Reviewerly/exHarmony huggingface dataset:
Smart Tiles for Elder Tracking and Fall Detection System

Fall disclosure for progressively settled and indefatigable is an essential association that has the limit of developing autonomy of seniors while confining the dangers of living alone. It has been a working examination point by virtue of the way where that human organizations industry has an imperative energy for things and advancement of fall territory structures. Inferable from the constant quick advancement in recognizing and remote correspondence degrees of progress, fall unmistakable confirmation structures have wound up being conceivable. They award seeing fall occasions for the old, checking them, and as such giving basic assistance at whatever point required. This paper depicts the driving work of seeing falls in free living senior townhouses using power sensors and 3-center point accelerometers confirmed under dubious tiles. The power sensors permit seeing progressively arranged people's falls, discovering, following and seeing human activities (walking, standing, sitting, resting, falling, and the developments between them). Everything considered, the revelation exactness on veritable data contains false alerts beginning from falling and lying positions. To light up this issue, we propose the mix between the power sensor estimations and the accelerometer sensor decisions. In like manner, the structure exactness is exquisite and the results show that the proposed approachs are productive, and they can be plausibly used in an authentic senior after and fall divulgence system.
Psychological Readiness for Mobile Learning Among Maldivian Students at Higher Education Institutions

Objective - Mobile learning had widely impacted higher education, providing technology enabled educational opportunities to the mobile-first learners of the millennium, anytime, anywhere. The adoption of mobile technology rapidly increased among higher education institutions of Maldives, changing the psychological perception of distance learners who were located in different atolls of the country. Methodology/Technique - This paper was developed to explore psychological readiness of institutional distance learning students to adopt mobile learning in Maldives. Using quantitative approach, the research was conducted among the distance learners from three key higher education institutions of Maldives. Contributing to the e- questionnaire, three hundred and forty-three (n=340) students expressed their psychological readiness to adopt mobile learning in Maldives. Data collected using mobile technology was analysed using the analysis summary retrieved from Google forms and SPSS. Finding - The analysis revealed that majority of the students of Maldives higher education institutions were acquainted and psychologically ready to adopt mobile learning as a convenient mode of delivery. Novelty - Thereby, it can be said that students were willing to welcome mobile learning enhanced by mobile technology and were psychologically ready to adopt the emerging shift in the paradigm. Type of Paper - Empirical. Keywords: Mobile learning, psychological readiness, paradigm shift, higher education institutions, Maldives JEL Classification: I21, I23
LDAP-Filter

No AccessOpenLDAP in der PraxisMay 2020LDAP-FilterStefan Kania, Andreas OllenburgStefan KaniaSearch for more papers by this author, Andreas OllenburgSearch for more papers by this authorhttps://doi.org/10.3139/9783446465312.008SectionsAboutPDF ToolsAdd to FavoritesDownload CitationTrack CitationsCopy LTI LinkPDF key 'share (en)' returned an object instead of string.FacebookTwitterEmailLinkedIn previous chapternext chapter FiguresReferencesRelatedDetails 2020Pages: 91-97Print ISBN: 978-3-446-46387-5eISBN: 978-3-446-46531-2 Copyright & Permissions© 2020 Carl Hanser Verlag GmbH & Co. KGPDF downloadLoading ...
Introduction to Robotics

The word robotics can mean a lot of things. For some people, it is anything that moves by itself; kinetic art is robotics. To other people, robotics means something that is mobile or something that can move itself from place to place. There is actually a field called mobile robotics; automatic vacuum cleaners, such as a Roomba or a Neato, fall into this category. To me, robotics falls somewhere in between kinetic art and mobile robotics.
A Study on the Effect of Individual Career Development Activity on the Career Satisfaction

This study is to suggest implications for individual career development activities.The questionnaire was distributed and collected among 305 people who have had more than one career development activity. The collected data verified the adequacy of the structural equation modeling and its cause-and-effect relationship to each concept.Social networks, hobbies, and acquiring the certificates do not show any significant relationship to career development, but achievement has a significant effect on it. It was found that two jobs have a significant effect on both career development and sense of achievement. It said that career development and sense of achievement have a significant effect on career satisfaction. Since career development and sense of achievement both effect career satisfaction while social networks, hobbies, and acquiring the certificates have a significant impact only on sense of achievement, the main implication of this study is that, by linking the above variables to career development, it is necessary to strengthen the compensation system and support measures that can induce career development in order to improve career satisfaction ultimately. It gives directions to those who want to develop activities..
Breaking Down of 51% Double Spend Attack (DSA) in Blockchain Technology

Today the emerging trend and innovative technology is block chain technology. The actual question is how to manage this. The basic concept behind this is mining. Block chain is equal to governance. It is basic type of governance. It governs a book called ledger which contains information. Here we focus on double spend attack in block chain. The attackers has a space to block the new transactions from gaining access to acknowledgements. They make half payments between some or all users. It is even possible to reverse transactions when using the network or holding the complete control of the network thus spending the coins twice which means double spend coins. This attack always exist as a thread and users are panic about their transactions being used by a corrupted miner. The solution for this malicious mining is Proof of Work (PoW) which is proved to be not sufficiently decentralized or secure. So here we are focusing on Proof of Stake (PoS) concept which is a response to the treat of centralization.
Blockchain Technology

More than hundred countries have experienced WannaCry Ransomware cyber-attack in 2017. This attack demanded around $300 of BitcoinBitcoin cryptocurrencyCryptocurrency from users to retrieve their data. There onwards, Blockchain technology and cryptocurrency are catching the attention of everyone. Blockchain is a growing digital record keeping register in the distributed form which cannot be altered. In case of Blockchain, no central authority is needed. Modification of the data or assets stored on Blockchain is highly difficult or nearly impossible. All the data available on Blockchain can be publicly seen by everyone. It cuts down the excessive costs required in the conventional manual record keeping registers. Blockchain technology has lot of bonus points including integrity, write access, reduced cost, trust, etc. With Blockchain technology, various tokens are available such as currency tokens, asset tokens, utility tokens, and equity tokens.
Statistical Analysis of Literacy Rates Using Indian Census Data

There exist many prevalent issues in today’s world, many of which seem to have no feasible solution. One such issue is the disparity in the education provided between males and females. Gender equality is an important topic for discussion and reform in the modern world, and yet a full, thorough understanding of the intensity of the issue is yet to be elicited. Using a combination of modern computational statistical analysis and the vast, extensive trough of census data, this paper provides a framework for gaining a better viewpoint on the issues plaguing us currently, thus taking a step closer to eradicating them.
Foreign Students’ Satisfaction of Russian Educational Environment in 2019

the article gives a review on foreign student’s satisfaction of Russian universities. A general assessment of the conformity of training, the current degree of satisfaction of students in socio-cultural adaptation, training requirements and difficulties in admission to training. A recommendation is given on organizational changes in universities. It will be useful to all employees of the international departments of universities, including professors and recruiting companies
A flexible operating tool to provide an efficient project's staffing and resource allocation

Resource allocation is paramount for the success of complex projects; many allocation and staffing models have been proposed in the literature, but none of them has found its way into practice yet. Hence, we propose a tool to provide an efficient project's staffing and resource allocation, with the goal to create cohesive teams, and an almost perfect matching among time/quality requirements and resources' skills. To achieve this objective, the tool makes use of a specific heuristic that reproduces the reasoning of the project manager, using logical rules based on sorting and prioritising criteria, both for tasks and resources. To validate the tool, we applied it to a comprehensive set of past projects, completed by a consultant company over the past five years. Solutions provided by our tool were assessed by a team of experienced project managers, and they were found superior to the ones originally implemented by the company.
Avoiding normalization uncertainties in deep learning architectures for end-to-end communication

Recently, deep learning is considered to optimize the end-to-end performance of digital communication systems. The promise of learning a digital communication scheme from data is attractive, since this makes the scheme adaptable and precisely tunable to many scenarios and channel models. In this paper, we analyse a widely used neural network architecture and show that the training of the end-to-end architecture suffers from normalization errors introduced by an average power constraint. To solve this issue, we propose a modified architecture: shifting the batch slicing after the normalization layer. This approach meets the normalization constraints better, especially in the case of small batch sizes. Finally, we experimentally demonstrate that our modified architecture leads to significantly improved performance of trained models, even for large batch sizes where normalization constraints are more easily met.
Experience in Mapping Technogenic Oil Pollution by Geophysical Methods

Abstract Summary The paper presents the results of geophysical studies using various geophysical methods for mapping technogenic hydrocarbon contamination of soils
Charged System Search Algorithm

This chapter consists of two parts. In the first part an optimization algorithm based on some principles from physics and mechanics, which is known as the Charged System Search (CSS) []. In this algorithm the governing Coulomb law from electrostatics and the Newtonian laws of mechanics. CSS is a multi-agent approach in which each agent is a Charged Particle (CP). CPs can affect each other based on their fitness values and their separation distances. The quantity of the resultant force is determined by using the electrostatics laws and the quality of the movement is determined using Newtonian mechanics laws. CSS can be utilized in all optimization fields; especially it is suitable for non-smooth or non-convex domains. CSS needs neither the gradient information nor the continuity of the search space.
Speaking in Good Time

The chapter discusses how interlocutors jointly optimize the timing of their contributions. It considers how they interleave their dialogue plans so that the steps are properly sequenced (e.g., an answer follows a question). It then considers how their contributions are interleaved so as to avoid overlap but with minimal gaps. Finally we consider how interlocutors entrain their speech rates to support coordinated speech planning and production.
Log Pearson III Distribution and Gumbel Distribution Model for Rainfall Data in Pekanbaru

Rainfall is very important for human life. Both high and low rainfall can cause some problems, ranging from flood to drought. We can see that flood can be found in several big cities, and one of them is in Pekanbaru. Therefore, rainfall data analysis is needed to know the model and the pattern of rainfall distribution. In turn, the result can be used as a consideration for the development of the city or the formulation of policy in Pekanbaru’s governance. In this study, Log Pearson III distribution and Gumbel distribution model were used to analyze data of rainfall in Pekanbaru from January 2011 to April 2017. The purpose of this study was to determine the best rainfall model among Log Pearson III and Gumbel Distribution. To estimate parameters from both models, we used Maximum Likelihood and Newton Rephson method. Based on the use of the AIC and BIC test, this study results showed that Log Pearson III is better than Gumbel distribution in modeling the rainfall data of Pekanbaru.
Child Pornography Websites on the Darknet

Cybercrime has been moving to the darknet which provides privacy and anonymity to users. Despite international efforts to eradicate child pornography, websites to distribute lurid materials are found to be resilient. Due to the significance of the criminality, law enforcement authorities have taken covert measures to dismantle the leadership of these websites, focusing on arresting the organizers and core members. In this paper, two cases involving child pornography websites were examined to disclose how these websites were structured and managed as well as investigation strategies and tactics employed by investigation agencies. Some similarities were identified during pre-arrest and after-arrest stages for an investigation goal and evidence verification, respectively. However, during a deanonymisation stage the two agencies used different investigation strategies to approach and arrest the target criminals. It is very likely that darknet websites will be managed in diverse manners, or that more anonymity and encryption will make pornography circulation structure invisible and unreachable. In this study, it was argued that perfect anonymity is not provided to the darknet users and that investigation agencies should make technical and social engineering efforts to deanonymise identities of criminals.
Indicator minerals of CL-25 kimberlite pipe, Slave Craton, NWT, Canada

CL-25 kimberlite pipe was discovered in September of 1994 in the territory of the Slave Craton, North West Territories of Canada.This pipe represents a new kimberlite cluster located approximately 100 km to the South from the well known Lac de Gras kimberlite field and related with regional fault zone of south¬ west -north-east direction containing a number of doleritic dykes sharply reflected in the magnetic field and subparallel to the MacDonald s fault zone which delimits the Slave Craton to the South-East.CL-25 pipe is composed by intensively altered kimberlite breccia which is highly enriched with xenogenic material represented mainly by different types of metamorphic and magmatic rocks of the crystalline shield.High amount of xenogenic and contaminated material in this breccia is reflected in chemical composition of this rock which is significantly different if compare with composition of classic kimberlite: Si02=44.3-45.5wt.%;TiO2=0.93-1.82wt.%;Al203=7.17-8.46wt.%;Fe as Fe2O3=6.40 9.47wt.%;MnO=0.11-0.13wt.%;MgO=17.6-21.4wt.%;CaO=1.79-3.12wt.5;Na20=0.04-0.48wt.%;K20=86-2.25wt.%;P2O5=0.19-0.22wt.%;LOI=11.5-15.0.Analysis of specially selected material of this breccia without the visible fragments of xenogenic matter shows some differences in composition if compare with data presented above and more similar to the kimberlite composition: SiC>2=39.5wt.%;Ti02=1.02wt.%;Al203=4.44wt.%;Fe203=6.23wt.%;MnO=0.12wt.%;MgO=23.9wt.%;CaO=5.16wt.%;Na20=0.02wt.%;K20=1.19wt.%;P2O5=0.27wt.%:LON18.22.Very interesting composition has the rock of the dyke which was drilled in the body of CL-25 pipe: SiO2=5.01wt.%;Ti02=1.47wt.%;Al203=2.74wt.%;Fe2O3=4.08wt.%;MnO=0.20wt.%;MgO=0.21.9wt.%;CaO=24.9wt.%;Na2O<0.01 wt.%; K2O=0.12wt.%;P2C>5=0.21wt.%;LOI=39.3wt.%.This altered rock has not visible xenogenic material.We have studied in detail the composition of garnets, picroilmenites, chromespinels and clinopyroxenes from the CL-25 kimberlite pipe.Garnets are represented by: a) chrome-pyropes of different parageneses; b) garnets from disintegrated rocks of crust; c) garnets of different types of eclogites.Cr-pyropes include: predominate pyropes of Iherzolite paragenesis (Cr2O3=0.2-13.3wt.%,CaO=3.5-7.8wt.%);subcalcic Cr-pyrope related with 1) harzburgite paragenesis (Cr2C3=3.6-14.2wt.%,CaO=2.8-5.7wt.% and very low admixtures of Ti, Na and andradite molecule), 2) metasomatized and Na-enriched Iherzolite paragenesis (relatively high admixtures of Na20 -up to 0.18wt.%,Ti03 -up to 0.61 wt.% and
Internal Adaption based Nature Inspired Algorithm for Application in Software Engineering

In this paper, new mutation strategies are proposed to improve the accuracy of the cost estimation by COCOMO's tuning parameters using the Internal adaption based mutation operator for differential evolution algorithm (IABMO Algorithm). The proposed method provides more promising solutions to take the lead evolution and helps DE abstain the circumstance of stability. The proposed algorithm applied software cost estimation and improve the performance of the initial phase for software engineering. This approach is used for precise prediction and reduces the error rate for the initial phase of software development phase projects. The software cost estimation based IABMO algorithm has been capable of a better for effort, MRE, MMRE, and prediction.
Estimating Image Enhancement Factor (IEF) using a Fuzzy Set &amp; Noise Level of Salt-Pepper Noise for Gray Level Imaging

Improving a noisy image is a necessary task when processing digital images. To correct the noise content in the natural image, adding known noise to the image before processing. Therefore, the simulated noise is added to the image just to understand the noise elimination process. A filtering technique that can be applied to eliminate noise from images. After observing the results of the quality measurement values, it is concluded that the filter works best to eliminate image noise in all chosen noise models. Eliminating noise from the image is one of the deep challenges in the area of image processing and computer vision, where the core objective is to estimate the experimental image, smoothing noise from a noise-impure version of the image. Image noise can be caused by unlike intrinsic and extrinsic conditions that are repeated not possible to avoid in realistic state.. Therefore, denoising image plays an vital role in a ample range of aim such as image restoration, visual tracking, image registration, image segmentation and classification, where to obtain image content The original is crucial for performance solid. Noise reduction is the process of eliminating noise from images; Each pixel in the image will change from the original values in a small amount. A noise elimination algorithm is to achieve noise reduction and resource preservation, but due to the limitations of the methods, it is blurred. The noise in different pixels can be correlated or not, because noise modeling is a very difficult task. We observed that the performance of the proposed study's diffuse set and the 3x3, 3x5, 2x3 size filter windows, the adaptive weighted median filter and the median filters and also adaptive fuzzy filter were used to reduce the salt and pepper noise filters and the elimination context noise, the most relevant value Accuracy is recovered. Finally, our results are compared with the image improvement factor (IEF), the mean square error (MSE) and the peak signal-to-noise ratio (PSNR)
Jazz Guitar

Throughout the history of jazz, the guitar has been an omnipresent voice as a rhythm section instrument and a solo voice. Having a strong guitarist in any jazz ensemble is a benefit and significantly increases the breadth of material that an ensemble can effectively perform. Taking a student with limited notational staff reading and chord vocabulary on the journey toward being a well-functioning guitarist in a jazz ensemble is no small feat! By understanding guitar function in jazz and melodic technique best practices, school music teachers can have a positive impact on young guitarists. This chapter addresses the technical possibilities/limitations of the guitar, diagnoses the needs and strengths of a young guitarist, recommends best practices, and provides a hands-on demonstration of learning through notated melodic and chordal examples.
iProov offers Eurostar a ‘world first’ biometric corridor

London-based iProov is developing an innovative facial recognition system for the high-speed Eurostar train service that runs through the Channel Tunnel between the UK and France.
Umicore acquires phosphine-bearing ylide ligands from Ruhr University Bochum

Sound transmission characteristics of panels have been extensively examined which is often quantified by transmission loss. Although acoustic materials are usually applied to passive noise solutions. In the present paper, the influence of sound-absorbing materials on the transmission loss of double-walled panels has been studied theoretically. An analytical method based on statistical energy analysis technique (SEA) is employed for predicting the transmission loss of double-wall steel and aluminum panels. Three commercially available acoustic materials, ie., polyurethane, glass wool, and melamine foam are chosen for investigation.
The Prediction of Heart Disease using Machine Learning Technique

Medical errors are generally costly and harmful. There are many deaths worldwide every year. Clinical decision support systems provide opportunities to reduce medical errors and improve patient safety. Certainly, one of the most important aspects of applying such a system is the diagnosis and treatment of heart disease. Machine learning technology is implemented to analyze different kinds of heart-based problems. For this, this study essentially had two primary goals. Firstly, this paper intends to understand the role of variables in heart disease modeling better. Secondly, the study seeks to evaluate the predictive performance of the decision trees. Based on these results, first, men seem to be more susceptible to heart disease than women. Age, chest pain type, resting blood pressure, serum cholesterol, fasting blood sugar, maximum heart rate achieved, exercise-induced angina, ST depression induced by exercise relative to rest, the slope of the peak exercise ST segment, and the number of major vessels also show increased odds of having heart disease. Second, for the full model, the accuracy rate is 0.873, which implies that the error rate is 0.127. Among the patients who predicted not to have heart disease, the accuracy that would not have heart disease was 85.43%, and the accuracy that had heart disease was 89.10% among the patients predicted to have heart disease.