Reviewerly/exHarmony huggingface dataset:
Image enhancement in wavelet domain based on histogram equalization and median filter

During the acquisition of a new digital image, noise may be introduced as a result of the production process. Image enhancement is used to alleviate problems caused by noise. In this work, the purpose is to propose, apply, and evaluate enhancement approaches to images by selecting suitable filters to produce improved quality and performance results. The new method proposed for image noise reduction as an enhancement process employs threshold and histogram equalization implemented in the wavelet domain. Different types of wavelet filters were tested to obtain the best results for the image noise reduction process. Also, the effect of canceling one or more of the high-frequency bands in the wavelet domain was tested. The mean square error and peak signal to noise ratio are used for measuring the improvement in image noise reduction. A comparison made with two related works shows the superiority of the methods proposed and implemented in this research. The proposed methods of applying the median filter before and after the histogram equalization methods produce improvement in performance and efficiency compared to the case of using discrete wavelet transform only, even with the cases of multiresolution discrete wavelet transform and the cancellation step.
USING RAP SONGS BY EMINEM IN TEACHING ENGLISH PRONUNCIATION TO EFL STUDENTS AT UNIVERSITAS PGRI RONGGOLAWE TUBAN

The purpose of this study to improving pronunciation of students in second semester at University of PGRI Ronggolawe Tuban. Tongue twister and Linking Sound were chosen as the teaching media in this research. In this study researcher used action research that used in process. The research consist of the understanding in Linking Sound. The research was carried out on June, 15th 2021 with the number of students is 19 students. The data in this research were qualitative and quantitative. The data were obtained by observing learning, teaching process during the implementation of material, and questionnaire. It was from google form and transcripts. The result of this study from observing the students were enthusiastic and from both of pre-test and post-test was increase and from oral test the students could did it clearly, and the last is queastionnaires from all the questions and statements the students agree if leaning pronunciation were useful to increase their pronunciation.
A multi-gene genetic algorithm for the Flappy Bird game based on neural network

The propose of this paper is to develop and study an artificial intelligence-based optimization algorithm for the famous “Flappy Bird”, which benefits to a better game score. We first create an agent that learns how to optimally play the game by safely dodging all the barriers and flapping its wings through them. In order to expand the feasible solution space and generalization ability, a multi-gene genetic algorithm based on the Genetic Algorithm and Neural Network is proposed. We carry out detailed experiments to prove the proposed multi-gene genetic algorithm to be useful and efficient. The quantitative results show that the multi-gene genetic can significantly improve the game score.
The Effect of Gouin and Series Method on Students’ Speaking Skill in Procedure Text at SMA Negeri 4 Tanjungpinang

This research is aimed to see the effect of Gouin and Series Method on students' speaking skills in procedure text at Tanjungpinang at SMAN 4 Tanjungpinang. This study uses quasi-experiments. In this study involves 60 students which divided into 2 classes, 30 students in class XI MIPA 3 as experimental class and taught using the Gouin and Series method and 30 students in class XI MIPA 5 as control class and taught using Grammar Translation method. The research instrument used was an oral test. The researcher conducted a pre-test then applied the methods in both classes, Then, the researcher gave a post-test to see the increase of the mean score after the treatment. The results of the pre -test and posttest were analyzed using normality, homogeneity and h ypothesis testing. The results of this research showed that the class that was taught using the Gouin and Series Method has higher mean which is 80.53 while the mean score of control class is 74.80. It can be seen that the Gouin and Series method has significance effect on students' speaking ability in procedure text. Based on the data in the table, Sig. (2 tailed) is 0.004 and alpha is 0.05 (p <α). That means that p is lower than alpha. Therefore it can be concluded that there is a significant effect of the use of the Gouin and Series method on students' speaking ability in procedure text at SMAN 4 Tanjungpinang. Finally the researcher concluded that the Gouin and Series method is effective on students' speaking ability in procedure text.
The Science and Technology Facilities Council: Connecting Science to Industry

Professor Ric Allott will introduce the the Science and Technology Facilities Council (STFC), and their expertise and capabilities across their 3 main campuses and the potential benefits of working with the SFTC. The talk will focus on 3 key areas of STFC: our Large Scale Facilities (x-rays, neutrons and lasers), High Performance Computing and Data Analytics and Technology. Professor Ric Allott will end with details on how to engage with the SFTC and access our facilities, technologies, scientists and engineers
An Enhancement for the Consistent Depth Estimation of Monocular Videos using Lightweight Network

Depth estimation has made great progress in the last few years due to its applications in robotics science and computer vision. Various methods have been implemented and enhanced to estimate the depth without flickers and missing holes. Despite this progress, it is still one of the main challenges for researchers, especially for the video applications which have more complexity of the neural network which af ects the run time. Moreover to use such input like monocular video for depth estimation is considered an attractive idea, particularly for hand-held devices such as mobile phones, they are very popular for capturing pictures and videos, in addition to having a limited amount of RAM. Here in this work, we focus on enhancing the existing consistent depth estimation for monocular videos approach to be with less usage of RAM and with using less number of parameters without having a significant reduction in the quality of the depth estimation.
SIM - Safe Irrigation Management V2.0

SIM (Safe Irrigation Management) is a one-dimensional, daily water balance model designed for simulating soil moisture content under specific crop, soil, irrigation management, water quality and climatic conditions. The model contains 4 modules (Figure 1): i) crop water demand and irrigation scheduling module, ii) salinity management module, iii) bacterial movement and risk assessment module and v) nutrient management module.
MEMS-mirror-based dynamic structured light projection system for three-dimensional measurement with high precision

Three-dimensional (3D) measurement based on structured light, as a non-contact, active, and high-precision measurement technology, is widely applied in the diverse fields of industrial detection, face recognition, reverse engineering, and so on. We adopted an adjustable grating-stripe coding as the dynamic structured-light mode, which can continuously cover the entire measured surface to guarantee high accuracy. A one-axis resonant-mode MEMS mirror combined with a linear laser was used to project the desired adjustable grating stripes, leading to a miniaturized module size. To make the scanning angle of the MEMS mirror matching the intensity distribution of the linear laser, we further introduced a single-chip microcomputer (STM32) to receive the feed-back signals from MEMS mirror, and synchronously controlled the laser power with corresponding function relationship output. Here, the MEMS mirror could provide a resonant frequency of 1.15 kHz, a scanning optical angle of ±30°, a feed-back scanning-angle resolution of 0.05°, and a reflected mirror size of 3 mm-diameter circle, respectively. Also, the laser source could generate a line width of 70 μm at a 300 mm focused distance. To decrease the error in the energy amplitude of each cycle of the structured light stripes, the empirical mode decomposition (EMD) was used to perform principal component analysis and recombination of the structured light stripes. In addition, total harmonic distortion (THD) is used to evaluate the quality of structured light stripes. Finally, the structured light based on the scanning of the MEMS mirrors exhibits a good sinusoidal stripes and high refresh rate, implying high adaptivity for the 3D reconstruction.
An Image-based Algorithm for Automatic Detection of Loosened Bolts

The bolted joint has been widely used to connect load-bearing elements in aerospace, civil, and mechanical engineering systems. During its service life, particularly under external dynamical loads, a bolted joint may undergo self-loosening. Bolt-looseness causes a reduction in the load-bearing capacity and eventually leads to the failure of the bolted joint. This paper presents an automated image-based algorithm combining the Faster RCNN model with image processing for quick detection of loosened bolts in a structural connection. The algorithm is validated using a lab-scale bolted joint model for which various bolt-loosening events are simulated. The imagery data of the joint is captured and passed through the algorithm for bolt-looseness detection. The obtained results show that the loosened bolts in the joint were well detected and their loosening degrees were precisely quantified. Therefore, the image-based algorithm is promising for real-time structural health monitoring of realistic bolted joints.
LibGuides: Artificial Intelligence and Careers after Coronavirus Articles.: Coronavirus Open Access

These articles are food for thought. These are to let students know what is being said; HBU does NOT ACCLAIM these to be the truth or our future.
Research Guides: JSTOR Data for Research (DfR): Overview

Define and request datasets for content on JSTOR, or download a sample dataset for teaching text mining techniques
IMPLEMENTASI SEGMENTASI ALGORITMA FUZZY C MEANS PADA PRINTED KARAKTER CITRA DIGITAL

Image segmentation is an important step in analyzing an image to find an area that represents an object or part that has meaning. Image segmentation is the process of dividing the region based on the similarity in the thresholding value, which is a pixel with the thresholding level comparison of neighboring pixels. Thresholding is the first step to determine image segmentation, where the thresholding value is obtained from the middle value calculated from the obtained gray scale. The segmentation method used is the Fuzzy C Mean method, which is the concept of Fuzzy clustering.The Fuzzy C Mean method used to group the areas in the test case images can be obtained after going through the calculations. After completing the calculation, then the user can make a choice of output images depending on the features to be selected. The use of Fuzzy C Mean for the Segmentation Process for Printed Characters is to be able to recognize the form of character recognition written on a computer and segment these characters for pattern recognition in digital images that have letters.The result of this research is an application that can be used to detect text in digital images using the Fuzzy C Means method. Based on the results of tests carried out, information in the form of characters in digital images will be obtained.
Investigating the Performance of AutoRegressive Integrated Moving Average and Random Forests in Retail Market

Data Science is one of the most contemporary technologies of today's century. The most sensitive and valuable input to machine learning systems is the quantity and veracity of data. Many recommender engines are developed based on massive datasets to provide comfort to mankind. These cover various sectors like food and hospitality, educational courses, banking and insurance, social networks and the most important of all travel and retail shopping. One of the intermediate steps before a system generates recommendations is to choose the best algorithm that best serves the purpose. Machine learning and deep learning algorithms play a vital role in developing such systems. This paper implements and investigates the performance of two algorithms namely, ARIMA and Random Forests which are applied on a retail dataset. The results are discussed based on the observations.
Development of A Raindrop-aware Environment Detection Algorithm for 3D-LiDAR Based Outdoor Mobile Robot Navigation

Stable perception of its environment is essential to navigating an autonomous mobile robot safely. Most autonomous mobile robots employ a LiDAR (light detection and ranging) to sense its surrounding. The LiDAR can stably and accurately identify the surrounding environment in a normal situation. However, it has a problem in the case of rain because it would detect raindrops as objects. When an autonomous mobile robot uses LiDAR to detect obstacles during rains, the laser emitted from LiDAR may hit raindrops, resulting in false-positive reading. In this paper, we employ a 3D-LiDAR and present a new method for automatic detection and tracking of raindrops. We consider the three-dimensional raindrop behavior due to gravity to reconstruct a rain-free surrounding environment. We conducted experiments with actual and simulated raindrops and validated the effectiveness of the method.
Company To Candidate Mapper

The problem of shortlisting and screening of candi- dates to find the best match in given time frame has always been a challenging task for recruiters in emerging as well as established companies. The paper proposes an intelligent system that could help in easing the recruitment process by mapping the resumes of the best candidates to the company’s job description. The described algorithm is based on ranking candidates on the basis of a scoring system that will act as a mapper. Ranking of the candidates would be on the basis of certain parameters which will be extracted from the resume parser using Machine Learning(ML) and Natural Language Processing(NLP) Techniques which are the best match with the requirements in a specified job description. Also, recommending resumes to the company based on the previous selection of candidates for a similar job description using Recommender Systems is a part of such an intelligent system. The accuracy of the system was calculated by using Normalized Discounted Cumulative Gain accuracy metric. The significance of this project is to bridge the gap and the challenges faced in the recruitment process.
LibGuides: Job Seekers: New York State Resources

Looking for a job? Check here to see what resources the Ossining Public Library has available for you.
KAJIAN PRAGMATIK BAHASA IKLAN DAN PEMANFAATANNYA BAGI PEMBELAJARAN BAHASA INDONESIA DI SMA

The rapid development of communication needs have enabled language also experienced significant developments in terms of delivery.Language is not only conveyed face-to-face, but language containing certain information is conveyed through the mass media.One example of information delivery through mass media, is advertising. Advertising is used to convey a message to manufacturers about a particular product or service with the aim of influencing the public so that they are interested in buying the products or services offered.These ads form the image of the advertised product. In the creation of advertisements, manufacturers try to convey a message to consumers in the form of a meaningful symbol, namely language.However, so far the language used as a means of communication in advertising has its own meaning, so that some people will not directly understand the meaning of the advertisement.This can be influenced by the form of advertising design expressed in various ways in order to achieve the target to be targeted.Based on this, the use of varied advertising language is interesting to research.By utilizing the development of pragmatic science, this paper seeks to describe the use of advertising language and its implementation as teaching materials for writing in high school.
DUAL TRANSFORMER ENCODERS FOR SESSION-BASED RECOMMENDATION

When long-term user proles are not available, session-based recommendation methods are used to predict the user's next actions from anonymous sessions-based data. Recent advances in session-based recommendation highlight the necessity of modeling not only user sequential behaviors but also the user's main interest in a session, while avoiding the eect of unintended clicks causing interest drift of the user. In this work, we propose a Dual Transformer Encoder Recommendation model (DTER) as a solution to address this requirement. The idea is to combine the following recipes: (1) a Transformer-based model with dual encoders capable of modeling both sequential patterns and the main interest of the user in a session; (2) a new recommendation model that is designed for learning richer session contexts by conditioning on all permutations of the session prex. This approach provides a unied framework for leveraging the ability of the Transformer's self-attention mechanism in modeling session sequences while taking into account the user's main interest in the session. We empirically evaluate the proposed method on two benchmark datasets. The results show that DTER outperforms state-of-the-art session-based recommendation methods on common evaluation metrics.
Trustworthy AI'21

In this workshop, we are addressing the trustworthy AI issues for Multimedia Computing. We aim to bring together researchers in the trustworthy aspects of Multimedia Computing and facilitate discussions in injecting trusts into multimedia to develop trustworthy AI techniques that are reliable and acceptable to multimedia researchers and practitioners. Our scope is at the conjunction of multimedia, computer vision and trustworthy AI, including Explainability, Robustness and Safety, Data Privacy, Accountability and Transparency, and Fairness.
Convexity Defect Based Hand Gesture Recognition Using OpenCV

The technology of gesture recognition systems focuses on improving human-machine interaction and proximity control. This paper mainly eyes on the hand gesture recognition system that can be used for controlling different automated systems such as automated wheelchairs for physically impaired people, robotic manipulators, and similar mechanisms. Out of several techniques, a convexity defect-based system is discussed here. As the platform, Spyder is used, which is an open-source cross-platform integrated development environment (IDE). The OpenCV library is used, which is a library of functions focusing on real-time computer vision. After developing the system for multiple features of different finger-based gestures, the distance-based accuracy for each feature is measured, where at the most effective distance (2ft) the average accuracy is found to be 93.75% with real-time response. In the case of the following technique, the gesture orientation is not mattered so the system is kept simple and time-efficient. Keywords: Hand gesture recognition, convexity hull defect, human-machine interaction, Python, Spyder, OpenCV
Distribution and quantification of Wigner negativity remotely generated via Einstein-Podolsky-Rosen steering

Wigner negativity, as a well-known indicator of nonclassicality, plays an essential role in quantum computing and simulation using continuous-variable systems. Recently, it has been proven that Einstein-Podolsky-Rosen steering is a prerequisite to generate Wigner negativity between two remote modes. Motivated by the demand of real-world quantum network, here we investigate the shareability of generated Wigner negativity in the multipartite scenario from a quantitative perspective. By establishing a monogamy relation akin to the generalized Coffman-Kundu-Wootters inequality, we show that the amount of Wigner negativity cannot be freely distributed among different modes. Moreover, for photon subtraction -- one of the main experimentally realized non-Gaussian operation -- we provide a general method to quantify the remotely generated Wigner negativity. With this method, we find that there is no direct quantitative relation between the Gaussian steerability and the amount of generated Wigner negativity. Our results pave the way for exploiting Wigner negativity as a valuable resource for numerous quantum information protocols based on non-Gaussian scenario.
JSP-Based English Teaching Model and Reform for Computer Science Major

Computer English and college English are both language courses and the latter is a public compulsory course, which has many influencing factors on the English courses for computer majors in the middle and late period of university. Computer English is an English course for computer majors after public English, which integrates computer knowledge and English application ability. IT is an important tool course and has become one of the necessary tools for students to take the domestic and international IT certification examinations. It is very important for students majoring in computer science to learn English well, but there are many problems in current teaching. This paper studies how to combine computer application technology and network technology with teaching, and puts forward the teaching mode and reform strategy of computer specialized English based on JSP. Make use of the important characteristics of active and controllable communication in the network to realize communication and learning between teachers and students, classmates and classmates, and make full use of network resources.
Visitor’s risk awareness towards water recreation activities at Tasik Dayang Bunting, Langkawi, Kedah

Over the years tourism has grown rapidly and for many regions and countries worldwide, it is an important sector. It is also said that tourism is the largest sector in the world and many people participate in this sector. Recreation becomes an alternative choice to release stress from work, studies and any of problem occurred. The accident during water recreation activities always happen at anywhere and anytime. This is due lack of information related with the safety and risk awareness about water recreation activity can therefore lead to the accident at the recreation place that can affects perception of visitor’s towards safety and the profit will reduced. This assessment needed to know the visitor’s risk awareness towards water recreation activities at Tasik Dayang Bunting Langkawi, Kedah. The 150 questionnaires were distributed towards visitor’s to know level of safety knowledge on water recreation activities. In addition, on the result shown the shows the positive effect of respondents about the level of visitors risk awareness towards water recreational activities. The evaluations of visitor’s motive to do water recreational activities in TDB are to encourage visitors to view and enjoy the environment of the existing recreational areas in Malaysia including in TDB. Then, the socio-demographic of visitors are from multiple races and from overseas who come to TDB. This analysis really important because important to prevent any circumstances and can reduced the risk’s death due of drowning.