Reviewerly/exHarmony huggingface dataset:
Interactive Grayscale Image Colorization with Generative Adversarial Networks

Grayscale image colorization is a classical image editing problem. There are two different methods for colorization. The interaction-based colorization method can generate results based on user interaction. However, this method requires considerable artificial interaction to achieve the desired results. Another method is automatic colorization based on deep learning. However, in this case, the colorization result is unique and cannot be adjusted if the result is incorrect or if the user has additional requirements. In this paper, we combine deep learning with user interaction and propose a grayscale image colorization method based on generative adversarial networks. In this method, a full convolutional neural network is constructed based on the U-net structure as a generator that can process images of any size. The training data is automatically generated by randomly simulating the interactive strokes. The experimental results indicate that this approach can efficiently achieve good colorization results and is capable of generating results based on different user interactions.
Emotional Research on Mobile Phone E-Commerce Reviews on LSTM Model

Emotional analysis has been omnipresent. Grabbing adequate information from online shopping evaluation and analyzing it can provide a basis to choose for businesses or consumers. Taking “Jingdong Mall” mobile e-commerce review as an example, the authors of this paper use web crawler technology to obtain sufficient data of 12 products under 7 mobile phone brands in the sales ranking. The authors then use Python’s Jieba library to segment the reviews and gensim module to train word2vec word vector model and classify the mobile e-commerce reviews by constructing LSTM neural network model. It is concluded that the consumers’ views that there exists some advantages and disadvantages of “Apple” and “Huawei” mobile phones.
A Robust Image Security System for Cloud-Based Smart Campus Using LBP and PCA

Most of the educational institutes now days because of increased threat to the campus security have started installing the biometric security support system for personal identification. In real time situation, a large number of biometric data get accumulated which could be an unbearable burden for the biometric security system of a digital smart campus. This had attracted the research community in the field of computer vision and security to use the convenience of cloud computing and store their large data set to cloud servers. During the transform of the bulky data to the cloud source there is necessity of reducing the computational burden and storage burden on the intelligent biometric security system. In this paper a enhanced method for personal identification using biometric system in cloud environment is proposed in which first biometric images are encrypted using either block encryption technique or pixel encryption technique. Out of these encrypted images local binary pattern (LBP) features are extracted for identification or classifications due to which privacy can be preserved. Further PCA is applied on LBP which helps to reduce the computational time and data transfer time to cloud. These extracted features using LBP and PCA are used for equivalent image retrieval using histogram equalization technique for personal identification.
Exploration and Research on CAUX in High-Level Context-Aware

With the rapid development and popularity of mobile devices, the aggressive adoption of mobile products poses new challenges to both users and User Experience (UX) researchers: Reducing the disruption to users when collecting subjective data, and recognizing users’ subjective data. The goal of this study is to enable the existing context-awareness tools with the ability to collect and recognize high-level context data sought by UX researchers. In this study, the author selects the idle context of users as the research objective, asks users to mark their own data, and summarizes the mapping relationship between the combination of three groups of reliable low-level context information. The Context Awareness User Experience (CAUX) system, which combines context-aware with remote data collection technology, is used for this research. This study shows that when students are both in both a high-level and idle context, if the low-level context combination is used to judge, the accuracy rate is 88%. This method of judging high-level context based on the combination of low-level context information can effectively solve the defects in the perception of high-level contexts by the current remote context-aware tools, thereby solving one of the challenges with remote user experience evaluation.
Guides: Edbird E-Tutoring: Mathematics

This guide has been created to support you in your role as an Edbird E-Tutor by curating where to discover: activities, worksheets, background information, online interactives and more to use in your tutoring sessions.
What Does It Mean for ML to Be Trustworthy?

The attack surface of machine learning is large: training data can be poisoned, predictions manipulated using adversarial examples, models exploited to reveal sensitive information contained in training data, etc. This is in large parts due to the absence of security considerations in the design of ML algorithms. Yet, adversaries have clear incentives to target these systems. Thus, there is a need to ensure that computer systems that rely on ML are trustworthy. Fortunately, we are at a turning point where ML is still being adopted, which creates a rare opportunity to address the shortcomings of the technology before it is widely deployed. Designing secure ML requires that we have a solid understanding as to what we expect legitimate model behavior to look like. In this talk, we lay the basis of a framework that fosters trust in deployed ML algorithms. The approach uncovers the influence of training data on test time predictions, which helps identify poison in training data but also adversarial examples or queries that would potentially result in a leak of private information. Beyond immediate implications to security and privacy, we demonstrate how this helps interpret and cast some light on the model's internal behavior. We conclude by asking what data representations need to be extracted at training time to enable trustworthy machine learning.
Perancangan Busana Yang Dapat Beradaptasi Dengan Perubahan Fisik Wanita Dalam Upaya Berkelanjutan

Abstract Eco- friendly lifestyles become a trend that is currently applied by the majority of women, due to several factors that make the public concern to consume environmentally friendly products, one of which is the use of sustainable fashion products. due to the impact of not optimal clothing use, which is caused by physical changes experienced by most women today, so that what is caused is the use of clothing that is not optimal which causes increased post-consumption waste. For this reason, the application of the sustainable fashion method with the application of zero waste pattern with the transformation fashion feature becomes an opportunity to create clothing that can be used for a long period of time and is comfortable to use for women with dynamic physical (easily changeable) based on the current female body type. , with the use of striated woven cloth that is applied to women's clothing. So the purpose of this research is to make clothing that can be adapted to changing physical shape and increase its use, minimize the waste produced, and preserve striated woven fabric by optimizing its application to fashion products in the present and future. Keywords: Eco-friendly lifestyle, women's physical change, sustainable clothing, lurik woven fabric
modum.io: Funding a Blockchain-Based Start-Up's Supply Chain Solution (Teaching Case)

At the end of June 2017, the founder of modum.io AG, Marc D., was preparing for an important meeting that would take place the next day with a major investor when he received an email. The goal of the meeting was to negotiate the final terms of a commitment. However, the email from the investor indicated that the negotiations related to modum.io would not make it onto the agenda. After months of promising discussions, the entrepreneur was disappointed by this unexpected decision. With a limited cash flow, the founders faced two choices: (1) provide a cash bridge until the negotiations could resume or (2) come up with an alternative plan. Modum.io was focused on one core business idea: streamlining supply chain processes by combining innovative technologies and proprietary hardware to provide an efficient, reliable, and secure shipment monitoring solution. More specifically, modum.io’s first use-case was aimed at monitoring temperature-sensitive pharmaceutical products in the supply chain. Their sensor devices are connected to the Internet of Things (IoT), and the collected data is stored on the blockchain to ensure integrity and authenticity.
Performing a Risk Assessment

In this chapter, we will learn how to perform a risk assessment for a serverless application. We will explore how to understand how the application works, which includes reviewing documentation, source code, and system accounts and using the application. We will discuss why we scope the risk assessment. We will learn how to develop a threat model and how to use it to start creating the risk assessment.
대장내시경 후 대장암: 중간 대장암의 원인과 예방

Colorectal cancer (CRC) is the third most commonly diagnosed cancer and the fourth leading cause of cancer death in the worldwide. Colonoscopy is the gold standard for screening and surveillance of CRC. Removing adenomas by colonoscopy has lowered the incidence and mortality of CRC. However, colonoscopy is imperfect for detection of colorectal neoplasia. After a colonoscopy that is negative for malignancy, CRC can be diagnosed. These are termed as post-colonoscopy CRC (PCCRC). The proportion of PCCRC, among all CRC was reported to be 1.8% to 9.0%. It occurred 2.4 times more in the right colon than in the left colon. The causes of PCCRC are missed lesions, incomplete resection, and new lesions. Among these causes, missed lesion and incomplete resection are procedural factors and preventable. Therefore, it is necessary to improve the quality of colonoscopy to minimize the occurrence of PCCRC. (Korean J Gastroenterol 2020;76:314-321)
Weaken Grammatical Error Influence in Chinese Grammatical Error Correction

Chinese grammatical error correction (CGEC), a task of correcting grammatical errors in text, is treated as a translation task, where error sentences are “translated” to correct sentences. However, some grammatical errors in the training data can confuse the CGEC models and have negative influence in the “translating” process. In this paper, we propose a Grammatical Error Weakening Module (GEWM) to impair the negative influence of grammatical errors in CGEC task. The grammatical error weakening module first extracts contextual features for each word in an error sentence via context attention mechanism. Then the proposed module uses learnable error weakening factors to control the proportion of contextual features and word features in the final representation of each word. As such, features from grammatical error words can be suppressed. Experiments show that our approach has better performance compared with the baseline models in CGEC task.
The most preferred teaching methodology: A questionnaire based assessment from medical students at Bidar institute of medical sciences, Bidar

Overhead projector (OHP) and Microsoft power point presentation (PPT) are the newer methods of teaching. The PPT is now the popular teaching tool in the delivery of lectures. Power point based lectures are increasingly used in the medical colleges in delivering lectures. Various studies have been conducted to study the effectiveness of the different methods of teaching. In one study the students preferred the traditional blackboard teaching as the best teaching method [5]. Whereas in another study power point was the considered as the best teaching method by the students. In the present study the medical students preferred blackboard as the effective teaching aid compared to the power point teaching method. 68(61.81%) students preferred blackboard as the teaching tool. 71(64.54%) students considered that blackboard helps in better perception of the subject compared to power point presentation. 64 (58.18%) of the students were of the opinion that blackboard helps to retain the information delivered in the class.
ENHANCING LEARNER’S READING COMPETENCY THROUGH PROJECT-BASED PRE-COOPERATIVE MULTILITERACY (Descriptive Study at CLC Hikmah District. Ciamis, CLC Al-Ghifari District. Cirebon, and CLC Geger Sunten District. West Bandung)

Education multiliteracy is an education that emphasizes on increasing the diversity of literacy in all aspects of life. The multiliteracy education program is a program of literacy by using a variety of approaches (arts, culture, environment, technology, race, ethnicity, gender, and others) are relevant to the learners to achieve and or develop literacy competencies and improve the income and quality of life of participants students. The focus of the problem is as follows: How to increase literacy skills of reading advanced literacy students through Project-based multiliteracy learning models in CLC Hikmah District. Ciamis, CLC Al-Ghifari District. Cirebon, and CLC Geger Sunten District. West Bandung? The project-based multiliteracy pre-cooperative learning model is multiliteracy learning with the theme of science and technology pre-cooperative sub-themes using project-based learning strategies. Learners during learning in enhancing the ability of literacy such as reading, writing, and arithmetic in the language of Indonesia to be given charge of pre cooperatives. Wherein the output of this study is the formation of pre-cooperative business groups, in the process of establishing this cooperative course pre herded learners to complete the project in any appropriate syntax learning project-based learning, namely: 1) Determination of project. 2) Designing project completion steps. 3) Compilation of project implementation schedules. 4) Project completion. 5) Report preparation. 6) Evaluate the process and process results. Based on the research results obtained Asymp.sig (2-tailed) = 0,000 <0.05 then Ho is rejected and Ha is accepted meaning there is an average difference between the pre-test and post-test learning outcomes, which means there is an influence on the use of the Project-based pre-cooperative multi-literacy model towards increased literacy skills in reading students.
An Effective Face Color Comparison Method

With the development of image processing technology and application, the recognition requirements for facial details are getting higher and higher. This paper presents a face color comparison method, which can compare the facial color difference quickly. At the same time, through experiments, this paper determined the formula of color difference used by the method and obtained the good accuracy of the method in accordance with human vision, which shows that the method has certain practicability in facial color comparison.
Feasibility of active contact tracing of COVID-19 infections in primary care: A pilot project

Over the past months, COVID-19 has turned healthcare and the whole society upside down, also in Belgium Social distancing remains the most important pillar of transmission control, but if the lockdown measures are lifted, alternative and preferably equally or more efficient tools are needed to keep the situation under control Testing, tracing and isolation (TTI) is a method that has been used in many countries since the beginning of the crisis, as advised by the World Health Organization, but our health system is not prepared for it At the end of April 2020, Medicine for the People conducted a first pilot project on contact tracing amongst its patients, to examine its consequences in terms of organization and resources They contacted a hundred recent possible COVID-19 infection batients from their patient population, asking them to test family members for COVID-19 infection In this article, they describe the process and conclusions from this operational exercise
Continuous Track Chair for Disabled Person

One of the basic problem of the user on manual wheelchair is architectural barrier and overcoming obstacles by a wheelchair always remains as topic of discussion for many researchers. This project involves an Functional design and fabrication of an stair climbing functionality will be upgraded by changing its structure design and mechanism. The important parts of this product are Styrene Butadiene rubber belt, frame and driving mechanism climbing wheelchair for regular use by disabled people. The design of frame will be done by considering different type of load, different type of stresses on different positions. The main factor of wheelchair is laid on the angle of stair and centre of gravity of whole system. Understanding the various issues concerning the function of wheelchair and introduce a advance design that will be an help for the disabled people. From this project we hope to build an alternative wheelchair and their mechanism system for the needful users.
Power Platform Integration in Power Automate

While this part of the book is devoted to Power Platform product integration, you likely already have learned that Microsoft Flow is a tool devoted to integration among hundreds of products. Within the Power Platform, it is sometimes referred to as the glue that brings all things together. In this chapter, you will learn about the integration points that exist between Microsoft Flow and the other Power Platform products.
Just how “blind” are we to advertising on Instagram? : En kvalitativ studie om hur människor uppfattar och tolkar betalade företagsinlägg som sker via Instagram.

In the beginning of 1944, the world could see a spread in the use of banners, a new digital way to market through. This quickly became a popular way to market. But this also led to discussions in r ...
Research on the Blended Teaching Mode Combining Mooc with Moso Teach

MOOC teaching mode has been developing rapidly in the world in recent years due to its advantages of learning process free from time and place and the ability to share high-quality teaching resources. However, in practice, there are some limitations. This paper explores a blended teaching mode combing MOOC with mobile intelligent teaching, and takes “Theory and Practice of Tea Culture” as an example to construct the teaching mode framework, so as to further improve the function of MOOC and enhance the teaching application effect of mobile intelligent teaching mode.
A Novel Simplified Approach for Text Line Extraction of Handwritten Malayalam Document

This paper presents a novel and simple method for extracting individual lines from handwritten Malayalam documents.The challenge involved in text line extraction of handwritten document is segmentation of touching lines. As far as Malayalam language is considered, symbols like chandrakkala will be classified into separate line due to the small gap between the Malayalam alphabet and the symbol chandrakkala. This paper addresses the possibility of touching lines and misclassification of character like chandrakkala into a separate line. In the proposed method, the scanned handwritten document is divided into vertical stripes. Using horizontal projection method lines are extracted in each vertical stripe separately. Touching lines, segmentation of character like chandrakkala into separate line and extra lines due to noise are addressed using the median values of the height of lines in each vertical stripe separately. The handwritten document image is divided into vertical stripes prior to line segmentation to account for the possibility of skewed lines. When the document is divided into vertical stripe, the characters will be cut in between. This paper also presents a solution to join the characters cut in between when the document is divided into vertical stripes. This is done by compensating for the distance of characters from the top of the line at the joining edge of the vertical stripe.
Content Enrichment Using Linked Open Data for News Classification

In the Web era, people tend to rely on the Web to receive news instead of traditional ways such as newspapers. However, the amount of news generated online is enormous that prohibits people from obtaining their interested news. Most of the common newswire sites still classified the news manually that costed a lot of human effort and may receive unstable result. In the past decades, text classification has been a hot topic and received attention from many scholars in areas such as natural language processing, information retrieval, and machine learning, etc. Various classification algorithms and models have been developed to tackle this problem. In the meantime, Tim Berners-Lee proposed the concept of linked data in 2006. Linked open data (LOD) were constructed prevalently since then. In this study, we try to incorporate LOD into the news classification system. We collected four datasets in order to evaluate the accuracy in various text lengths with or without incorporating LOD. Three classification algorithms, namely K nearest neighbors, support vector machines, and decision trees, were used to classify the news. The experimental results show that the linked open data can improve the accuracy in news classification, especially for short texts or small datasets.
Lightweight Fine-Grained Search Over Encrypted Document

In fog computing, we mainly focus on lightweight fine-grained ciphertexts search (LFGS) which is a composite of CP-ABE and SE technologies, fog computing is used as an additional technology of cloud computing. The LFGS can transfer computation and storage from user to fog nodes. Its main focus on using attributes update in order to prevent unauthorized access which automatically resist CKA and CPA. In the modern world, this demo proved LFGS system performance efficiency and workable nature.
The Theoretical Framework Design of College English Teaching Mode under Modern Technology

This paper attempts to put forward the theoretical framework of the new college English teaching mode under the modern educational technology. The theoretical framework integrates the multi-modal, multimedia, multi-environment theory, the integration of computer technology and foreign language curriculum ecology and constructivism. It takes the creation of environment and the change of teaching structure as its main features, and multi-modal experience and mode transformation learning as the focus of practical operation. Compared with the previous theoretical framework based solely on constructivism theory or / and computer-aided language learning theory, the framework of this paper is more systematic and detailed, and more instructive to the design of practical teaching mode.
Lane Recognition System for Machine Vision

With the rapid increase in the number of cars, driving safety has been paid more and more attention. The lane line recognition algorithm has also become a hot research area. In order to realize the unmanned driving of smart cars, this article aims to study a lane recognition system for machine vision. First, the realization of the host computer is introduced. The host computer is convenient to control the trolley. The host computer can also change the model, making the car adapt to driving in different environments. Next, this article introduces lane recognition. In this paper, a fully convolutional network is used to semantically segment the image to obtain the feasible region of the road. Then this article introduces the communication and control part of the system. The emphasis is on the serial communication and control implementation of the system. The system is controlled by computer and Arduino is used as the control board of the car. In addition, this article introduced the experimental process. Finally, the shortcomings of the design and implementation of a machine vision lane recognition system in this paper are summarized and the research prospect is prospected.