Reviewerly/exHarmony huggingface dataset:
Action-Independent Generalized Behavioral Identity Descriptors for Look-alike Recognition in Videos

There is a long history of exploitation of the visual similarity of look-alikes for fraud and deception. The visual similarity along with the application of physical and digital cosmetics greatly challenges the recognition ability of average humans. Face recognition systems are not an exception in this regard and are vulnerable to such similarities. In contrast to physiological face recognition, behavioral face recognition is often overlooked due to the outstanding success of the former. However, the behavior of a person can provide an additional source of discriminative information with regards to the identity of individuals when physiological attributes are not reliable. In this study, we propose a novel biometric recognition system based only on facial behavior for the differentiation of look-alikes in unconstrained recording conditions. To this end, we organized a dataset of 85, 656 utterances from 1000 look-alike pairs based on videos collected from the wild, large enough for the development of deep learning solutions. Our selection criteria assert that for these collected videos, both state-of-the-art biometric systems and human judgment fail in recognition. Furthermore, to utilize the advantage of large-scale data, we introduce a novel action-independent biometric recognition system that was trained using triplet-loss to create generalized behavioral identity embeddings. We achieve look-alike recognition equal-error-rate of 7.93% with sole reliance on the behavior descriptors extracted from facial landmark movements. The proposed method can have applications in face recognition as well as presentation attack detection and Deepfake detection.
CSSLibraryGuides: Library Resources for your Brightspace Classroom: LibGuides

A smorgasbord of tasty items you can add to your Brightspace classroom to put the Library and all its great resources at the fingertips of your students. Get you thoughts out there and get feedback from your readers with a blog.
Mass Generation and Non-Euclidean Metric from Fractional Dynamics

Fractional-time Schrodinger equation (FTSE) describes the evolution of quantum processes endowed with memory effects. FTSE manifestly breaks all consistency requirements of quantum field theory (unitarity, locality and compliance with the clustering theorem), unless the order of fractional differentiation and integration falls close to one. Working in the context of the minimal fractal manifold, we confirm here that FTSE approximates the attributes of gravitational metric and provides an unforeseen generation mechanism for massive fields.
IMPROVING STUDENTS READING COMPREHENSION OF VIII GRADE STUDENTS AT SMP NEGERI 3 GALANG THROUGH THINK ALOUD STRATEGY

The objective of this research is to find out or the application of think aloud strategy effective to improve students’ ability in reading narrative text. It is a pre-experimental research. The study is take by the VIII Grade of SMP Negeri 3 Galang. It is conduct in one class (VIII A). the data are obtain through a pre-test and post-test. The researcher used SPSS 16.0 program to analyze the data collection. The result of the analysis showed that the application of Think Aloud Strategy greatly to students in reading narrative text. The mean score of pre-test was 40.81 while in the post-test improved up to 81.96. Moreover the minimum mastery criterion of English lesson is 65 (sixty-five). Then the data of both test were analyzed by using T- test , and the result showed that the T- count value is 13.63 greater than T- table value is 2.060. it can be inferred that the application of think aloud is very effective to improve students’ ability in reading narrative text. Key Word: Improving, Reading, Think Aloud
The Impact of Facebook Access Motivation on Facebook Addiction among High School Students: The Mediator Role of Online Self-Disclosure

Online self-disclosure was hypothesized as a mediating variable, explaining the relationship between Facebook access motivation (relationship expansion, curiosity about others’ life, maintenance of social connection, social pressure from others, habitual use, impression management, searching for information, and content sharing) and Facebook addiction. Data came from 407 high school students in the Busan, and Gyeongnam provinces. Structural analysis was used to specify the relations among measured construct. Facebook access motivation of curiosity about others’ life, Facebook access motivation of maintenance of social connection, Facebook access motivation of social pressure from others, Facebook access motivation of habitual use, and Facebook access motivation of impression management were significant predictors of Facebook addiction. Online self-disclosure mediates between Facebook access motivation of curiosity about others’ life, Facebook access motivation of social pressure from others, Facebook access motivation of searching for information & Facebook access motivation of content sharing and Facebook addiction. Viewing online self-disclosure as a mediator has important implications for social media addiction counseling practice
ИНТУИЦИЯ И ЕЕ РОЛЬ В СТРУКТУРЕ НАУЧНОГО ПОЗНАНИЯ

Abstract. The article discusses the concept and role of intuition in scientific knowledge. The characteristic of intuition as a mode of cognition is given. The author emphasizes the role of the neural network in the process of intuition. The author comes to the conclusion that it is necessary to study consciousness in order to understand the mechanisms of intuition.
The versatile Heliosat-V method for estimating downwelling surface solar irradiance from satellite imagery

&amp;lt;p&amp;gt;Downwelling surface solar irradiance (DSSI) is one of the Essential Climate Variables defined by the Global Climate Observing System. The knowledge of its space and time variabilities is of primary importance for different applications, including Earth sciences, agriculture and renewable solar energies. To characterize such variabilities, the retrieval of long time series and of a dense kilometric global spatial coverage is required. The Heliosat methods are developed by Mines ParisTech since the mid-1980&amp;amp;#8217;s to estimate DSSI from the imagery produced by geostationary meteorological satellites. A challenge today is to use imagery from different satellites, including non-geostationary. This raises a number of issues, related among others to the different viewing geometries and spectral sensitivities of the sensors. These issues motivate the evolution of the Heliosat methods toward a more flexible version: the versatile Heliosat-V method. Other difficulties, mainly of operational types, such as massive data retrieval/processing, geometric correction, radiometric cross-calibration, missing data, seamless mosaicking, etc. are out of the scope of this communication.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Heliosat-V is designed to produce estimates of DSSI that can cover a wide variety of satellite optical sensors that have at least one radiometric channel with sensitivity in the 400-1000-nm part of the electromagnetic spectrum. The method is capable of using calibrated imagery from geostationary and also non-geostationary satellites. External remote-sensed data of surface reflectance anisotropy (Ross-Li model parameters derived from the imagery of the Moderate-Resolution Imaging Spectroradiometer (MODIS)) and atmospheric composition (ozone, water vapour and aerosol types and optical depths) from coupled meteorological and chemical transport models (Copernicus Atmospheric Monitoring Services) are used to produce fast radiative transfer simulations. Typical reflectances of cloudy scenes at the top of the atmosphere are produced via look-up tables derived from a radiative transfer model (libRadtran). They can adapt to the spectral sensitivity of the satellite channel, and to the solar and viewing geometries. This algorithm setup allows its use without past data, which were necessary for previous Heliosat methods. This is a real asset for its implementation to non-geostationary satellites.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;We test the validity of the method, by comparing DSSI estimates derived from one year of Meteosat Second Generation 0&amp;amp;#176; imagery, with ground-based pyranometer measurements from 10 stations of the Baseline Surface Radiation Network, on different continents and environments. Our results show root-mean square errors of 15-min averaged DSSI between 12% and 35% (71 and 133 W m&amp;lt;sup&amp;gt;-2&amp;lt;/sup&amp;gt; in absolute value), similarly to existing surface irradiance products based on Heliosat-2 or Heliosat-4.&amp;lt;/p&amp;gt;
A Study of the Establishments of the Edu-fine system at Private Kindergarten

본 연구의 목적은 2020년 3월부터 전국 사립유치원에 전면 도입된 에듀파인 학교회계 시스템에 대한 사용자의 인식을 분석하여 성공적인 정착 방안을 도출하는 데 있다. 이를 위해 다음과 같이 연구문제를 설정하였다. 첫째, 사립유치원 에듀파인 시스템에 대한 전반적인 이해도는 어떠한가? 둘째, 사립유치원 에듀파인 시스템의 업무 효율성에 대한 인식은 어떠한가? 셋째, 사립유치원 에듀파인 시스템의 성공적 정착을 위한 방안은 무엇인가? 이와 같은 목적을 달성하기 위해서 대구와 경북지역 사립유치원 교직원 208명을 대상으로 설문조사를 실시하였으며, 주요 결과는 다음과 같다. 첫째, 사립유치원 교직원들은 에듀파인 시스템 도입에 대해 많은 관심을 가지고 있었으며 대체로 긍정적으로 인식하고 있었다. 둘째, 사립유치원 교직원들은 에듀파인 시스템의 도입이 업무 효율성에 미치는 영향에 대해서는 부정적이었으나 유치원회계의 투명성과 신뢰성 제고에 있어서는 긍정적으로 인식하고 있었다. 셋째, 에듀파인 시스템이 성공적으로 정착 및 발전하기 위해서는 사립유치원의 실정에 맞는 시스템 개선, 적절한 교육과 연수의 개발과 함께 지원기관의 적극적인 지원이 필요하다. 이상의 분석결과를 토대로 지원인력 구성 및 확대, 사립유치원 행정전담인력의 확보, 양성기관에서의 사전교육 필요성 등을 개선방안으로 제안하였다.The purpose of this study is to investigate the users’ perception of the Edu-fine system environment at private kindergartens. To achieve this objective, research questions were set up as follows: Firstly, how is the overall understanding of the edu-fine system at private kindergarten? Secondly, what is the recognition of the work efficiency of the private kindergarten edu-fine system? Thirdly, what are the effective strategies for settle edu-fine system down at private kindergarten? A survey was conducted on 208 users at private kindergarten through convenience sampling. Data were collected by a valid and reliable questionnaire, consisting of three sections. Collected data sets were analyzed by SPSS software. Results show that users are interested in the edu-fine system and have concerns about the efficiency of the edu-fine system. Results were discussed in terms of the supporting strategies and pre-training at college level.
A Secure Variant of the Fiat and Shamir Authentication Protocol Using Gaussian Integers

In this paper we propose a cryptographic topic. It’s a new identification protocol. We use the Gaussian integers to ameliorate the Fiat and Shamir scheme. The method is based on the hardness to factor large composite numbers. We analyze security and complexity of the proposed protocol.
Penentuan Aturan Asosiasi Pola Pembelian Pada Minimarket Dengan Algoritma Apriori

Data mining is a technique for producing information from a data warehouse into new knowledge. Information is very important and useful to achieve a goal, therefore many people who use information, as well as those carried out in sales businesses such as 212 Mart. 212 Mart is located with a residential complex of residents, of course, will affect the level of sales every day, this causes data storage is increasingly growing, besides that the laying of goods is also not following consumer behavior. The association rule analysis with apriori algorithm is the right method to find the association pattern based on consumer shopping patterns so that it can be known the goods purchased at the same time. The results of this study found the highest support and confidence values ​​are Eggs and Noodles, with a support value of 40% and a confidence value of 85.71%.
A Review Paper on Solar Tree Mechanism and Installation for Energy Generation

Nowadays solar energy is the most explored and attainable area of but exploration is not so easy and solar energy is accepted as a key resource for the future of the world.  Solar energy can be utilized to cover energy demand over a significant part of the countries. The solar tree is the most popular example of utilized solar energy. Solar Energy is free, inexhaustible, and nonpolluting This paper represents the reviews about the development of Solar Tree for domestic application and the solar tree considering the average requirement of a small Indian house. A solar tree is the most economical way of exploiting solar energy. It can make use of the energy occupying less space.
LibGuides: Library Support for Faculty: Streaming Video and Audio Collections

Information about University Libraries resources for instructional use in the classroom, online courses, and Blackboard
PENGEMBANGAN SMART VILLAGE KAKI LANGIT DENGAN PENGOPTIMALAN WEB INTEGRATIF

Smart Village is a village that has the ability to use Information and Communication Technology systems in developing the potential for both natural and human resources. Smart Village can indirectly improve the economy of a village, this is supported by the ability of a smart village to communicate the potentials of natural resources outside the village, and provide knowledge or understanding in managing village potential by the villagers.&#x0D; The development of the Kaki Langit Tourism Village is to accommodate people who love their village to work together to carry out their respective activities with TOURISM as a binding knot by prioritizing the value of local wisdom, so that the community will be more prosperous. Likewise, the role of information technology is needed in realizing the skyline tourism village as a smart village pioneer.&#x0D; Kaki Langit Smart Village Development with Integrative Web Optimization can manage data related to kaki langit tourism villages, thus helping visitors in choosing the desired tourist attraction, and applications are developed by integrating web and homestay management applications so as to help visitors in choosing homestays and packages the desired tourism.
Determining the advantage of quantum radar

We discuss our progress towards creating a computer model of a quantum illumination type quantum radar. This will allow us to determine the quantum advantage from several important initial experimental demonstrations.
A heuristic framework for perceptual saliency prediction

Saliency prediction can be regarded as the human spontaneous activity. The most effective saliency model should highly approximate the response of viewers to the perceived information. In the paper, we exploit the perception response for saliency detection and propose a heuristic framework to predict salient region. First, to find the perceptually meaningful salient regions, an orientation selectivity based local feature and a visual Acuity based global feature are proposed to jointly predict candidate salient regions. Subsequently, to further boost the accuracy of saliency map, we introduce a visual error sensitivity based operator to activate the meaningful salient regions from a local and global perspective. In addition, an adaptive fusion method based on free energy principle is designed to combine the sub-saliency maps from each image channel to obtain the final saliency map. Experimental results on five natural and emotional datasets demonstrate the superiority of the proposed method compared to twelve state-of-the-art algorithms.
Approximating Bayes Estimates by Means of the Tierney Kadane, Importance Sampling and Metropolis-Hastings within Gibbs Methods in the Poisson-Exponential Distribution: A Comparative Study

Here, we work on the problem of point estimation of the parameters of the Poisson-exponential distribution through the Bayesian and maximum likelihood methods based on complete samples. The point Bayes estimates under the symmetric squared error loss (SEL) function are approximated using three methods, namely the Tierney Kadane approximation method, the importance sampling method and the Metropolis-Hastings within Gibbs algorithm. The interval estimators are also obtained. The performance of the point and interval estimators are compared with each other by means of a Monte Carlo simulation. Several conclusions are given at the end.
Collective motion planning for a group of robots using intermittent diffusion

In this work we establish a simple yet effective strategy, based on optimal transport theory, for enabling a group of robots to accomplish complex tasks, such as shape formation and assembly. We demonstrate the feasibility of this approach and rigorously prove collision avoidance and convergence properties of the proposed algorithms.
Dynamic Knowledge Embedding and Tracing.

The goal of knowledge tracing is to track the state of a student's knowledge as it evolves over time. This plays a fundamental role in understanding the learning process and is a key task in the development of an intelligent tutoring system. In this paper we propose a novel approach to knowledge tracing that combines techniques from matrix factorization with recent progress in recurrent neural networks (RNNs) to effectively track the state of a student's knowledge. The proposed \emph{DynEmb} framework enables the tracking of student knowledge even without the concept/skill tag information that other knowledge tracing models require while simultaneously achieving superior performance. We provide experimental evaluations demonstrating that DynEmb achieves improved performance compared to baselines and illustrating the robustness and effectiveness of the proposed framework. We also evaluate our approach using several real-world datasets showing that the proposed model outperforms the previous state-of-the-art. These results suggest that combining embedding models with sequential models such as RNNs is a promising new direction for knowledge tracing.
When Virtual Therapy and Art Meet: A Case Study of Creative Drawing Game in Virtual Environments.

There have been a resurge lately on virtual therapy and other virtual- and tele-medicine services due to the new normal of practicing 'shelter at home'. In this paper, we propose a creative drawing game for virtual therapy and investigate user's comfort and movement freedom in a pilot study. In a mixed-design study, healthy participants (N=16, 8 females) completed one of the easy or hard trajectories of the virtual therapy game in standing and seated arrangements using a virtual-reality headset. The results from participants' movement accuracy, task completion time, and usability questionnaires indicate that participants had significant performance differences on two levels of the game based on its difficulty (between-subjects factor), but no difference in seated and standing configurations (within-subjects factor). Also, the hard mode was more favorable among participants. This work offers implications on virtual reality and 3D-interactive systems, with specific contributions to virtual therapy, and serious games for healthcare applications.
Identifying the oppurtunities for the design of digital platforms: a topic modelling approach

Aquaculture is one of the fast-growing food-producing agriculture subsectors. However, the digital infrastructures developed in aquaculture are self-organising platforms i.e. they do not rely on a centralized intermediary for monitoring, coordinating activities or for overseeing transactions. Hence, the main objective of this research paper is to identify the challenges farmers face in an entire supply chain for designing a digital platform for the aquaculture domain. The main problems faced by the farmers include water quality issues, disease outbreak, lack of proper information regarding suitable insurance policies etc. We have identified eight such issues that the farmers face in an entire harvest period and also prioritized them. The results from our study could be used for the further advancement of an integrative perspective in the design and implementation of the digital platform for aquaculture.
KrigHedge: GP Surrogates for Delta Hedging

We investigate a machine learning approach to option Greeks approximation based on Gaussian process (GP) surrogates. The method takes in noisily observed option prices, fits a nonparametric input-output map and then analytically differentiates the latter to obtain the various price sensitivities. Our motivation is to compute Greeks in cases where direct computation is expensive, such as in local volatility models, or can only ever be done approximately. We provide a detailed analysis of numerous aspects of GP surrogates, including choice of kernel family, simulation design, choice of trend function and impact of noise. We further discuss the application to Delta hedging, including a new Lemma that relates quality of the Delta approximation to discrete-time hedging loss. Results are illustrated with two extensive case studies that consider estimation of Delta, Theta and Gamma and benchmark approximation quality and uncertainty quantification using a variety of statistical metrics. Among our key take-aways are the recommendation to use Matern kernels, the benefit of including virtual training points to capture boundary conditions, and the significant loss of fidelity when training on stock-path-based datasets.
Pemanfaatan Sampah Plastik sebagai Potensi E-Commerce Berbasis Komunitas

The purpose of this service activity are utilizing plastic waste for recycling into valuable products, sharpening creativity through training in managing plastic waste to communities both children, Youth Organization and women in Kampung Kulitan, and inviting people in Kampung Kulitan to get to know and be more courageous in promoting the results of used plastic waste products through e-commerce. The first method is to collect plastic waste that is wasted and is no longer utilized by residents in Kampung Kulitan, then manage the plastic waste as best as possible so that it becomes an item that has more value for sale with training and the last step that must be taken is to socialize e-commerce. The results show that plastic waste can be used to be recycled into valuable products, plastic waste that is used is used coffee containers, used plastic bottles, and used paint vats. Sharpening creativity is done through training in managing plastic waste to the community in Kampung Kulitan which produces high-value products, so that the community in Kampung Kulitan can take advantage of the results. The people in Kampung Kulitan know more and are more willing to promote the results of used plastic waste products through e-commerce that can increase income and improve the economy of the people who participate in the community .
Syu’aib Controller: Innovative Digital Device for Supervision of Fraud of Dose (Mikyāl) and Weight (Mīzān)

One of the most significant issues in the Indonesian traditional markets is the reduction of dose (Mikyāl) and weight (Mīzān) done by sellers in traditional markets. As a solution to this corruptive reality, this paper offers an application called Syu'aib Controller (SC) . This is a dose and weight frauds detector. With this application, consumers can control the process of selling and buying as it told in the story of the Madyans. Syu'aib Controller (SC) was developed on a digital basis based on the criteria of the Quran ic values taught by the Prophet Syu'aib AS to the Madyans. The se values include justice , accuracy, and satisfaction. This innovative device can be used in buying and selling activities in traditional markets. With this digital device, the buyers could know the real weight of the object, check and supervise the dose, and scale used in the traditional market. The Syu'aib Controller (SC) is expected to foster an anti-corruption mentality. Thus the fair and honest characters of the Nusantara merchants are formed.