the classification of geographic ontology research, geographic ontology model is in the category of domain ontology. It is a set of abstract structures to express ontology according to the spatial location, attribute characteristics and relational characteristics of geographic data. This paper discussed the logical components and architecture of geographic ontology, designed the geographic ontology model reference to GML, described the model using OWL language, and constructed the geographic ontology model based on GML. The geographic ontology model comprises three sub-models: element model, geometric model and spatial relation model. Finally, based on Protégé ontology construction tool, this paper designed the semantic description of geographic entity and realized the construction of geographic ontology system.
Perbandingan Kinerja Topologi Canonical Dan Folded Clos Tree Pada Jaringan Data Center

A Data Center (DC) can be said to be of quality if it can provide optimal service. Optimal service means that the access provided must be free of distractions. Disturbances can originate from outside the system or from within the system itself Both can only be overcome if a DC has a good architecture. There are two comparable topologies compared, namely canonical tree and folded closs tree topologies which aim to get better data transfer rates between the two and which one has better data transfer speeds between the two when interference occurs. In analyzing these comparisons, the authors compare using the ftp method in mathematically analyzing the data transfer rates of the two DC architectures above using the same comparator data on 3 trials so as to obtain an accurate result, which one has better data transfer speeds and the best data transfer when both are interrupted in case one of the best flow switches is interrupted.
A Study of Neural Network Performance for Gesture Recognition

As the Digital Revolution progresses, it is characterized by a fusion of technologies that is blurring the lines between the physical, digital, and biological spheres. While earlier Industrial revolutions were characterized mainly by advances in technology, the underlying basis for the current innovation lies in communication, connectivity and user centricity. People who suffer from visual, speech and hearing impairment find it difficult to communicate. The aim of this paper is to analyze two neural network methods and compare them based on well- defined criteria obtained from the use case of gesture recognition using neural networks. The paper will broadly cover two neural networks including MobileNet and a traditional neural network.
An Empirical Study of Hate Crime Occurred in Korea: Based on The Cases Appeared in Internet News

본 연구는 2000년 1월부터 2019년 11월까지 인터넷 기사에 나타난 우리나라의 실제 증오범죄 사례 35건을 판단표본추출(judgement sampling)하여 내용분석한 후, 피해집단의 특성, 공동범행 여부, 가해자의 미성년자 여부, 행위태양, 가해동기에 따라 분류하고 그 의미를 고찰하였다. 연구 결과, 피해 집단은 외국인, 여성 및 다문화, 장애인의 순이었으며, 35건 중 21건이 단독범죄였고, 35건 중 11건의 가해자가 미성년자였다. 행위태양은 폭행이 가장 많았으며 그 다음이 모욕의 순이었다. 또한 여성 및 외국인을 대상으로 한 증오범죄는 모두 단독범에 의해 이루어졌으며, 다문화를 대상으로 한 증오범죄는 모두 미성년자에 의한 학교폭력의 형태로 이루어졌다. 미성년자들은 91%의 사건에서 공동범행을 하였으며, 성인은 96%의 사건에서 단독범행을 한 것으로 확인되었다. 가해동기를 중심으로 보면, 스릴추구형은 주로 다문화 가정 청소년을 대상으로 한 학교폭력에서 많이 발견되었으며, 방어형은 외국인을 대상으로 한 단독범에게서 많이 발견되었다. 동성애자에게 욕설 등을 가하는 형태의 의무감형 증오범죄 사례 역시 확인할 수 있었으나, 선행 증오범죄에 대한 보복으로 또 다른 증오범죄를 저지르는 보복형은 발견할 수 없었다. 한편 특정개인에 대한 분노를 그 개인이 속한 불특정 집단 구성원에게 표출하는 형태로 이루어진 일부 사례들은 위 네 가지 유형 어디에도 해당된다고 보기 어려웠다. 이상의 발견을 토대로 증오범죄 통계수집, 차별금지법 제정, 인권교육 실질화 등의 정책적 방안을 논의하였다.This study analyzed 35 hate crime cases that occurred in Korea. The data were collected from internet news appeared from January 2000 to May 2019. The result shows that hate crimes against multi-cultural and handicapped persons occurred mainly in the form of a school violence involving multiple juvenile offenders, while hate crimes against women, foreigners, and homosexuals were often committed by a single adult offender. When it comes to the psychological motive of offenders, the thrill-seeking type mainly occurred in the form of a co-offending against multi-cultural students and the handicapped in the school, and the defensive type occurred mainly in the form of a single-handed offending against foreigners. Some mission type cases against homosexuals were also found, but no retaliation type hate crimes were found. Meanwhile, some cases including the Yoo Young-Chul murder case were not applicable to any of the above four types, and this study named this type as private anger expression type and examined its characteristics. Based on the findings, I discussed policy implications including collecting hate crime statistics, enacting anti-discrimination law, and giving human rights education some substance.
Penerapan Metode Kompresi Burrows Wheler Transform Pada Citra Hasil Interpolasi Bicubic

Image compression or image compression aims to minimize memory requirements in representing digital images by reducing duplication of data in the image so that the memory needed is less than the original image representation. This is useful to shorten the image sending time and also save memory usage compared to uncompressed images. One image that is often compressed is the image of interpolation. Interpolation (often called resampling) is an imaging method to increase (or reduce) the number of pixels in a digital image. Some digital cameras use interpolation to produce images that are larger than the captured sensor or to make digital zoom. Almost all image editing software supports one or more interpolation methods. How an enlarged image can be smooth without leaving the impression of rupture depends very much on the sophistication of the interpolation algorithm. Burrows Wheler Transform Algorithm and Bicubic Interpolation Algorithm are good compression and interpolation methods in image processing. Magnification and compression of the image of an image is done by performing matrix operations on the image to be enlarged and compressed
A Profit Maximization Scheme with Guaranteed Quality of Service in Cloud Computing

Cloud computing has grown in popularity being a practical and efficient method to offer clients computing resources and services on demand.One of the most important elements from the standpoint of cloud service providers is revenue, which is mostly influenced by how a cloud service platform is built in light of market demand.To design a cloud platform, nevertheless, a single long-term rental plan is often used.This cannot ensure the quality of the service and results in significant resource waste.In order to address the difficulties at hand, this study first designs a twofold resource rental model that combines short-term and long-term rentals.This system of duplicate renting may significantly cut down on resource waste and efficiently ensure the caliber of service for every request.In second step, a service system is modeled as an M/M/m+D queuing model, and performance metrics that influence profitability of our twofold renting scheme are examined, such as average fee, the percentage of requests that require temporary servers, and other factors.Third, a profit maximization challenge for the dual renting scheme is created, and the optimal design of a cloud platform is produced by resolving issue.In order to evaluate profit of our suggested plan with that of only one rental scheme, a number of computations are finally performed.The findings demonstrate that our plan not only ensures that every request will receive high-quality service, but also generates more profit than the alternative.
The institutional economics of blockchain

This chapter introduces the institutional economics of distributed ledger technology. Blockchains are a distinct general purpose technology that provide reduce the transaction costs of exchange; that is, they are an institutional technology. The chapter presents the economic attributes of blockchains in the framework developed by Oliver Williamson. Blockchains complement and compete with other institutions that work to mitigate opportunism by industrialising trust. The chapter concludes with a comparative institutional analysis of blockchains as an institutional technology.
Pembuatan Aplikasi Resep Makanan Tradisional Indonesia Berbasis Android MengunakanMetode Generate and Test Untuk Pencarian

Cooking requires a knowledge in terms of preparing and processing ingredients that can be used as food that is beneficial to humans, therefore it is necessary to eat recipes that can help in preparing food ingredients, how to make and how to serve it to produce with taste delicious, delicious and interesting. Cooking recipes have been obtained from generation to generation from our parents, but sometimes not all food recipes can be known because of a lack of knowledge due to lack of information on certain food recipes, especially traditional food recipes that have begun to be forgotten along with the presence of modern food recipes . In the case of traditional food is the food down from our ancestors and is no less delicious and delicious with modern food. But the current flow of information makes modern food a step further than traditional food. Therefore it is necessary to have an information system that can inform these traditional food recipes in order to help Indonesian traditional food lovers.
An Improved Reversible Watermarking Based on Pixel Value Ordering and Prediction Error Expansion

In this paper, a new pixel value ordering (PVO) and prediction error Expansion (PEE) based reversible watermarking method is proposed. PVO based method firstly introduced by Li et al.’s has been concerned and expanded because it can achieve high embedding capacity without losing the implication of the cover. We improve related work in two points: the first is the way to build location map, the second is technique of embedding secret data. Only one bit is used to create location map while related scheme utilizes two bits. So that we get the location map with shorter size. The less size location map the more embedding capacity because we have more space to embed data, the embedding capacity of the proposed scheme is thus increased. Theory analysis and experimental results showed that the proposed scheme is clearly better in terms of embedding capacity compared with state-of-the-art works. The watermarked image that is applied our technique is good imperceptibility.
A Study on the Recognition and Activation of Youth Training Activity

The purpose of this study is to analyze the perception and preference of youth training activities as part of a basic study to find ways to promote them in general. In order to achieve research purposes, the survey on overall training activities was conducted on students, teachers, and school administrators who use training facilities to analyze data on their responses. T- or F-testing was performed to analyze differences in preference for training activities. For the analysis of the above mentioned data, the SPS 24.0 Statistical Pekage was used. First, after analyzing the purpose of participating in the training activities, 33.2 percent of teachers and 30.4 percent of parents choose career and academic guidance for the purpose of participating. Second, after analyzing the timing of their desire to participate in training activities, everyone preferred fall. Third, an analysis of places where people want to participate in training activities showed that the most preferred mountain areas (47.1 percent) were the entire subjects. Based on what has been studied so far, the following results can be made. First, standards for training facilities should be set up at a broader level and the utilization rate of secured training facilities should be improved and increased as well as quantitatively secured. Second, training facilities are desperately in need of serious research on training activities, abandoning stereotypes. Third, youth training facilities consisting of public institutions should be lavishly provided with institutional and material support from the government and local governments as a venue for the youth’s all-round lifelong education activities.
Abstract P501: Mobile Daily Physical Activity and Fall Risk Monitor for Lifestyle Management, Disease Prevention and Risk Alert Generation

Mobile health monitoring is driving many smart health innovations. In this research, we focus on the daily physical activity and fall risk monitoring, for intelligent activity tracking and fall risk detection purpose. Physical activity is of a tremendous value to cardiac and brain health, and has been widely agreed as a metric to improve human health, foster healthy lifestyle, and mine the impacts on diverse health issues. The risk of death can actually be lowered by 20 to 30% with moderate activities for one and half an hour per week (WHO). Besides, fall risk detection is also of huge importance since each year, there are 29% of older adults having around 29 million falls and causing 7 million fall injuries (CDC). The challenge we target is how to accurately recognize diverse physical activities and fall patterns from the biomechanical dynamics sensed by the phone. More specifically, the phone sensor is leveraged to provide real-time always-on streaming of biomechanical dynamics. Then, the data is learned by a deep learning framework (long short-term memory) for activity type and fall pattern recognition. To consider real-world scenarios, the users can put the phone in either left or write waist pockets. The users have performed 9 different kinds of activities such as walking, standing up, going upstairs and jumping, as well as 8 different kinds of fall patterns such as falling backward, sitting and falling, and falling forward with protection. A total of 11,770 activities performed by 30 subjects aging from 18 to 60 have been used to evaluate the framework, yielding an accuracy as high as 95.4%. This encouraging result shows the potential of the mobile monitor in real-world application scenarios.
Fast privacy-preserving keyword search on encrypted outsourced data

Cloud providers offer storage as a service to the data owners to store emails and files on the cloud server. However, sensitive data should be encrypted before storing on the cloud server to avoid privacy concerns. With the encryption of documents, it is not feasible for data owners to retrieve documents based on keyword search as they can do with plain text documents. Hence, it is desirable to perform a multi-keyword search on encrypted data. To achieve this goal, we present a fast privacy-preserving model for keyword search on encrypted outsourced data in this paper. Specifically, the model first performs a keyword search on encrypted data and checks its support for dynamic operations. Based on keyword search results, it then sorts all the relevant data documents using the number of keywords matched for a given query. To evaluate its performance of our model, we applied the standard metrics like precision and recall. The results show the effectiveness of our privacy-preserving keyword search on encrypted outsourced data.
A Domain Specific ESA Method for Semantic Text Matching

An approach to semantic text similarity matching is concept-based characterization of entities and themes that can be automatically extracted from content. This is useful to build an effective recommender system on top of similarity measures and its usage for document retrieval and ranking. In this work, our research goal is to create an expert system for education recommendation, based on skills, capabilities, areas of expertise present in someone’s curriculum vitae and personal preferences. This form of semantic text matching challenge needs to take into account all the personal educational experiences (formal, informal, and on-the-job), but also work-related know-how, to create a concept based profile of the person. This will allow a reasoned matching process from CVs and career vision to descriptions of education programs. Taking inspiration from the explicit semantic analysis (ESA), we developed a domain-specific approach to semantically characterize short texts and to compare their content for semantic similarity. Thanks to an enriching and a filtering process, we transform the general purpose German Wikipedia into a domain specific model for our task. The domain is defined also through a German knowledge base or vocabulary of description for educational experiences and for job offers. Initial testing with a small set of documents demonstrated that our approach covers the main requirements and can match semantically similar text content. This is applied in a use case and lead to the implementation of an education recommender system prototype.
Advanced Software Architectures and Technologies in High Performance Computing and Data Centers

This paper reviews advanced software architectures and technologies that support in-networking computing and improve the overall performance of data centers and high-performance computing clusters; the ability to converge software and hardware allows for new solutions, such as artificial intelligence, to be deployed massively.
Case Based Architecture to Categorize SMS in Mobile System

The intense growth of smart mobile phones has contributed to the growth of online or offline Instant Messaging and SMS usage as an alternative way of Transaction and communication. The rapid growth of users, along with the faith they instinctively have in their devices, makes this kind of messages a congenial environment for spammers. In fact, reports distinctly shows that volume of spam over Instant Messaging and SMS is rapidly increasing year by year. This represents a challenging problem for classical filtering methods these days. Smishing This term represents a phishing in SMS/Messages called as Smishing is a cyber-security attack, which utilizes Short Message Service (SMS) to steal personal data/credentials of mobile users. The faith level of mobile users on their smartphones has attracted attackers to perform various mobile security attacks like Smishing. In this paper, we implement the SMS-Case-based data mining classification approach to classify them subpart of SMS category by detecting of Illegitimate/Smishing messages. This proposed approach identified more than fifteen Cases which can efficiently classify them into three parts like- Primary/Useful, Illegitimate/Fraud/Smishing SMS. Furthermore, our approach applies different classification algorithms to train these renowned Cases. Since the SMS/ Messages text are usually short and generally written in Lingo language, we have used text normalization to convert them into standard form to get better Cases [1]. The performance of the proposed approach is evaluated, and it achieved more than 99% true negative rate. Further, the proposed approach is very effective for the detection of the zero hour attack too and we will classify them into three subparts, like Primary/Useful, Illegitimate/Smishing, Promotional/Others. This classification data can be used to make a better enhanced existing SMS/Message application, by providing an enhanced version of SMS application
TECHNOLOGY APPLICATION IN MUSEUM

With collections in form of historical objects, as well as objects related to human culture, museums have taken an important role in providing education, especially for tourists who visiting a destination. However, at its conditions who have lacks of innovation, has implications for the declining number in interest of tourists to come and dig deeper into the collections in the museum. The form of innovation carried out in this art exhibition uses technology, including artificial intelligence. These forms of innovation that have been carried out by the art exhibition performance form should also be replicated by other museums in Indonesia. The research will be conducted to answer how could technology applied during social arts performance at the museum?Research will be conducted by inviting some practitioners of technology application at museum, augmented reality, virtual reality, private sectors, government (both central and local government), and museum administrator. Focus group discussion and depth observation will be conducted on January in several areas in Jakarta. This research is expected to answer interaction and immersion model which could still be remain after technology applied at museum. It is also expected to answer in which ways technology could be immersed in visitor’s experience with technology that could be classified into non-immersive (within a screen), semi-immersive (projected into a huge screen or a wall), and fully immersive (with a headset such as Virtual Cardboard or Oculus Rift). Interaction and immersion model will be linked with six dimensions of well being experienced, that should be occurred for visitor’s journey at the museum, including self-acceptance, positive relations, autonomy, environmental mastery, personal growth, and purpose in life.
Optimalisasi Infrastruktur Jaringan Menggunakan Link Aggregation Control Protocol Dengan Device Cloud Router Switch

The development of data in a company is getting bigger and requires fast access time. the existence of a system that uses computer networks and internet access to support the activities of the company becomes an important part in the use of infrastructure in the company. Computer networks are accessed by all staff and employees in the building and there are servers and databases that are accessed all the time. In the building part consists of several work processes that simultaneously access to the same network and server. Then each staff and employee will access the same network infrastructure, where the data transfer burden is delegated to only one (1) switch port to connect. This can result in a large burden and network access can be slowed. By providing a configuration to optimize the switch network that adopts the link agro-protocol protocol (LACP) method on the use of network infrastructure so that it can be a solution for overcoming large network loads and slow access. By applying PPDIOO to the infrastructure development method so that the expectations can be achieved in accordance with the desired results
5·4 Literature to See in the Viewpoint of Reformism : Focused upon the Practice of Literary World Surrounded by the Revolution of “The Short Story Magazine”

초록·키워드 목차 오류제보하기 등록된 정보가 없습니다. #Revolution #Improvement #Unbalance #『The Short Story Magazine』 #Old Literature #New Literature #Realism #Romanticism #New Romanticism #Three-dimensionality 1. 서론 : ‘굴절’의 시간으로서의 5·42. 본문 : 이론의 ‘과잉’과 창작의 ‘빈곤’에 대하여3. 결론 : ‘굴절’의 시간으로서의 5·4參考文獻ABSTRACT