Reviewerly/exHarmony huggingface dataset:
Viewport-Aware Dynamic 360° Video Segment Categorization

Unlike conventional videos, 360{\deg} videos give freedom to users to turn their heads, watch and interact with the content owing to its immersive spherical environment. Although these movements are arbitrary, similarities can be observed between viewport patterns of different users and different videos. Identifying such patterns can assist both content and network providers to enhance the 360{\deg} video streaming process, eventually increasing the end-user Quality of Experience (QoE). But a study on how viewport patterns display similarities across different video content, and their potential applications has not yet been done. In this paper, we present a comprehensive analysis of a dataset of 88 360{\deg} videos and propose a novel video categorization algorithm that is based on similarities of viewports. First, we propose a novel viewport clustering algorithm that outperforms the existing algorithms in terms of clustering viewports with similar positioning and speed. Next, we develop a novel and unique dynamic video segment categorization algorithm that shows notable improvement in similarity for viewport distributions within the clusters when compared to that of existing static video categorizations.
Challenges of teaching humanities in innovative educational environment

This article analyzes the issues of implementation of innovations and respective methodology of teaching humanities in universities. The aim of this article is to reveal challenges related with implementation and use of advanced innovative methods of teaching humanities in universities. This work substantiates the concept that modern processes occurring in education are direct consequence of complicated and deep transformations in culture, economy, policy of the World. Adaptation of life to wide-scale transformations is impossible without holistic comprehension of motives, trends and prospects of further social development, including education. The novelty of the work is in development of certain theoretic models of education development, which is rapidly moving away from the differentiation and fragmentation of scientific disciplines, modules and is concentrated on their integration. Another novelty in the existing paradigm of education can be presented by targeting of potential not just on distance methods but on creation of innovative education systems based, for instance, on technologies of virtual reality (VR). This work proves that in VR the educational components or prototypes can be presented by such units as virtual laboratory (workshop), lecture spaces, displaying of considered entities, network educational establishments.
AUDIT INFORMASI PADA UPT BAHASA UNIVERSITAS NUSA CENDANA

This research aims to present the results of the study about the information management practice through conducting an Information Audit (IA). The research was conducted at Language Centre of Nusa Cendana University in Kupang – East Nusa Tenggara. The information audit was conducted to examine (1) the existing information resources available to the staf of Language Centre and (2) to find out the information problems faced by the staf in the Language Centre.Case study research methodology was applied with document analysis, questionnaire and interviews were used for data collection. All data were analysed manually, where data from questionnaire was generated directly to Microsft Excel to create a list of information resources. Further, Thematic analysis method was used to analyse the interview data to find general themes of information problem. Study found that documents, websites,and information system were the information resources used by the staf. While, People, Timeliness, and Technology were the main information problems faced by the staf. This study recommended that Language Centre must create an information policy, conduct a digital literacy or computer training for the employees to improve their performance in using technology and create an integrated information system. It is also important that university can also conducting information audit for whole units, faculties in Undana in order to create a general information policy for university to have a better information management practice as well as to help the university to achieve its strategic goals. &#x0D; Keywords: Information Management, Information Audit, Information Resources, Case Study, Information problems.&#x0D;
Predicting Adversary Lateral Movement Patterns with Deep Learning

This paper develops a predictive model for which host, in an enterprise network, an adversary is likely to compromise next in the course of a campaign. Such a model might support dynamic monitoring or defenses. We generate data for this model using simulated networks, with hosts, users, and adversaries as first-class entities. We demonstrate the predictive accuracy of the model on out-of-sample simulated data, and validate the findings against data captured from a Red Team event on a live enterprise network
Personal determinants of professional development of the future specialist

The article highlights the issues of identifying personal determinations of the development of future specialists, and in particular, physical education teachers in their professional training, substantiates and empirically tests the dependence of the professional development of a future physical education teacher on his personal qualities. The author analyzes the features of the professional development of future physical education specialists in the article. Personal and professional development is viewed as an integral self-developing system based on the activity-based transformation of the personality of itself. The author identifies personal determinants that affect the professional development of a future specialist, such as professional orientation, consisting of an interest in the teaching profession and the desire to master knowledge and skills; a pedagogical vocation, which grows out of the awareness of the abilities for the profession of a physical education teacher. The author presents the results of this study, presents conclusions about the effectiveness of the experiment.
Application of Artificial Intelligence in Samsung  – A Case Study

The global quest for issues with Artificial Intelligence (AI) is in a crisis point and the rewards are great. AI tech is expected to rapidly become a lifestyle for many consumers by everyday interactions with a digital assistant or personalized IT offering solutions based on a client's visual, tactile, or emotional signals. Samsung has been in a fantastic position to turn the future of connected AI technology into reality, from various electronic devices to 5G hardware to strong chipsets, based on roughly half the billion products sold by the company per year. Samsung works with a vision that says By dedicating our technologies and expertise to support a broader international world, we create superior services and goods. Looking to be a global leader that evolves alongside people and local communities. Samsung It is the largest multinational corporation in South Korea, and is made up of various firms, several of which are named after Samsung. Lee Byung-Chul founded Samsung as a commercial enterprise in 1938. The company expanded into food processing, apparel, insurance, shares and delivery sectors over the next 30 years. In the 1960s and the mid-1970s Samsung enters the electronics and construction industries; those industries would result in further growth. Within this paper, highlight their technological histories and list Samsung's implementations, financial plans, market challenges and products. We tried examining about various fields where artificial intelligence is used, such as Bixby to facilitate smartphone connectivity with the Galaxy S8 Samsung smartphone, in the 8 K TV system we used a machine learning technique to improve image quality, walking robot's vertical approach allowed Saram to navigate and cross many surfaces.
Perceptual Image Quality Assessment with Transformers

In this paper, we propose an image quality transformer (IQT) that successfully applies a transformer architecture to a perceptual full-reference image quality assessment (IQA) task. Perceptual representation becomes more important in image quality assessment. In this context, we extract the perceptual feature representations from each of input images using a convolutional neural network (CNN) backbone. The extracted feature maps are fed into the transformer encoder and decoder in order to compare a reference and distorted images. Following an approach of the transformer-based vision models, we use extra learnable quality embedding and position embedding. The output of the transformer is passed to a prediction head in order to predict a final quality score. The experimental results show that our proposed model has an outstanding performance for the standard IQA datasets. For a large-scale IQA dataset containing output images of generative model, our model also shows the promising results. The proposed IQT was ranked first among 13 participants in the NTIRE 2021 perceptual image quality assessment challenge. Our work will be an opportunity to further expand the approach for the perceptual IQA task.
Review on Steganography Techniques

With the increase in the use of the internet, user wants to access the data easily and securely at any spot of time. So, user start saving and sharing the important information on cloud. Hence, the security of data on cloud computing become a major issue of concern. Steganography is used as a standard practice for both cloud service providers and cloud users as a tool against unauthorized surveillance. Steganography refers to guarding the information by concealing it in some other media such that only the owner has the ability to safely recover the information. The purpose of this paper is to give an overview of different techniques of steganography used in cloud computing and compare them on the parameters like, technique selection, carrier formats, payload capacity.
Remote Sensing Aplication and Geochemical Studies for Hydrocarbon-Induced Alterations Discoveries in Western Kendeng Zone

The development of satellite imaging technology that has spectral capability has the potential to be utilized in hydrocarbon exploration. The presence of hydrocarbons can be detected through spectral recording of hydrocarbon seepage. Over a long period, hydrocarbon seepage will change the chemical structure and mineralogy of the surrounding soil and rocks, so that it will cause spectral anomalies that are key to the existence of active hydrocarbons and petroleum systems. The West Kendeng zone was chosen as a research location because several hydrocarbon seepage sites were found to contain, either oil or gas in the area. Based on hydrocarbon seepage spectral theory, Landsat 8 imagery has a wavelength spectrum capability that is sensitive to the anomalous object of hydrocarbon seepage. Therefore, this research was conducted to determine the distribution of hydrocarbon seepage areas in the West Kendeng zone by using Landsat 8 imagery. In addition to using Landsat 8, to strengthen the research results a surface geological mapping process was also carried out at the seepage location. Then the samples obtained were analyzed by XRD and XRF. XRD analysis was carried out to determine the types of minerals that became an anomaly around the seepage location. In addition, the XRF analysis is carried out to determine the chemical composition of rocks that have undergone alteration. Based on the results of Landsat 8 data calibration, an altered rock which is an anomaly of hydrocarbon seepage is found in the south and southwest of the study site. These results are confirmed by the location of the discovery of several points of seepage of hydrocarbons in the research area. The XRD test results also showed anomalous clay mineral content in the form of halloysite, albite, and augite in the southwest and south of the study site. Besides this anomaly, magnetite and pyrite were also found at that location. While the XRF test results from the sample also showed the presence of Fe2O3 element at 9.21% and CaO at 7.42% in the south and southwest of the study location. This indicates a reaction between hydrocarbons and rocks that affect the acidity conditions around them, so they will form clay minerals, iron oxides, and iron sulfides. Therefore, based on Landsat 8 image analysis, XRD, and XRF, a hydrocarbon seepage distribution area accumulated in the Bancak, Boto, Wonokerto, and Nyemoh areas in the Semarang Regency.
Causal factors discovering from Chinese construction accident cases

In China, construction accidents have killed more people than any other industry since 2012. The factors which led to the accident have complex interaction. Real data about accidents is the key to reveal the mechanism among these factors. But the data from the questionnaire and interview has inherent defects. Many behaviors that impact safety are illegal. In China, most of the cases are from accident investigation reports. Finding out the cause of the accident and liability affirmation are the core of incident investigation reports. So the truth of some answers from the respondents is doubtful. With a series of NLP technologies, in this paper, causal factors of construction accidents are extracted and organized from Chinese incident case texts. Finally, three kinds of neglected causal factors are discovered after data analysis.
Early Reading Difficulties : A Phenomena in Reading Problems

Reading Difficulties in one of challenging which faced by student in elementary school in Indonesia. This research purpose to find variety of challenging by student in early reading. 31 students with early reading problems who comes from 7 elementary school is use as respondent. Data collection is use by informal early reading test which validation with expert in special education needs and Bahasa Indonesia. Finding of this research is almost students with reading problems can read the letters, both vowel and consonant. They have problems in blending between letters become syllable and word.
Classification of phishing websites using extreme learning machine and hybrid bat algorithm

Phishing is an electronic fraud through which an attacker can gain access to user credentials. Phishing websites are the one which mimics the legitimate websites and fraudsters evade their detection without much effort. The effect of phishing attack raises the necessity of anti-phishing mechanisms. Several approaches are there to recognize phishing websites such as whitelist, blacklist, machine learning and heuristic-based approach. This paper investigates extreme learning machine and hybrid bat algorithm for the classification of website phishing attacks. The features that distinguish the legitimate from the fraudulent website is selected using the random forest algorithm. The comparison of these techniques with other classification methods, for instance, support vector machine, logistic regression, decision tree and the random forest is also carried out. The results of the classification accuracy show that the hybrid bat algorithm achieves better classification accuracy compared to other classification methods.
Focused Attention Improves Document-Grounded Generation

Document grounded generation is the task of using the information provided in a document to improve text generation. This work focuses on two different document grounded generation tasks: Wikipedia Update Generation task and Dialogue response generation. Our work introduces two novel adaptations of large scale pre-trained encoder-decoder models focusing on building context driven representation of the document and enabling specific attention to the information in the document. Additionally, we provide a stronger BART baseline for these tasks. Our proposed techniques outperform existing methods on both automated (at least 48% increase in BLEU-4 points) and human evaluation for closeness to reference and relevance to the document. Furthermore, we perform comprehensive manual inspection of the generated output and categorize errors to provide insights into future directions in modeling these tasks.
Wireless Gesture Controlled Robot Car using Arduino Microcontroller

This paper is to develop a wheel chair control which is useful to the physically disabled person with his hand movement or his hand gesture recognition using Acceleration technology. Tremendous leaps have been made in the field of wheelchair technology. However, even these significant advances haven‟t been able to help quadriplegics navigate wheelchair unassisted. It is wheelchair which can be controlled by simple hand gestures. It employs a Flex sensor which controls the wheelchair hand gestures made by the user and interprets the motion intended by user and moves accordingly. In Acceleration we have Acceleration sensor. When we change the direction, the flex sensor are changed and that values are given to microcontroller. Depending on the direction of the Acceleration, microcontroller controls the wheel chair directions like LEFT, RIGHT, FRONT, and BACK. The aim of this paper is to implement wheel chair direction control with hand gesture reorganization. According to a research there are about 6 million populations in the world who are paralysed and needs a wheelchair for their mobility. Earlier the wheel chairs had to be moved and be externally supported by any person. To help overcome this “joystick-controlled wheelchairs” are developed. But in regular use, these joystick-controlled wheelchairs became difficult to use. Especially in the case of paralysed people, the use of joystick became more difficult due to the hard buttons and unidirectional use of the joysticks. To overcome these problems, we’ve tried to develop a “gesture-controlled wheelchair” which can be moved with a slight tilt of the hand. This can be used in both hands and can be controlled to come to the user from a distance. The current work is implemented with Arduino based devices such as Arduino and UNO processors and programmed through Arduino IDE.
Studi Perencanaan Bangunan Pelengkap Pada Boezem Di Kelurahan Blimbing Kota Malang

The area of Blimbing Village is one of the areas of Malang City where often having flood in rainy season. The flood in the Blimbing Village area is caused by the inadequacy of the existing drainage and also not using water absorption building or Boezem effeciently, therefore need some effort to overcome this problem. One of the solution to tackel this problem is make use boezem more efficiently, in order to reduce flood. In the analysis results of design discharge of the study area was obtained for 3.970 m3/ sec for the two years period and 4,606 m3/ sec for five years period. In order to reduce flood at the study area, an alternative flood control is implemented. The alternative is to increase the storage capacity of the Boezem and planned support buildings specifically planning drainage channels, and planning for inlet and outlet of sluice gates. There are alternative, it can reduce flood by 30%. Based on the results of the analysis, it is obtained that the design budget (RAB) for support buildings planning according to the main unit price for the activities of the city of Malang is IDR 146,620,000.
Sarcasm Beyond Hate Speech: Facebook Comments on Syrian Refugees in Turkey

In Turkey, the widespread sharing of false information about refugees on social media is one of the main reasons behind the ever-increasing antirefugee sentiment. In this study, with a reference to critical discourse studies and by adopting a theoretical approach on indirect violence, 1,000 user comments made under the most viral false claims on Facebook about Syrian refugees during the election years of 2018–19 were analyzed. Together with comments that are classified under categories of hate speech and discriminative rhetoric, a significant number of sarcastic comments were also detected by critical discourse analysis. It is observed that sarcasm is instrumentalized to reproduce superiority over refugees as well as criticizing official policies. Such comments cannot simply be considered as “innocent jokes” and are indeed part of a vicious cycle of violence and function like hate speech and discriminatory rhetoric.
Letteratura e antiletteratura? Cinquant'anni dopo

Reflections and reinterpretations on Sixty-eight, fifty years later, put those who already existed then in the condition of one who confronts what he experienced without being able to understand it, having then come to understand it (or believe he understood it) only much later, on wave of those fifty years that have passed.
Confidence estimation method for regression neural networks

Numerous confidence estimation methods have been proposed for classification neural networks; however, this problem has not been well addressed for regression neural networks. That is, softmax layers are not available in regression networks and the interpretation of confidence becomes less clear. To alleviate these problems, a simple but effective method is proposed that computes the confidences of regression results. First, the confidence is considered as a scalar value representing relative error-levels. Then, a mini-batch based training method based on this interpretation is developed. Precisely, in each mini-batch, desired outputs for confidence values are assigned by sorting current errors. Experimental results on the loose wheel nut detection problem as well as a simulated example have shown that the proposed method can be successfully applied to regression problems.
PathBench: A Benchmarking Platform for Classical and Learned Path Planning Algorithms

Path planning is a key component in mobile robotics. A wide range of path planning algorithms exist, but few attempts have been made to benchmark the algorithms holistically or unify their interface. Moreover, with the recent advances in deep neural networks, there is an urgent need to facilitate the development and benchmarking of such learning-based planning algorithms. This paper presents PathBench, a platform for developing, visualizing, training, testing, and benchmarking of existing and future, classical and learned 2D and 3D path planning algorithms, while offering support for Robot Oper-ating System (ROS). Many existing path planning algorithms are supported; e.g. A*, wavefront, rapidly-exploring random tree, value iteration networks, gated path planning networks; and integrating new algorithms is easy and clearly specified. We demonstrate the benchmarking capability of PathBench by comparing implemented classical and learned algorithms for metrics, such as path length, success rate, computational time and path deviation. These evaluations are done on built-in PathBench maps and external path planning environments from video games and real world databases. PathBench is open source.
Arrendale Library: Permalinks for Online Services: OpenAthens Link Generator

This guide will show how to obtain permalinks to journal articles, ebooks and ebook chapters, and videos found in the Library's online research services. Permalinks can be used to create links to learning objects in Canvas courses.
Study on Selection Methods of Parents and Crossover in Genetic Algorithm

Genetic Algorithms are the population based search and optimization technique that mimic the process of Genetic and Natural Evolution. Genetic algorithms are very effective way of finding an Optimized solution to a complex problem. Performance of genetic algorithms mainly depends on various factors such as selection of efficient parents and type of genetic operators which involve crossover and mutation operators etc. This paper will help the people to acquire the knowledge about various strategies of selecting parents and description about standard crossover operators.