Reviewerly/exHarmony huggingface dataset:
Comprehensive Ontological Model for Senior Wellness Activity Recognition in Smart Homes

There are several works in the field of smart homes for healthcare, with different types of sensors used to monitor medical, behavioral and environmental parameters for patients. In the context of smart home for the elderly, the use of sensors needs to be adapted to respect the privacy of elders and to work passively without the need for caregiver assistance. Most research in this area focused on activity recognition (e.g. eating, sleeping, watching TV, etc.) which may be defined as the identification of a sequence of actions (e.g. using microwave, lying down, etc.). In this chapter, we propose a comprehensive ontological model for well-being activity recognition in smart home. Our approach takes into account different aspects of the well-being context such as patient profile, object being used to perform the activity, the time of running the activity, its location, etc. In order to validate the proposed ontology and reason on it, we perform a set of queries and inference rules.
미래지향적 예술인재양성 교육에 대한 소고 - 초․중등교육을 중심으로 -

This study explores the meaning and value of fostering and training artistic talent in the age of artificial intelligence and the social environment due to the advent of a hyper-connected society. In doing so, this study first explores the expansion of the concept of art in the 4th Industrial Revolution and the education paradigm. Secondly, it presents not only the need for elementary and secondary education that is no longer college admission and competition-driven, but more tailored to students’ career paths, and also with the need to foster artistic talent in the changing environment where art is no longer exclusive to one particular class. On these grounds, this study investigates the current status of Korea's art talent fostering and education in order to illustrate problems and improvements that can be made within the changing socio-economic structure. This study then conclusively proposes a future-oriented way of fostering artistic talent by: firstly providing a model for an ideal Neo-renaissance art talent with creative capacities; secondly acknowledging the need for an integrated curriculum for fostering artistic talent; amd thirdly establishing a tailored smart education environment that also meets the needs of the local community. This review can be used as basic support material for developing a policy level support system strategy, and a specific roadmap, as well as improving the current curriculum for artistic human resource education and professional art education.
The insertion of confidential information into digital images using blowfish cryptography and end of file steganography

Abstract Identity Theft Resource Centre revealed there were 668 cases of cybercrime occurring with a total number of lost data 22,408,258 started from January to July 2018. It indicates that there was a vulnerability in the defences from attacks carried out through the internet. Thus, the world of information systems should also be accompanied by a high level of security. The stages of system development were started from the analysis of system requirements, the design of the UML, implementation, and testing. The testing process into two-phase. Firstly, system output testing in the form of stego image with various criteria, namely imperceptible, fidelity, recovery, robustness, and histogram. Secondly, system feasibility testing using the SUS method. Based on the results, it revealed that the merging of the blowfish cryptographic method and the end of file steganography was not very effective because, based on the output testing with robustness criteria; it was proven that the message inserted into the image was damaged during extraction. The changes in the size of the original cover with the resulted stego image had increased file size with a ratio of 1: 5.5, meaning that each created stego image was five times the size of the original image.
Decision strategy for landslide event based on 4 parameters

Abstract Landslides are typically caused by heavy rain in some locations that have a certain slope of land compounded by deforestation or earthquakes. For instance, in 2018 there were 148 reported landslides in the Banjarnegara highlands, Indonesia. By using that fact, some research has been done. The research is about the indicator parameters of landslides by combining rain gauge sensors, soil moisture sensors, ground shift sensors and groundwater pressure sensors using Arduino Promini. The data from sensor is sent through LoRa Bee to the database server using NodeMCU ESP8266 which is connected to the Internet in real-time through access points. The data that has been sent to the server will be processed and displayed on the website. In this paper, the author devises an algorithm for analysing the data from each sensor to a decision-making strategy. The decision-making method for an early warning of landslides uses a decision tree that compares the measured parameters with a predetermined threshold of each sensor. After analysis and testing, this system is expected to provide early warning of the landslides quickly and accurately.
Importance of computer science in the results of the evaluation of higher education in Colombia

Abstract Information and communication technologies have transformed social behavior into teaching and learning processes, however, it is debated whether greater access to technology influences the quality of knowledge acquired by undergraduate students. This article aims to determine the incidence of information technology and communication tools in the results obtained in the Saber Pro 2017-2018 tests by administration and related students; these tests are the exams that the Colombian state performs annually to determine the quality of higher education in public and private universities. The achievement of this objective was carried out through an analysis of variance that consists in evaluating if there are significant differences in the results, according to the students who have a computer, have access to the Internet and the time in hours dedicated to this. The analysis of variance left as the main conclusion that the use of Information and Communication Technologies increases the chances of improving the results obtained by students.
An Access Abstraction Model for Mitigating the Insider Threat

The risk represented by the legitimate members of organizations with their access to valuable information and services continues to increase with the adoption of information technology-based services. Misuses of such access create costs in terms of losses to businesses, and in some cases human costs.
Lightweight Automated Structure Inference and Binding of Data Sources to Predefined Data Types

There is great variety and volume of data sources available on the Internet today. Software developers seeking to access such data and incorporate it into their programs have numerous libraries they can use to do so. However, in many contexts, such as rapid prototyping or lightweight scripting, these libraries are too heavyweight, requiring significant syntactic overhead or scaffolding in order to use them in a program. This paper presents a methodology (and implementations) to facilitate retrieval and dynamic binding of online data sources (in common formats such as XML, CSV, JSON, fixed-width, etc.) to programmer-defined data types with minimal syntactic overhead and no scaffolding. As such, the paper offers a particularly novel approach, among a continuum of existing techniques, towards enabling developers to access external data and convenient bind it to native data types in their programs.
El problema semántico de los emoticones. Una perspectiva legal

The general theory of law has historically analyzed the relationship between language and law and tried to provide solutions to the problems that this causes when interpreting the law. The new media presents challenges for these schemes; we now face problems posed not by words (which may be vague or ambiguous) but rather by virtual symbols. The question, then, is how to interpret them; can the emojis have legal transcendence or they are simple symbols? This paper is to emphasize that the law faces a new problem of interpretation.
Phase Retrieval Method for Phase-shifting Interferometry with Machine Learning

Phase contrast imaging attracts attention in the biomedical field thanks to higher contrast than absorption contrast. However, the phase retrieval for phase-shifting interferometry (PSI) often involves the problems, e.g., the noise, stepping error and phase wrapping. In the conventional way, each issue had to be addressed individually. In this paper, we propose the machine learning based method, which uses the neural network and learns features in an end-to-end manner. The proposed method can resolve the noise, stepping error artifacts and phase wrapping, simultaneously. The results are shown by numerical simulation.
The principles of adaptive control of a technical system using Cetlin probabilistic automata

Abstract This article examined the principles of adaptive control of a technical system using Cetlin probabilistic automaton. The study aims to reduce the learning time of the machine through the introduction of a progressive method for predicting short time series by the refined Brown method.
Mobile Android Based Geographic Information System (GIS) Software Development for Tourist Destination Seekers in Palembang City Using Rasch Model Measurements

Abstract Rapid change and growth of technology such as automatization and computerization in many types of business according to information technology communities and practitioners are demanding us to be well-prepared in facing the evolution like mobile devices especially android. Android is a mobile operating system used for touch screen based smart phones and computer tablets. The strength of GPS based android devices is in making it easy for users to access many kinds of information of tourist destinations consisting all facilities around the places. The development of this android based application is using Java Android programming language and designed by using RUP (Rational Unified Process) as the development method with Unified Modelling Language (UML) concept. The purpose of this research is to produce a Geographic Application for tourist guidance in Palembang city containing tourist objects list, public places list, transportations list, culinary places list and also other features that will help tourists to find the most effective and efficient tourist destinations. The Rasch Model measurements uses 74 respondents, to test the data using the Rasch Model measurements with the Ministep application. In the aspect of reliability, for person reliability the value is 0.89.0.90, producing a very good value. While for reliability items the value is 0.82 and 0.84 produces a good value. while the Cronbach alpha index also produces a Cronbach Alpha value yields a value of 0.93 (produces a very good value). Determination of sample size uses the Item Measure table based on the accuracy of confidence measurements (95%).
Performance Optimization of Cloud Application at Software Architecture Level

Due to the limited search space in the existing performance optimization approaches at software architectures of cloud applications (SAoCA) level, it is difficult for these methods to obtain the cloud resource usage scheme with optimal cost-performance ratio. Aiming at this problem, this paper firstly defines a performance optimization model called CAPOM that can enlarge the search space effectively. Secondly, an efficient differential evolutionary optimization algorithm named MODE4CA is proposed to solve the CAPOM model by defining evolutionary operators with strategy pool and repair mechanism. Further, a method for optimizing performance at SAoCA level, called POM4CA is derived. Finally, two problem instances with different sizes are taken to conduct the experiments for comparing POM4CA with the current representative method under the light and heavy workload. The experimental results show that POM4CA method can obtain better response time and spend less cost of cloud resources.
Arabic digit recognition using robust deep convolution neural network

Abstract Recently, digit recognition becomes one of interest problems for many researchers. However, Arabic digits have lack for such research. In this work, we used a robust deep convolution neural network (DCNN) to evaluate our collected Arabic digit dataset. We introduce substantial changes to CNN models to achieve superior results to prior work. Extensive experimental results are contacted to show the robustness of proposed models. Our detector achieves best current state-of-the-art results.
Possibilities for Applying Information of Computerized Car Systems and Devices Installed thereon in the Process of Investigation

The paper draws attention to the development of computerized car systems and the expansion of their functionality. However, according to the author, the use of information recorded in these devices for the criminalistic purposes in crimes investigation is clearly not receiving enough attention in science and in practice. The paper discusses the main range of systems that allow you to obtain forensic information, as well as the possibility for practical application of electronic information from computerized car systems. The author draws the conclusion on the possibility of a forensic investigation of computerized car systems using forensic developments in the field of electronic traces and electronic evidence. A correctly conducted study can allow you to get a dynamic threedimensional model of a criminally committed traffic accident, as well as other criminal events recorded by car sensors. The paper also examines the prospects for the study of so-called smart cars. An increase in the effectiveness of expertise in the production of integrated computer-aided technical research is noted.
Facial Expression Recognition Adopting Combined Geometric and Texture-Based Features

In recent facial expression recognition competitions, top approaches were using either geometric relationships that best captured facial dynamics or an accurate registration technique to develop texture features. These two methods capture two different types of facial information that is similar to how the human visual system divides information when perceiving faces. This paper discusses a framework of a fully automated comprehensive facial expression detection and classification. We study the capture of facial expressions through geometric and texture-based features, and demonstrate that a simple concatenation of these features can lead to significant improvement in facial expression classification. Each type of expression has individual differences in the commonality of facial expression features due to differences in appearance and other factors. The geometric feature tends to emphasize the facial parts that are changed from the neutral and peak expressions, which can represent the common features of the expression, thus reducing the influence of the difference in appearance and effectively eliminating the individual differences. Meanwhile, the consolidation of gradient-level normalized cross correlation and Gabor wavelet is utilized to present the texture features. We perform experiments using the well-known extended Cohn-Kanade (CK+) database, compared to the other state of the art algorithms, the proposed method achieved provide better performance with an average accuracy of 95.3%.
Oscillating between classically entangled state and separable state: an analogy between classical and quantum optics

In this paper, we study the possible realization of a classical system with quantum characteristics on the level of classical optics. Indeed, following Arrizon et al . [ J. Opt. Soc. Am. A 32 , 1140 ( 2015 ) JOAOD6 0740-3232 10.1364/JOSAA.32.001140 ], we first use quantum optics formalism to consider the propagation of two coherent states in a Kerr medium where the interaction between the two states is described by the cross-Kerr interaction. We then draw an analogy between the dynamical process of this structure and that of a Gaussian wave propagating in a quadratic gradient index medium. We demonstrate that by using this structure, we can generate a state that oscillates between a classically entangled state and a separable one.
Aquamotion welcomes back regulars following reopening

Following the State Government’s announcement of its COVID-19 Roadmap to Recovery, the City of Wanneroo has opened the doors to its indoor fitness and leisure centre Aquamotion.
Requirements modeling of Web services-based business processes

Purpose This paper reviews existing business process (BP) modeling languages that are widely used in the industry as well as recent research work on modeling and analysis of BPs in the service-oriented environment and Internetware-based software paradigm. BPs in such environment are different from traditional BPs due to loose coupling of partner services, dynamic and on-the-fly selection of partners and run-time process adaptability. The unique characteristics of these BPs require formal modeling of the requirements and constraints in each phase of their life cycle, including design phase, implementation and deployment phase and execution phase. Design/methodology/approach The paper first provides a categorization of typical user requirements in each phase of the BP life cycle. Then a detailed comparison of the selected languages with respect to their requirement modeling and analysis capabilities in each of the identified categories is provided. The paper also discusses new requirements engineering research challenges arising from future software needs and emerging trends in software engineering in the context of Web-services-based BPs and Internetware. Findings There is a need to have a framework that provides support for user requirements modeling and analysis for all the phases of BP life cycle in an integrated manner. Such a framework would be useful not only in resolving the inconsistencies between requirements across phases but also in addressing the issues related to BP evolution due to changes in user requirements over time. Moreover, with the Internet of things (IoT) adoption in BPM, there is a need to have an integrated environment that provides support for capturing the resilience requirements of enterprise BPs as well as the mobility constraints of the underlying IoT devices. Originality/value This paper reviews existing BP modeling languages and frameworks and discusses the new requirements engineering research challenges arising from future software needs and the emerging trends in BP management in the service-oriented environment and Internetware-based software paradigm.
An Improved Collaborative Filtering Recommendation Algorithm Based on Fusion Time Factor

Traditional collaborative filtering recommendation algorithms only focus on the user's historical behavior information, using similarity measurement method to obtain the user group with similar behavior to the target user and producing the recommendation result. However, the recommendation accuracy is low and the recommendation result is relatively simple and lacks novelty. In practice, the user's interest changes dynamically with time, and traditional collaborative filtering algorithms cannot reflect the user's interest changes in time. For this problem, this paper proposes an improved collaborative filtering algorithm based on traditional collaborative filtering algorithm. When analyzing the user's historical behavior data information and establishing user behavior characteristics, consider the influence of time factors on the user recommendation results. Experiments show that the improved collaborative filtering algorithm with fusion time factor has higher accuracy than the traditional collaborative filtering algorithm, and its recommendation results meet the needs of users, which proves the effectiveness of the algorithm.
TIDY: Publishing a Time Interval Dataset with Differential Privacy (Extended abstract)

Log data from mobile devices usually contain a series of events with time intervals. However, the problem of releasing differentially private time interval data has not been tackled yet. We propose the TIDY (publishing Time Intervals via Differential privacY) algorithm to release time interval data under differential privacy. We use the frequency vectors as a compact representation of the time interval data to reduce the aggregated noise. We also develop a new partitioning method adapted for the frequency vectors to balance the trade-off between the noise and structural errors. Our experiments confirm that TIDY outperforms the existing algorithms for releasing 2D histograms.
Cooperating in video games? Impossible! Undecidability of Team Multiplayer Games

We show the undecidability of whether a team has a forced win in a number of well known video games including: Team Fortress 2, Super Smash Brothers: Brawl, and Mario Kart. To do so, we give a simplification of the Team Computation Game from Hearn and Demaine's “Games, Puzzles, and Computation” [7], and use that to give an undecidable abstract game on graphs. This graph game framework better captures the geometry and common constraints in many games and is thus a powerful tool for showing their computational complexity.
Sentiment Analysis for Predicting the Popularity of Web Series

With the rise of the social networking era, there is a sudden and great increase in user-generated content. Millions of people share their daily life and status by blogging on social media like Twitter. So it’s a great source to analyze sentiments by simply using the text of social media and simple manner of expression. Due to the advancement of technology and easy availability of internet people are getting attracted towards the web television series due to the originality of the content and free of commercials breaks. Netflix is also one of the subscription-based videos on demand site is popularizing and got a sustainable advantage over traditional networks these days. This paper focuses on four popular comic web series and performed sentimental analysis for the prediction of the most popular web series among the four cartoon series.
A Novel Method for Unsafe Driving States Detection

With the increase in vehicle consumption in recent years, traffic accidents have become the most important cause of premature death all over the world. In particular, the unsafe driving state like fatigue and distraction, which lead to around 90 percent of crashes. In this paper, an unsafe driving state detection method based on deep learning is proposed. First, the optimized MTCNN method is used to detect human face and locate facial feature points, the optimized MTCNN method accelerating the speed up to 27 times. Second, a new ERFP method is used to achieve more accurately facial feature points locating. Meanwhile, a simple and efficient method FOD is proposed to detect the facial orientation by analyzing the change of the relative position between the nose tip and facial position. Third, this paper also built the new unsafe driving state dataset UDS for training the classification model of the status of eyes and mouth. Finally, the different standards are designed to detect the different unsafe driving states in experiments, compared with previous methods, the method proposed in this paper got a better result in drivers' unsafe state detection.