Reviewerly/exHarmony huggingface dataset:
Power Assist Wheelchair For Physically Challenged Person

A physically challenged people face many problems in their day to day life, they need to seek help from others to perform their routine tasks such as for going hospital, malls or market etc. Mobility of the Physically Challenged people is a great concern of the society. Considering these in mind, the present work is focused on the history of wheel chairs, market surveys, and physically challenged people requirements. On the basis of gathered information the design of the power assist wheelchair which has low cost and approachable for poor and middle class population. Power assist is the attachment made to fit any standard wheelchair. The designed wheelchair can be used manually or can be used as electric wheelchair based on the requirement of the user.
Optical Character Recognition using Neural Network

Character Recognition (CR) has always been an active research field in the past and is still a challenging research topic due to its wide range of applications. The most important methods of offline handwriting recognition can be divided into two categories: overall and segmentation- based. When considering the global features extracted from the complete word image, the holistic method is used when recognizing limited vocabulary. On the other hand, the segment-based strategy uses a bottom-up approach, starting at the line or symbol level, and processing meaningful words. After segmentation, the problem comes down to recognizing a single character or line. Therefore, the system can use unlimited vocabulary.
Neuromorphic Photonics for Optical Communication Systems

Neuromorphic photonics creates processors 1000 × faster than electronics while consuming less energy. We will discuss the role of neuromorphic photonics in optical communications, review existing approaches, and outline the required technologies to evolve this field.
Exploration and Practice of Organic Chemistry Online Teaching Based on the Zhihuishu and Tencent Classroom

Two online education platforms, Zhihuishu and Tencent classroom, were applied to the online teaching of organic chemistry.The Zhihuishu was mainly used for pre-class preview and after-class homework assignment, while Tencent classroom was used for live teaching, which complemented each other's advantages to ensure the smooth progress of online teaching and achieved good teaching effects.
Case Study : Pilot Corporation / Wan Mohd Zawir Wan Mokhtar

The product suggested by our group is marker pen. Permanent markers are durable pens that can be written on surfaces such as glass, plastic, wood, steel, and stone. The ink is usually resistant to friction and heat, and can last for several years. However, depending on the surface and the marker used, the traces can often be removed with either intense scrubbing or with chemicals such as acetone. A whiteboard marker, or a dry-erase marker at some places, uses an erasable ink, designed to be used on a glossy (or matte-finished), non-porous writing surface, for temporary writing with overhead projectors, whiteboards, and the like. However, there is a comment that it is hard to see the writing when in the dark situation especially in the classroom. So our suggested product will be glow in the dark. When write at walls or paper or whiteboard, the writing will be glowing in the dark. There were so much product that have been used ‘glow in the dark’ style but why there is no for marker pen? So our suggested product is user friendly as this new innovation will be focused on teachers or lecturers and also students
Factors Effecting English Speaking Ability of Second Year Students in the Faculty of Humanities and Education, Mahamakut Buddhist University

The objectives of this research study factors effecting English speaking ability of second year students in the Faculty of Humanities and Education, Mahamkut Buddhist University. The study sampling subjects were 40 second year students who are studying in first semester 2016 at Mahamakut Buddhist University. The sampling was chosen from 2 faculties are Humanities Faculty and Education Faculty.The instrument used for data collection was questionnaire. Data were analyzed for percentage, mean, and standard deviation.The findings of the study indicate that the second year students from 2 faculties namely: Humanities faculty and Education faculty in first semester 2016 at Mahamakut Buddhist University thought factors effecting English speaking ability of second year students in the Faculty of Humanities and Education, Mahamkut Buddhist University at a high level. When considering by aspect, it was found that the highest mean was learning behavior, student’s personality, student’s attitude toward learning, basic experience in studying English, and promoting and supporting the learning of the family.
Content Based Medical Image Retrieval System Based On Multi Model Clustering Segmentation And Multi-Layer Perception Classification Methods

Content-based Medical Image Retrieval (CBMIR) has been active in the research field over the past few years. A CBMIR system recovery's performance depends largely on some aspects, the nature of which has been studied in detail for decades. Although different strategies have been proposed, it is still one of the most challenging issues in current CBMIR research. This is mainly due to the so-called semantic gap between the device and the high-resolution image-low pixel capture. Today's medical images in daily practice have been increasingly created on the scale of millions. Recovering medical images from huge classifications is difficult, so it rises to the Content-Based Medical Image Retrieval System (CBMIR) system. In existing systems, images are first retrieved and then classified. Also, the retrieval rate obtained by the existing method is not ideal. Therefore in this work, a Clustering Segmentation and Multilevel Tetrolet Feature Extraction strategies are proposed to overcome the existing work drawbacks. The simulation of the proposed work is developed using Matlab simulation software. The predictive result for this work has encouraged performance, and the method is cost- effective compared to the purposes described in the literature. In terms of performance measurements, i.e., Accuracy, Precision and Recall.
Role of Geospatial Concordance And Exams Through Learning Management System in The Education Sector

Nowadays, there are more web-based online exam systems are developed. Bearing in mind the increasing studies on the web based educational systems the present study has considered the role of geospatial concordanc in the context of providing computer education. Additionally, this paper aims to identify and evaluate the existing online secure exam features, to generate questions based on difficulty and providing authentication for the generated question using Advanced Encryption Standard (AES) encryption, and to evaluate the proposed web-based system. The system is developed by using Hyper Text Markup Language (HTML) and PHP (Hypertext Preprocessor (PHP) language). The scope of this paper is based on a short structured question. The paper produced an online exam system that generates question-based on difficulty and secured the generated question using AES encryption. In the future, this system could be upgraded with different types of questions. Moreover, the study also revealed that the geospatial concordance is necessary and people do assign psychological meaning to them at different levels primarily dependent on the psychological and physical distance from them.
LibGuides: Marketing Outreach Toolkit: Content

This project consists of a monthly emailed checklist of outreach tasks that all build on one another to achieve large-scale goals. The idea is to frequently show stakeholders that the library is advancing campus priorities.
Quantum Key Secured Communications Field Trial for Industry 4.0

We seamlessly integrate quantum key distribution with &gt; 1Mb/s secure bit rate into a smart-manufacturing production network. This provides a 10Gb/s quantum key encrypted link with long-term stable operation, compatible with national network infrastructure.
LibGuides: Cataloging Manual: Cataloging/Accepting Donations

The Northwest Arkansas Community College Cataloging Manual. See the library's donations policy for explanation about who approves donated items and the types of items the library accepts.
Research and Practice of a Novel Six-in-one Assessment System for Analytical Chemistry Experiments

The common assessment methods for analytical chemistry experiments are not scientific and instructive enough. According to the curriculum characteristics of analytical chemistry experiments and talent training goals, an integrated assessment system covering six modules including pre-lab test, virtual simulation experiment, lab work, data quality, calculation and report has been constructed in this essay. The detailed evaluation indicators and specific implementation procedures are also introduced. In addition, the ideological and political education elements contained in the analytical chemistry experiments have been explored and integrated into the assessment system to guide students to transform the knowledge and skills they had learned into inherent virtues. Pilots in some classes have proved that the Six-in-one assessment method is feasible and operable which has been highly praised by teachers and students.
Identification Phishing Websites Using Machine Learning

The phishing process is a huge threat to society these days. These websites target human information rather than hacking into our systems. It is a process where the criminal attacks a victim online to obtain the victim’s data. Nowadays, phishing is one of the massive attacks on the users of the World Wide Web. Each time an attacker will use a new technique new way to attack a user. Hence, it is needful to have a real-time solution that is fast, reliable, and mainly efficient. Here, we develop a system that is efficient and reliable and which is adaptive to the changing environment. URLs are unique for all the websites also it is an identity of a website, so here we use the URL data as input and identify a phishing website and help the users from getting phished. This project offers an intelligent system that identifies a phishing website. The system uses the Logistic Regression technique for identification. Since the Logistic Regression technique has reportedly has good performance in classification it has been selected.
PENERAPAN MODEL PEMBELAJARAN QUANTUM TEACHING DALAM UPAYA MENINGKATKAN HASIL BELAJAR MATEMATIKA SISWA DI KELAS IV SD NEGERI 157618 HUTAGURGUR I

The Problem In This Research Is The Low Mathematics Learning Outcomes Of Students In The Material Of Simple Room Building In Grade IV SD Negeri 157618 Hutagurgur I, To Overcome This Problem In This Study The Application Of The Quantum Teaching Learning Model., This Research Is A Classroom Action Research. From The Results Of The Initial Test It Was Found That The Lowest Score Was 21 And The Highest Score Was 86. Studied) As Many As 13 People (59.09%). And The Mean Value Of The Initial Test Was 63.59. After Giving Action In Cycle I Through The Stages Of Implementing The Quantum Teaching Learning Model, At The End Of The Lesson, The Students Were Given A Test Of Learning Outcomes, So The Class Average Value Was 77.27. In The First Learning Outcome Test, It Can Be Seen That There Were 19 Students Who Completed Learning (86.36%) And 3 Students Who Did Not Complete The Study (13.64%).Based On The Results Of The Above Research, It Can Be Concluded That The Application Of The Quantum Teaching Learning Model Can Improve Student Learning Outcomes In Simple Building Materials In Class IV SD Negeri 157618 Hutagurgur I.
Postphenomenology of FRP Material on Grand Banks Yachts Production Ship Design

The use of Fiberglass Reinforcement Plastic (FRP) as the basic material for forming ships does not necessarily change the appearance of the fishing yacht design produced by Grand Banks Yachts (GBY), which has been famous for a long time with its classic style. The phenomenon of GBY product models with classic characteristics is interpreted as beautiful by special users with all their interpretations of beauty, thus attracting a lot of interest. The research problem in disclosing the concept of design sustainability through GBY's FRP technology is interesting to examine with the structuralist functionalism paradigm, where FRP elements have characteristics and properties that can facilitate and even replace the role of humans in their use. The case study method used in this study explains that the FRP material on the GBY vessel can be interpreted as a social phenomenon in a posthumanist context, assisted by Don Ihde's post-phenomenological theory, which dissects the relationship between humans versus this technology. Explain the research results in the form of individual and collective interpretations as an aesthetic expression of a GBY product concept which is a posthumanist phenomenon. The research objective as the end result is to find a posthumanist concept in FRP material technology in aesthetic interpretations of GBY products.
Devising An Entropy-Based Approach for Identifying Patterns in Multilingual Texts

Even though the plagiarism identification issue remains relevant, modern detection methods are still resource-intensive. This paper reports a more efficient alternative to existing solutions.The devised system for identifying patterns in multilingual texts compares two texts and determines, by using different approaches, whether the second text is a translation of the first or not. This study's approach is based on Renyi entropy.The original text from an English writer's work and five texts in the Russian language were selected for this research. The real and translations that were chosen included translations by Google Translator and Yandex Translator, an author's book translation, a text from another work by an English writer, and a fake text. The fake text represents a text compiled with the same frequency of keywords as in the authentic text.Upon forming a key series of high-frequency words for the original text, the relevant key series for other texts were identified. Then the entropies for the texts were calculated when they were divided into sentences and paragraphs.A Minkowski metric was used to calculate the proximity of the texts. It underlies the calculations of a Hamming distance, the Cartesian distance, the distance between the centers of masses, the distance between the geometric centers, and the distance between the centers of parametric means.It was found that the proximity of texts is best determined by calculating the relative distances between the centers of parametric means (for texts ‒ exceeding 3, for translations ‒ less than 1).Calculating the proximity of texts by using the algorithm based on Renyi entropy, reported in this work, makes it possible to save resources and time compared to methods based on neural networks. All the raw data and an example of the entropy calculation on php are publicly available.
An Abnormal Activity Detection Using Harris corner, Optical Flow and Dynamic Thresholding

In this paper, new method has been introduced for identifying abnormal activity from videos. This method is totally based on motion which can be calculated by applying optical flow method. In this method key points are also detected for calculating method. Key points are detected by Harris corners. For identifying abnormal activity dynamic threshold is used. For calculating dynamic threshold energy has been used. This method doesn’t used any prior knowledge or training data. It also do not required static threshold for identifying abnormal activity. This method can detect abnormality from UMN, BEHAVE and UCF-Crime dataset. The activity identified robustly. It also doesn’t require much computation.
ENT 530 Social Media Portfolio: La Noire Fragrances / Fatin Nur Shaheera Mohd Fauzi

Our company established on the 24th September 2020. La Noire Fragrances was created to be known as the authentic perfume shop of our product. We invented one of the most authentic, original unique scent yet affordable of perfume than others as we produce few additional perfumes which not yet exist in our competitors. To maintain the authenticity, we need to ensure the quality that comes with it before we deliver to our customer. This is because we learn that most of the beauty,cosmetics and personal care companies lost its quality when they produce lots of quantity. That is why we produced our perfumes with our own unique scent recipe assisted by the well-known fragrances expert from Malaysia. We always strive to producee the finest quality of a perfumes for our dear customers. Therefore, we require our workforce to prioritize the quality of each of our product before deliver to the customers. The brand’s success and its consumer’s satisfaction are the result of consistently meeting the high expectations that are expressed through the more potential customers. We are driven by a passion in preparing our product so that it will feel like the expensive one of the kind perfumes because we want our customers to experience of the top notch quality perfumes with affordable prices. Hence, we also ready to receive any feed backs from our customers in order to fulfil their needs and satisfactions towards our perfumes.
Complete System Integration of Chip-Based Quantum Key Distribution Devices

Solutions for a practical, wide-scale deployment of quantum secure communication devices have long been awaited for. Recent reports of quantum key distribution (QKD) chips, yet promising, were restricted to proof-of-concepts of individual components. We now demonstrate a complete QKD system, entirely based on photonic chips and distributing quantum secure encryption keys at high bit rate. This establishes photonic integration as a viable solution for a low-cost, scalable deployment of QKD.
Business Model Canvas : Measuring Set with Scale / Afifah Allias

Measuring sets with scale will help the consumer is weighing their ingredient accurately by using a digital scale with a wide LCD at the holder of the measuringset. The quality of the product is very high because it has a screen that will auto power off after 1 minute without operations. Therefore, the customer can easy to read the weight of the ingredient. It will save battery power and money. The readings will auto hold when it reaches a stable weight and presses the hold button to unlock the screen. Customers need to keep a balance to ensures precise measurement for their ingredients. The price that the company sells to customers is affordable with the new technology provided
Elliptical curve cryptography for data confidentiality with output feedback mode

With the increase in Internet usage, Data security is a critical issue to ensure the safe transmission of information through the internet. As more users started utilizing internet services, this attracts a great deal of cyber-criminals. So, we propose a mutual authentication mechanism based on Elliptic curve cryptography for faster data transmission and to provide a high-security level. Other techniques like Diffie-Hellman and RSA cryptographic methods are based on the creation of keys by using substantial prime numbers. Hence, basic design requires a lot of computational power. This Elliptical Curve Cryptography is used along with output feedback mode. Any bit errors that may occur throughout transmission aren't propagated to affect the decryption of the resulting blocks. ECC with output feedback mode is a very efficient public-key cryptography mechanism. It provides privacy and security with lesser computation overhead and can offer faster encryption for large data blocks.
Computational learning methods for early detection of ovarian cancer

Artificial Intelligence methods can be very effective in classification tasks that involve the processing of ordered sequences of data. Here we explore two different approaches to tackle the problem of ovarian cancer detection from a sequence of longitudinal measurements of several biomarkers. The first approach relies on a Bayesian hierarchical model whose fundamental assumption is that measurements taken from case subjects exhibit a changepoint in one or several biomarkers. The second approach is a purely discriminative machine learning algorithm based on the use of recurrent neural networks, a kind of artificial neural network specially suited to the processing of inputs of different lengths.
The Accuracy and Stability of Body Representation

How we perceive our bodies and how the body is represented in the brain is not yet fully understood. We need accurate information about our bodies in order to interpret and react to sensory information that is constantly being received and that is coded relative to our body. My dissertation aims to understand how the body is perceived and represented in the brain by exploring the accuracy and stability of body representation. I developed a novel two-alternative forced choice adaptive staircase psychophysical method to determine how accurate people are in judging real and distorted life-size images of their body. Participants were sequentially shown two life-size images of their body (one interval containing the undistorted image and one interval containing the distorted image) and had to report which image most closely matched their own perception of their body size. Width and length dimensions were distorted separately. The image was also presented in different orientations (such as upright, right, left, and upside down) in order to assess how accuracy perception changes when the image is presented in familiar and unfamiliar views. Four separate experiments were conducted to test perceived size for: 1) the face, 2) the arm, 3) the hand, and 4) the full body. The goal of these studies was to measure accuracy in different orientations, for both the width and length dimensions, to obtain baseline values of how distorted the brains representation of various body parts are. I demonstrated that there are distortions in perceived size and that factors such as body part, orientation, sex, and body satisfaction impacted accuracy. To explore the nature and extent of the brains plasticity and flexibility, I investigated how manipulating body representation affects body perception and whether accuracy values can be changed. Manipulating body representation using both visual and vestibular methods resulted in changes to perceived body size accuracy. These results provide insights into how the brain represents the body, revealing that body size perception is flexible and plastic.
Recognition of Sign Language using Deep Neural Network

Speech impairment affects an individual’s ability to communicate. People affected by this problem, suffer by the communication barrier with the normal people. Hence, to express their emotions and thoughts people will use sign language for their communication and. Although sign language is common in world, there may be a difficulty for people who do not have knowledge about sign language to communicate with speech impaired people who knows the sign language. Now there is a prominent growth in the field of computer vision and deep learning, which has been tremendous development in the fields of sign and motion recognition. The proposed model focusses on overcoming the challenges in verbal communication between non-sign language speakers and sign language speakers by building a deep learning model to recognize alphabets of American sign language.   The model was trained on the dataset collected from Kaggle website which consisted of 26 American Sign Language alphabets. The model achieved 99.3% mean average precision in recognition of sign and average probability value for test image achieved was 0.99. The deep learning method used to build the model achieved more accuracy than the previous solutions.