Validation of Tagging Suggestion Models for a Hotel Ticketing Corpus

This paper investigates methods for the prediction of tags on a textual corpus that describes hotel staff inputs in a ticketing system. The aim is to improve the tagging process and find the most suitable method for suggesting tags for a new text entry. The paper consists of two parts: (i) exploration of existing sample data, which includes statistical analysis and visualisation of the data to provide an overview, and (ii) evaluation of tag prediction approaches. We have included different approaches from different research fields in order to cover a broad spectrum of possible solutions. As a result, we have tested a machine learning model for multi-label classification (using gradient boosting), a statistical approach (using frequency heuristics), and two simple similarity-based classification approaches (Nearest Centroid and k-Nearest Neighbours). The experiment which compares the approaches uses recall to measure the quality of results. Finally, we provide a recommendation of the modelling approach which produces the best accuracy in terms of tag prediction on the sample data

Efficient skyline processing algorithm over dynamic and incomplete database

The notion of skyline processing is to discover the data items that are not dominated by any other data items. It is a well-known technique that is utilised to determine the best results that meet the user’s preferences. However, the rapid growth and frequent changes of data make the process of identifying skyline points no longer a trivial task. Most of the existing skyline approaches assume that the database is complete and static. However, in real world scenario, this assumption is not valid especially in multidimensional databases in which some dimensions have missing values while they are dynamic due to the continual modifications made towards them. Blindly examining the whole database after changes are made to identify the skyline points is inappropriate as not all data items are affected by the changes. Hence, in this study we propose a skyline algorithm, DyIn-Skyline, which is capable of identifying skyline points over dynamic and incomplete databases, by exploiting only those data items that are affected by the changes. Several experiments have been conducted and the results show that our proposed algorithm outperforms the previous work by reducing the number of pairwise comparisons in the range of 50% to 73%

Sensor Technologies for Caring People with Disabilities

Today, the population uses technology for every daily activity involving business, education, communication, entertainment, etc. Technologymay also help us to take care of peoplewho suffer some kind of disability. Complex technological ecosystems with pervasive and intelligent capabilities get along with us, facilitating the vigilance of those who need special attention or assisted living cares due to their health limitations. The advances in sensor research have enriched the powerful of these ecosystems to achieve more sophisticated monitoring and alarm systems, also taking into account the balance between the level of assistance and the people’s privacy. The Special Issue on “Sensor Technologies for Caring People with Disabilities” aims to present recent developments on sensor technologies for caring people with disabilities, focusing on the different configurations that can be used and novel applications in the field

Review of Intent Diversity in Information Retrieval : Approaches, Models and Trends

The fast increasing volume of information databases made some difficulties for a user to find the information that they need. Its important for researchers to find the best method for challenging this problem. user intention detection can be used to increase the relevancies of information delivered from the information retrieval system. This research used a systematic mapping process to identify what area, approaches, and models that mostly used to detect user intention in information retrieval in four years later. the result of this research identified that item-based approach is still the most approach researched by researchers to identify intent diversity in information retrieval. The used of item-based approach still increasing from 2015 until 2017. 34% paper used topic models in their research. It means that Topic models still the necessary models explored by the researchers in this study

FATIMAH AL-BANJARI (d. 1828 CE) INDONESIA'S WOMAN ULAMA

This study discusses the da'wah contribution of Indonesian female ulama Fatimah Al-Banjari (d. 1828 AD). This research uses qualitative methods by making and observing works, books, academic research, videos, internet sources, and historical documents. The existing data is then analyzed using the explanatory analysis method where the logic of social phenomena is common sense by using historical, anthropological, and sociological approaches. This research tries to show the role model of female ulama Fatimah Al-Banjari so that women today can learn and imitate the activities and struggles of these female ulama so that many benefits are generated for the improvement of the ummah, especially women. The concept of women scholars, contributions, strategies carried out by these women scholars are presented. Then the supporting and inhibiting factors of women ulama in preaching are also discussed so that they can be understood in depth

Приоритеты научно-технологического развития железнодорожной отрасли в контексте цифровизации: зарубежный опыт

Digitalization opens new opportunities and ways of doing business in all sectors of the economy. This process does not bypass the railway industry. The criticality of digitalization of the industry is explained by the widespread use of railway transport, and the increasing demand on quality and speed of providing transportation services. The article is devoted to the analysis of the priorities of digital transformation of the railway industry and highlights key trends of digital transformation, as well as priority areas of scientific and technological developments. The objective is to describe a three-level study of prospects for scientific and technological development of the railway industry in the context of digitalization of the economy based on application of the methods of system analysis to international expertise and practices. The first level of the study was devoted to identification of the main directions of development of digital technologies which can be applied to railway transport; the second level was the analysis of strategic railway documents developed in some regions followed by identification of key trends in digital development; the third one made it possible to identify the most effective information technologies to be implemented for railways, particularly in the Russian Federation.Цифровизация открывает новые возможности и способы ведения бизнеса во всех отраслях экономики. Данный процесс не обходит стороной и железнодорожную отрасль. Критичность цифровизации этой отрасли объясняется повсеместным использованием железнодорожного транспорта, возрастающими потребностями в качестве и скорости предоставления транспортных услуг. Настоящая статья посвящена анализу приоритетных направлений цифровой трансформации железнодорожной отрасли. Были выделены ключевые тренды цифровой трансформации, приоритетные направления научно-технологического развития.Целью данной статьи является описание проведённого трёхуровневого исследования перспектив научно-технологического развития железнодорожной отрасли в контексте цифровизации экономики на основе применения методов системного анализа международного опыта. Первый уровень заключается в определении магистральных направлений развития цифровых технологий, которые могут быть применены к железнодорожному транспорту; второй уровень направлен на анализ стратегических документов железнодорожного транспорта в ряде регионов с выявлением ключевых тенденций цифрового развития; третий – на выявление наиболее эффективных информационных технологий для применения на железнодорожном транспорте, в том числе в Российской Федерации

A Conceptual Model for Participants and Activities in Citizen Science Projects

24 pages, 4 figures, 3 tablesInterest in the formal representation of citizen science comes from portals, platforms, and catalogues of citizen science projects; scientists using citizen science data for their research; and funding agencies and governments interested in the impact of citizen science initiatives. Having a common understanding and representation of citizen science projects, their participants, and their outcomes is key to enabling seamless knowledge and data sharing. In this chapter, we provide a conceptual model comprised of the core citizen science concepts with which projects and data can be described in a standardised manner, focusing on the description of the participants and their activities. The conceptual model is the outcome of a working group from the COST Action CA15212 Citizen Science to Promote Creativity, Scientific Literacy, and Innovation throughout Europe, established to improve data standardisation and interoperability in citizen science activities. It utilises past models and contributes to current standardisation efforts, such as the Public Participation in Scientific Research (PPSR) Common Conceptual Model and the Open Geospatial Consortium (OGC) standards. Its design is intended to fulfil the needs of different stakeholders, as illustrated by several case studies which demonstrate the model’s applicabilityPeer reviewe

The role of osteoprotegerin (OPG) in fibrosis:its potential as a biomarker and/or biological target for the treatment of fibrotic diseases

Fibrosis is defined by excessive formation and accumulation of extracellular matrix proteins, produced by myofibroblasts, that supersedes normal wound healing responses to injury and results in progressive architectural remodelling. Fibrosis is often detected in advanced disease stages when an organ is already severely damaged and can no longer function properly. Therefore, there is an urgent need for reliable and easily detectable markers to identify and monitor fibrosis onset and progression as early as possible; this will greatly facilitate the development of novel therapeutic strategies. Osteoprotegerin (OPG), a well-known regulator of bone extracellular matrix and most studied for its role in regulating bone mass, is expressed in various organs and functions as a decoy for receptor activator of nuclear factor kappa-B ligand (RANKL) and tumor necrosis factor-related apoptosis-inducing ligand (TRAIL). Recently, OPG has been linked to fibrosis and fibrogenesis, and has been included in a panel of markers to diagnose liver fibrosis. Multiple studies now suggest that OPG may be a general biomarker suitable for detection of fibrosis and/or monitoring the impact of fibrosis treatment. This review summarizes our current understanding of the role of OPG in fibrosis and will discuss its potential as a biomarker and/or novel therapeutic target for fibrosis

Y-DWMS - A digital watermark management system based on smart contracts

With the development of information technology, films, music, and other publications are inclined to be distributed in digitalized form. However, the low cost of data replication and dissemination leads to digital rights problems and brings huge economic losses. Up to now, existing digital rights management (DRM) schemes have been powerless to deter attempts of infringing digital rights and recover losses of copyright holders. This paper presents a YODA-based digital watermark management system (Y-DWMS), adopting non-repudiation of smart contract and blockchain, to implement a DRM mechanism to infinitely amplify the cost of infringement and recover losses copyright holders suffered once the infringement is reported. We adopt game analysis to prove that in Y-DWMS, the decision of non-infringement always dominates rational users, so as to fundamentally eradicate the infringement of digital rights, which current mainstream DRM schemes cannot reach

Knowledge, perceived risk, and preventive behaviours amidst Covid-19 pandemic among dental students in Malaysia

The purpose of this study is to assess the knowledge status, perceived risk, and preventive behaviours of dental students in Malaysia on COVID-19. A cross-sectional study across dental schools in Malaysia was conducted through online survey. 93.5% had a high score of knowledge on COVID-19. Regarding perceived risk and preventive behaviours, female students scored higher than the males. Chinese students scored the highest in knowledge of COVID-19, while Malay students had the highest perceived risk score. In terms of preventive behaviors, the mean score did not vary across ethnicity. On-campus students scored higher in knowledge and perceived risk scores whereas off-campus students practiced more preventive behaviors. The mean score for knowledge was higher among clinical students as compared to preclinical students. The final year dental students scored higher in knowledge and perceived risk compared to their juniors. In conclusion, majority of dental students have good knowledge about COVID-19, high perceived risk, and practiced most of the preventive behaviors. Nevertheless, they should always keep up with the latest advancements in COVID-19