Reviewerly/exHarmony huggingface dataset:
Efficient yet Robust Privacy Preservation for MPEG-DASH-Based Video Streaming

MPEG-DASH is a video streaming standard that outlines protocols for sending audio and video content from a server to a client over HTTP. However, it creates an opportunity for an adversary to invade users’ privacy. While a user is watching a video, information is leaked in the form of meta-data, the size of data and the time the server sent the data to the user. After a fingerprint of this data is created, the adversary can use this to identify whether a target user is watching the corresponding video. Only one defense strategy has been proposed to deal with this problem: differential privacy that adds sufficient noise in order to muddle the attacks. However, that strategy still suffers from the trade-off between privacy and efficiency. This paper proposes a novel defense strategy against the attacks with rigorous privacy and performance goals creating a private, scalable solution. Our algorithm, “No Data are Alone” (NDA), is highly efficient. The experimental results show that our scheme is more than two times efficient in terms of excess downloaded video (represented as waste) compared to the most efficient differential privacy-based scheme. Additionally, no classifier can achieve an accuracy above 7.07% against videos obfuscated with our scheme.
Applying Human “Rules of Dialog” to Reach Conversation Resolution

This is the first chapter of Part 3, where you learn in depth the ins and outs of voice design and development, one key topic at a time. Don’t sweat the details might be good advice for life in general, but as you’ve started to see, in voice development it’s all about the details. To make a conversational UI seem “smart,” it can’t only make the voice sound human, add conversational phrases, recognize and understand what the user said, get the context, and know about that user and about the world in general—it has to do all those well to seem at least as smart as your average 3-year-old.
ВЛИЯНИЕ ЦИФРОВИЗАЦИИ НА ЭФФЕКТИВНОСТЬ НЕПРЕРЫВНОГО ОБРАЗОВАНИЯ СПЕЦИАЛИСТОВ ДЛЯ ИНДУСТРИИ 4.0

Digitalization of continuing professional education for Industry 4.0 specialists is caused by the contradiction between the growing need for specialists’ skills development in Industry 4.0 and the impossibility of traditional education to realize mass training of specialists in conditions of their intensive labor activity, rapid updating of production technologies, and digitalization. Meeting the educational and professional needs of specialists, a digitalization model was proposed that included: informing of potential learners about advanced training programs, electronic educational environment, electronic educational content, electronic communications for educational and pedagogical interaction, and digital tools. The measures to increase digital literacy of learners are offered. The model was tested in empirical research, involving more than 4000 learners. To solve the research tasks observation, questionnaires, study and analysis of the students' outcomes were used. The indicators achieved statistically important difference that is 1.2–2 times compared with the indicators of previous years.
Cloud Computing for MATLAB and R Users: Part II – Transferring Data and Cloud Storage

Cloud-based computing has tremendous potential for academia in general and researchers in particular. The ability to store, read and manipulate large dataset is increasingly important to be on the cutting-edge of research. While most researchers have extensive programming skills, they generally are not computer scientists. A number of cloud-based, virtual work spaces have been developed which can bring enormous computing advantages over any desktop or laptop. However, the instructions to get up and running in the cloud are often overwhelming, and require a significant investment of time. There is an initial steep learning curve associated with developing a high performance computing environment that several times becomes an obstacle, preventing many from benefitting the most from using the cloud. This paper seeks to demystify the process and get the reader up and running very quickly. Once this initial process is over and the reader is proficient on these issues, performing computational chores that would take days on a desktop can be done in minutes. We next show the way the readers can implement their research using two well-known computer programs, MATLAB and R. Part II provides an in-depth instruction on using Amazon Web Services (AWS) for transferring data and cloud storage.
Optimization of a Stochastic Number Generator Using D Flip Flop

Escalating development in science and technology with exponential demand for gadgets and devices towards smart, intelligent and effective implementation for sustainable livelihood is the need of the society. The demand has fueled for improvising hardware and its design for enhanced computational speed, less latency, less power consumption, low cost involved in fabricating these hardware components. One such approach is stochastic computing, although developed long back, still the field is at naive and rudimentary stage mandatory incorporation of latest circuit techniques and methodologies. The objective of our study is to incorporate D-Flip Flops (DFFs) within the stochastic number generator (SNG) architecture and assess the performance of stochastic circuit to break haven the cost involved in hardware fabrication, power consumption etc. Our study compared the positioning of DFFs within and outside SNG and compare the power consumption and area occupancy relating with efficiency. Experimental investigations revealed that DFFs within the SNG architecture was more optimal, effective and efficient, catering the needs and objectives of our study. Since our investigations is at preliminary stage, further warranting and validation is sought to take over to next stage of implementation.
Tecnología aural, fenomenología y matrices de datos en el Tratado de los objetos musicales de Pierre Schaeffer: Contribuciones para una Ciencia de lo que se oye

In this presentation I propose to present three theses about Pierre Schaeffer's Treatise on Musical Objects. The first is the idea that this author is more a follower of the innovations of aural technology, than of the musical innovation of the 20th century. The second is to review Schaeffer's links with phenomenology. The third is to articulate what Schaeffer called the object-structure pair, make a reading of it from the data matrix systems that Juan Samaja theorized and, in turn, link the phenomenological method in Schaeffer with the data matrices. .
Peningkatan Kapasitas Guru Akuntansi SMK Negeri 1 Lhokseumawe Dalam Penggunaan Aplikasi MYOB Accounting

Computer accounting application MYOB Accounting is an accounting application designed to facilitate the presentation of a company's financial statements. Computerized accounting with MYOB Accounting is one of the compulsory subjects in all SMKs in Indonesia, especially in Accounting. This science and technology application activity aims to provide training in the use of the MYOB Accounting application for accounting teachers at SMK Negeri 1 Lhokseumawe. The target of this activity is to increase the capacity of accounting teachers in SMK Negeri 1 Lhokseumawe in understanding the MYOB Accounting application. This training was conducted for all Accounting teachers at SMK Negeri 1 Lhokseumawe City. The training method uses a practical method. The training was carried out in the laboratory of SMK Negeri 1 Lhokseumawe City. The training materials provided are opening setup, recording transactions, and presenting reports. and report preperation.
Parsimonious Feature Extraction Methods: Extending Robust Probabilistic Projections with Generalized Skew-t

We propose a novel generalization to the Student-t Probabilistic Principal Component methodology which: (1) accounts for an asymmetric distribution of the observation data; (2) is a framework for grouped and generalized multiple-degree-of-freedom structures, which provides a more flexible approach to modelling groups of marginal tail dependence in the observation data; and (3) separates the tail effect of the error terms and factors. The new feature extraction methods are derived in an incomplete data setting to efficiently handle the presence of missing values in the observation vector. We discuss various special cases of the algorithm being a result of simplified assumptions on the process generating the data. The applicability of the new framework is illustrated on a data set that consists of cryptocurrencies with the highest market capitalization.
Research on Bad Driving Detection Based on Behavior Recognition

Dangerous driving behavior is considered to be the direct or indirect reason of road accidents.Although artificial video surveillance is good to prevent bad driving, it wastes too much time and manpower.How to effectively identify behavior becomes the focus of the research.In recent years, deep learning showed the huge advantage in the field of computer vision.This paper adopt a number of deep learning network models, mining video integration of space and time features, introduction of analogy in human visual attention mechanism, improve the model deeply, using the LSTM to accurate and efficient video behavior analysis technology.
Preparing Students for the Digital World The Essential Role of Technology in Primary Education

The purpose for this project was to examine the requirements for Primary School children when progressing from Key Stage 2 into Secondary School (Key Stage 3) and then to build an e-learning application to teach and test children on these requirements.The project began with a Literature Review that examined the educational requirements as set out in Governmental requirements; this was then followed by a look at teaching methods for children and software development styles and approaches.This was then followed by the design and implementation of the e-learning application the author wished to create. This had two separate designs, one for boys one for girls. The reasoning behind this design approach was the author’s idea based upon her learning throughout this course as well as the findings throughout the research section of this project.After building and deploying the application the author then proceeded to evaluate the application by having a group of primary school children to test the application and provide an evaluation. An evaluation was also sought from teachers. This collective feedback was then utilised to conduct an evaluation of the author’s project.The findings were that the application was highly desirable and received very high ratings. The main constructive feedback was that that some children were put off using the application due to the testing element; something that is not common in primary education and that some elements of the application were a little difficult for the age group. Demo URL: http://ghada.x10.mx/gender_select.htm
A Methodology for Applying Machine Learning Algorithms in the Medical Industry

In our day-to-day life, we use lots of machine learning (ML) techniques and applications for farming, Medical care, Products Recommendations, stock marketing, Social Media (Facebook, LinkedIn), Traffic flow Alerts (Maps), Transportation, and Commuting (Uber, OLA), etc. Machine learning is a type of learning in which the machine learns by itself without explicitly programmed it. This is the type of application of artificial intelligence that provides the facility with the facility to spontaneously learn and develop from their understanding. This research paper discusses the potential of applying machine learning skills in the medical sector. ML is organized in mainly four learning forms. Supervised learning contains labeled information when unsupervised learning contains unlabelled data. Semi-supervised learning is a combination of supervised and unsupervised learning. Reinforcement learning is a type of learning method that works together with its environment by generating actions and at the same stage determining errors and rewards. Trial & error search and delayed reward are all the most relevant features of reinforcement learning. ML is utilized in the healthcare sector like robotic surgery, Health Imaging Analysis, Sharing Patient Data, Drug Discovery, and Medical Imaging Diagnosis. Here we are studying in brief with several techniques and checking which algorithm is more accurate with less time consumption. This research paper summarizes some machine learning techniques such as K-nearest neighbor, support vector machine, random forest, a decision tree for disease prediction and disease detection. This work supports the dropping research gap between machine learning and the medical sector.
Hubungan Pengguna Air Sungai Dengan Keluhan Penyakit Kulit Pada Masyarakat Desa Kaya Pangur Kecamatan Deleng Pokhkisen Kabupaten Aceh Tenggara

Water is a natural resource that is needed for the livelihoods of many people, even by all living things. Therefore Water resources must be protected so that they can be properly utilized by humans and other living things. Of the many needs of living things on this earth, water is a very important requirement for their survival. Based on disease data in Aceh Province in 2018, the number of skin disease patients reported for all age groups in the 2018 period reached 78,641. Slightly decreased compared to 2017 when the number of cases reached 88,913. Meanwhile, based on data obtained from the Southeast Aceh District Office, it shows that skin disease is still dominant in the community. The number of sub-cutaneous skin disease patients for all age groups reported in the 2017 period reached 260 cases.This study aims to determine the relationship between River Water Users and Complaints of Skin Diseases in Kaya Pangur Village Communities, Deleng Pokhkisen District, Southeast Aceh Regency in 2019. This research used cross sectional. The results of the research obtained from Kaya Pangur Village, Deleng Pokhkisen District, Aceh Tenggara Regency can be seen that river water user factors are factors related to skin complaints because the p-value is ≤ 0.05. This research still requires further study on solutions to prevent skin diseases, especially in river water users in the Kaya Pangur Village area, Deleng Pokhkisen District, Southeast Aceh Regency. So that the level of public health will continue to increase.
Multi-level fluid monitoring to understand the origin of transients

&amp;lt;p&amp;gt;Anomalies in timeseries are frequently reported in the context of earthquake precursor studies. The state of knowledge can be summarized as follows: (i) significant anomalies exist, (ii) seismo-tectonically induced anomalies might exist, (iii) anomalies of non-tectonic origin exist and may look very similar to tectonic ones. Thus, presumably only a fraction of all reported precursors is real in the sense that they are of seismo-tectonic origin. A key problem in earthquake prediction research is to understand the origin of an anomaly and thus the separation of internal and external drivers like e.g. rainfall.&amp;amp;#160;&amp;amp;#160;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;State-of-the-art fluid monitoring techniques allow for a high temporal resolution compared to the low-resolution discrete sampling approach used in the last decades. A unique approach will allow to monitor ascending fluids along a vertical profile in a set of drillings from a depth of a few hundred metres to the surface. This setup can provide hints on the origin of temporal variations related to the opening of fault-valves, admixture of crustal fluids to a background mantle-flow or the release of hydrogen during fault rupturing. Gas migration velocities can thus be measured directly from the arrival times of anomalies at different depth levels. In addition, potential admixtures of mantle fluids with crustal or meteoric fluids during the ascent to the Earth&amp;amp;#8217;s surface can be quantified.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;A prototype of a multi-level gas monitoring system has been implemented at a mofette. Mofettes are gas emission sites where CO2 ascends through long-lived, narrow channels from the deep crust and possibly the Earth&amp;amp;#8217;s upper mantle and thus provide natural windows to magmatic processes at depth. The primary objective of our research on mofettes is to clarify physical links between fluid properties, their pathways and the relation to swarm earthquakes. The Hartou&amp;amp;#353;ov mofette field with an estimated daily CO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; flux between 23 and 97 t over an area of about 350,000 m&amp;lt;sup&amp;gt;2&amp;lt;/sup&amp;gt; has been chosen as a key site in the frame of the ICDP project: &amp;amp;#8220;Drilling the Eger Rift: Magmatic fluids driving the earthquake swarms and the deep biosphere.&amp;amp;#8221; It is located in the Cheb Basin, which terminates the Czech part of the Eger Rift to the West and is known for recurring earthquake swarms and mantle degassing. Gas and isotope compositions will be continuously analyzed in-situ at different depth levels (30 m, 70 m, 230 m) reached by three adjacent boreholes.&amp;lt;/p&amp;gt;
PENERAPAN MODEL PEMBELAJARAN KOOPERATIF TIME GAMES TOURNAMENT BERBASIS ONLINE DIMASA PANDEMI COVID 19 UNTUK MENINGKATKAN HASIL BELAJAR SISWA SEKOLAH DASAR

The success of teachers in conducting online learning in the Covid-19 pandemic situation depends on the ability of teachers to innovate in designing and concocting materials, learning methods, and what applications are in accordance with the materials and methods. Creativity is the key to success for a teacher to be able to motivate students to stay enthusiastic about learning online (online).  The Time Games Tournament TGT learning model is a model that can be applied in online learning to eliminate children's boredom and provide learning variations.  In this study, the research targets were the fourth-grade students of SDN 037 Sabang Bandung City, West Java Province, totaling 20 people. The material that becomes the focus of the research is the Style subject matter science.  The results of this study are comparing student learning outcomes before using the TGT learning model after using the TGT learning model.  The results of the analysis show that the use of the TGT learning model can improve student learning outcomes, this can be seen from the increase in the number of students who complete learning.
METHODS FOR DETERMINING THE FORMATION OF PROFESSIONAL CULTURE OF STUDENTS IN HIGHER EDUCATION

This article fully clarifies the content and order of application in practice of socio-metric methods aimed at diagnosing the mental and spiritual development of the individual, the direction of competence in various areas of activity.Our time forces a person to think, reason, reflect and draw conclusions for himself every second as an independent-minded person. That is, in this infinite world, we have to know and study pedagogy-psychology because we cannot imagine ourselves without others, without our own interests.
A Critical Analysis of Fraud Cases on the Internet

We lived in the era of technology, where online websites have made communication and interaction much easier than the early decade. The modern world is changing so quickly, and emerging new trends simplify our lives, but on the other hand, it will also create risks. A website acts as a more admired platform by the user to access the different web applications. Because of the functions of the website, all the data on the website is available in the proper structure, which makes the working environment much convenient and efficient. The websites may undoubtedly be a precious resource for young people, but it may also cause severe problems. It is really easy to build a fake website that looks like an original website where hackers like to deceive consumers and businesses for their own benefits. In this paper, researchers have examined online fraud cases through web applications and how fraudulent websites affect financial loss. Researchers also highlighted the current situation regarding the usage of online services, as well as the threats that have an impact on users. In addition, researchers have suggested that new laws and regulations will be implemented for preventing cybercrime.
Microscopic analysis of unsignalised intersections in heterogenous traffic conditions

Microscopic study of unsignalised intersections in heterogeneous traffic conditions. in this study, focus on diverse traffic and pedestrian parameters has been established thus proving useful for further studies and model categories.
ANALISIS KEBERLANJUTAN PENGENDALIAN PENCEMARAN AIR LIMBAH DOMESTIK GREYWATER MENGGUNAKAN TEKNOLOGI LAHAN BASAH BUATAN

Along with the significant increase of population in Bandung City at the moment, domestic wastewater management process must be considered to avoid river contamination, which one of the causes is domestic wastewater disposal without any prior management process. This study is located in Bandung City, which the research was performed in Research Center for Water Resources Office (PUSAIR) Bandung by involving residents of RW 09 Kelurahan Dago as respondents. The method used in this research is a combination of qualitative and quantitative methods. This study aims to analyze the sustainability of the domestic wastewater management process which is carried out using constructed wetlands by considering the economic, environmental, social, and technological aspects. The result shows that the sustainability value of the domestic wastewater management process conducted in the PUSAIR office is approximately 65.2% with the status of moderate sustainability. The detail result of each aspects is economic dimension 62.5%; ecological dimension 75%; social dimension 33.3%; and technological dimension 90%.Keywords: Domestic wastewater, Constructed wetlands, Surface flow techniques, Sustainability analysis
Searchable encryption architectures: survey of the literature and proposing a unified architecture

While the world is developing rapidly, cloud security becomes the main concern of the era, especially when dealing with big data and different environments. Users and different organisations are willing to store large amount of data on the cloud securely in order to be protected against many threats. One way to achieve this goal is to encrypt data before being sent to the cloud. Searchable encryption techniques are used to process the encrypted data on the cloud without the need to download or decrypt that data in order to preserve the required security. Up to our knowledge, and after conducting an extensive search, none of the previous surveys have dealt with searchable encryption (SE) architectures. This is what has motivated us to compare different kinds of searchable encryption architectures, determine their components and illustrate their functionalities. This is done in order to make it easier for researchers to get into the details of this important field of could security. Afterward, we propose a new unified searchable encryption architecture that can be considered as a reference for creating new searchable encryption schemes or models.