Reviewerly/exHarmony huggingface dataset:
Unsupervised Learning for Object Representations by Watching and Moving

Author(s): Yang, Yanchao | Advisor(s): Soatto, Stefano | Abstract: The power of deep neural networks comes mainly from huge labeled datasets. Even though it shines on many computer vision tasks, supervised learning bears little hope to hack into the core of intelligent visual systems. On the other side, unsupervised learning is believed to be the future of AI; however, its performance is always inferior compared to the supervised counterpart. The goal of our research is to develop unsupervised learning algorithms for computer vision tasks while matching or even outperforming the supervised ones. Our key is a representation that is as informative as the supervisory labels, which can be constructed from an unlimited amount of unlabeled data. In theory, this representation contains richer information than the processed supervisory signal. Moreover, we develop algorithms that can utilize existing labeled datasets to expedite the information extraction from the unlimited unlabeled data. Our research is lined up in an order similar to the visual development in early infancy, such that we can also investigate the interplay between different visual functionalities. The final goal is to develop a robotic visual system akin to a human's, that can automatically acquire semantics from concepts of objects fostered by basic perceptions of motion and depth with the minimum amount of human supervision.
An Auditing Scheme for Cloud-Based Checkout Systems

The goal of this paper is to design and implement a security mechanism for cloud-based checkout systems based on chain-hashing scheme. Many cloud-based checkout systems are developed for merchants. However, storing transaction data in cloud storage is associated with serious security risks. The repudiation problem exists between merchants and service providers. We need a scheme that enables the service provider to prove its innocence and the merchant to prove its guilt. The proof of innocence is also called auditing. This paper designs a secure cloud-based checkout system. We use chain hashing to design auditing scheme for checkout systems.
Comparison of low-dimension speech segment embeddings: Application to speaker diarization

Segment clustering is a crucial step in unsupervised speaker diarization. Bottom-up approaches, such as, hierarchical agglomerative clustering technique are used traditionally for segment clustering. In this paper, we consider the top-down approach to clustering, in which a speaker sensitive, low-dimensional representation of segments (speaker space) is obtained first, followed by Gaussian mixture model (GMM) based clustering. We explore three methods of obtaining the low dimension segment representation: (i) multi-dimensional scaling (MDS) based on segment to segment stochastic distances; (ii) traditional principal component analysis (PCA), and (iii) factor analysis (i-vectors), of GMM mean super-vectors. We found that, MDS based embeddings result in better representation and hence result in better diarization performance compared to PCA and even i-vector embeddings.
Laser Interferometric Particle Imaging Measurement Image Processing Dependent on Skewed Chaotic Field

To perform fast segmentation of laser images effectively and facilitate later image processing, a laser interferometric particle imaging measurement laser image processing method based on skewed chaotic field is proposed on the basis of previous image segmentation algorithm. Particle size and position information are obtained by skewed chaotic field operator to implement particle field measurement and achieve the segmentation of image features. The edge images are extracted to improve the recognition accuracy of laser image. Finally, the experimental results show that clear laser images can be obtained by using the method proposed this paper, and the feasibility and practicability of the design are further verified.
The Application of Emotional Development Theory to Hotel Intern’s Career Choice Intention

The purpose of this study was to analyze the relationships among psychological separation, self-identity, internship satisfaction, and hotel career choice intention by applying emotional development theory. In order to test the conceptual model, this study conducted a survey with hotel interns in Seoul. A total of 400 valid surveys were analyzed through structural equation modeling. The results showed that (1) emotional independence of psychological separation affected self-identity; (2) psychological separation did not affect internship satisfaction; (3) psychological separation did not affect hotel career choice intention; (4) self-identity affected internship satisfaction; (5) self-identity affected hotel career choice intention; (6) internship satisfaction affected hotel career choice intention; (7) self-identity had a full mediation effect on the relationship between emotional independence and internship satisfaction; and (8) self-identity had a full mediation effect on the relationship between emotional independence and hotel career choice intention. Ultimately, this study contributes to the advancement of hotel internship research and suggests changes to training for hotel internships.
Analysing the Trade-Off Between Computational Performance and Representation Richness in Ontology-Based Systems

As the result of the intense research activity of the past decade, Semantic Web technology has achieved a notable popularity and maturity. This technology is leading the evolution of the Web via interoperability by providing structured metadata. Because of the adoption of rich data models on a large scale to support the representation of complex relationships among concepts and automatic reasoning, the computational performance of ontology-based systems can significantly vary. In the evaluation of such a performance, a number of critical factors should be considered. Within this paper, we provide an empirical framework that yields an extensive analysis of the computational performance of ontology-based systems. The analysis can be seen as a decision tool in managing the constraints of representational requirements versus reasoning performance. Our approach adopts synthetic ontologies characterised by an increasing level of complexity up to OWL 2 DL. The benefits and the limitations of this approach are discussed in the paper.
Recognizing Humans from Their Behavioral Patterns

Authentication of human in an unobtrusive manner is important in modern technology to enrich society. Authentication of a person in an environment like smart home, car driving, etc., can lead to better man-machine conjugation. Advancement in sensor technology and machine learning makes it possible to obtain and analyze a significant amount of data. This paper explores the important aspects of human behavior daily routine in the home. Traditional approaches rely on the extraction of statistical features for machine learning algorithms. However, with an increased number of sensors, feature extraction may not be possible. Therefore, human identification in a smart home is performed using deep learning technique on the data obtained from multiple sensors placed at the various place and devices in the homes like a bed, bathroom, door. In this paper, both statistical, as well as deep neural networks, are implemented for human activity data. For humans in smart home deep learning has upper hand as compared to other machine learning techniques. Thus proposed approach can identify humans based on analysis of sensor data using various machine learning technique using unobtrusive sensory data.
Parallax Occlusion Mapping Using Distance Fields

Parallax occlusion mapping (POM) is a technique to introduce 3D definition using a depth map instead of adding new geometry. The technique relies on ray tracing with higher samples resulting in a better approximation, especially at steeper angles. The distance between each sample is constant and it is possible to skip over fine detail at lower sample count. Our technique relies on a distance field (DF) instead of a depth map. This allows us to ray march through the field and lower the sample count considerably. We can get good results even with a single sample. Comparable results are obtained by less than half the samples of the industry standard POM approach.
Criminal identification using facial recognition

individualistic characters of the human face can be extracted by face recognition. The human face detection and recognition finds a major role in the application as video surveillance, face image database management. Face recognition is a simple and agile biometric technology. This technology uses the most obvious human identifier of the face. The face recognition finds its application in security, health care, criminal identification, places where human recognition is the necessity. With the advancement in technology, the extracting features of the human face become simpler. This paper discusses a different algorithm to recognize the human face. The purpose is to identify the criminal face and retrieve the information stored in the database for the identified criminal. The process is categorized into two major steps. First, the face is extracted from the image, distinguishing factors in the face are extracted and stored in the database. The second step is to compare the resultant image with the existing image and return the data related to that image from the database.
Illegal Photograph Detection under Modulated LED Illumination

Nowadays, almost everyone has a smartphone and can easily take pictures. Consequently, illegal acts such as photographing or video-recording copyrighted works and uploading them to the internet are reported as a growing problem in our society. This paper proposes a method for detecting such illegal photography. By illuminating copyrighted works with an LED light emitting orthogonal frequency division multiplexing multi-carrier signals and utilizing the feature of exposure time ratio in a rolling shutter camera, it is possible to distinguish between photographs taken by authorized and unauthorized cameras. The evaluation experiments confirmed that the proposed method could correctly identify photographs taken by authorized and unauthorized cameras.
Looking Inside a Document

In Chapter 1 , you learned how to describe and structure a document. You now know that you, as the designer and developer of an app and its documents, control what data is stored, where and how it is stored, and how to identify and reference it.
A Optical Quantum Router Based on GHZ States

Inspired by teleportation, we find that the GHZ state can be used to realize the quantum routing. This paper presents a scheme for optical implementation of a quantum router. The device directs the signal photonic qubit according to the control information. First we describe our proposal, showing the exact principle of operation on a optical scheme, the polarization state of the signal photon is undisturbed by control information under the routing operation, and the success probability can nearly reach up to 1/2. Subsequently, we discuss generalization of the scheme with multiple output ports, showing how to route signal qubit to any of the outputs.
SISTEM REKOMENDASI PRODUK DENGAN DATA MINING METODE FUZZY C-MEANS UNTUK MENDUKUNG STRATEGI PENJUALAN PRODUK PADA INDUSTRI KREATIF

PT. INFIA NIAGA DIGITAL is a company engaged in the field of media and advertising that is very well known among millennials, especially on Instagram social media besides selling a product, this company also gives us new information and viral on social media. Industry 4.0 is a relatively new term and may still not be widely known and understood by audiences in the industrial field. In the opinion of the Minister of Industry and Trade (Work Cabinet) Airlangga Hartarto quoted from Glienmourinsie (2016), Industry 4.0 made the production process run with the internet as the main support. Data Mining is a process that uses statistical techniques, mathematics, artificial intelligence, machine learning to extract and identify useful information and related knowledge from various large databases. Fuzzy clustering is the process of determining the degree of membership, and then using it by entering it into data elements into one or more cluster groups.
Development of Polytechnic Education in the Conditions of Integration of General-Engineering and Special Disciplines

Abstract In the conditions of innovative development of Polytechnic education and society in general in an educational paradigm there are basic changes. Today, the main units of updating of content of education are competence, the characteristic of their types and structure. Understanding students of existence of cross-disciplinary communications the importance of the studied disciplines in their interrelation and interaction is determined by cross-disciplinary competences. In modern conditions, the role of geometric-graphic preparation is greatly expanded. The advantage is given to those professionals whose thinking is able to synthesize imaginative and rational. The development of the ability to such a synthesis is greatly facilitated by mastering the methods of geometric-graphic modeling of objects and processes. Let us emphasize that models based on geometric and graphical methods (with the ability to visualize the model) are often more effective in practice than purely analytical models. Therefore, the development of the theory of geometric modeling (with computer visualization) should not be considered in the narrow sense of geometric-graphic preparation, but as a self-valuable component of geometric-graphic education. The author substantiates the essence of cross-disciplinary integration, presents the mechanisms of integration of disciplines at the Polytechnic University, pedagogical conditions, methods of teaching the theory of geometric-graphic modeling, as well as the results of practical implementation of theoretical provisions.
Correctness and Consistency of Event-Based Systems

Event-based systems encounter challenges of correctness and consistency. Correctness means that the execution results match the intention of the designer. Consistency means that different data elements that co-exist within a certain system creates an internal consistency with respect to the system's requirements. In this tutorial, we cover the different aspects of correctness and consistency. We discuss issues of correctness with respect of the temporal properties of the system, such as order of events, and boundaries of time windows. We further discuss the different aspects of fine-tuning required in event-based system, where different semantic interpretations are possible, such as: repeating events, or consumption. The consistency discussion relates to two classic issues in the data management world: data dependencies and integrity constraint enforcement. Since event-based systems typically consist of loosely coupled component architecture in distributed environment, the challenge is compliance with data dependencies and assertions about consistency. Finally, yet importantly, we discuss the validation of event-based systems by using static and dynamic analysis.
Implementing Documents on iOS: UIDocument and UIDocumentBrowser ViewController

Documents are critical components of many apps and have been so from the beginning of the personal computer era. Many people still think of documents as paper-based objects, but the documents that people work with today on iOS and macOS are much more sophisticated than their paper predecessors. This chapter introduces today’s documents and their structures. It then explains how to use UIDocumentBrowserViewController to manage documents.
Research on Chinese-Language Disambiguation Based On Computer

When using computer to deal with natural language documents,various ambiguities are problmes that must be faced and solved, to some excent, ambiguity resolution becomes one of the core tasks in natural-language processing. Aim at the particularity of the Chinese language disambiguation, the paper discusses the focus of the ambiguity: ambiguity definition, ambiguity classification, ambiguity cause and ambiguity resolution. Meanwhile, in this paper, the advantages and disadvantages of various research methods are compared, and the difficulties and common problems in the research are pointed out.
Integration of spoken dialogue system and ubiquitous computing

With the progress of ubiquitous computing, computers/machines can understand various human contexts via various sensors. A wearable device is possible to estimate calories burned, fatigue degree, even QoL (Quality of Life) by analyzing the heart rate, steps, sleep quality, etc. Simultaneously, the significant progress of deep learning brought the drastic performance improvement in not only image recognition, but also speech processing and natural language. Nowadays, it will become a reality that the humanoid robot instantaneously recognizes what is shown in the camera image and speaks the human-like sentences with human-like voice in multiple languages. Therefore, a collaboration between human and machines have already started. In a call center, AI chatbot has already worked to handle the typical Inquiries on behalf of human operators. A smartwatch and activity trackers keep monitoring owner's physical states and sometimes make an intervention for improving the owner's health. We are also developing the digital signage that persuades the passing person to change his/her behavior to a better way. However, there is still a distance between actual human-to-human interaction and machine-to-human interaction. That means that there is some context information that the machine side is not yet aware of. For example, while human beings observe a slight change of facial expression and body gestures, they change their way of talking and tone, but the machine can not take such information (emotion, agreement, etc.) into consideration when it generates a dialogue. In my keynote, I would like to widely introduce the leading-edge research on context recognition in the research area of ubiquitous computing. Then, I explain the requirements on how next - generation dialogue system should be. In the next-generation dialogue system, it is natural to change the content of conversation and the state of utterance according to the recognized context, for example, the conversation content will change according to the number of steps and stress situation during dialogue. Finally, we discuss technical issues required for integrating spoken dialogue system with ubiquitous computing.
A Study on the Optimization of the Examination Model in the Second Foreign Language Teaching

With the development of education, economy and culture in China, the opportunities of international communication are increasing day by day.As an important neighbor of our country, Japan has a close contact with our country in various fields, so the use of Japanese is wide, and the number of Japanese learners in our country is increasing.Japanese is an important second language choice for English majors in the courses of foreign language education in colleges and universities.Therefore, the setting of overall teaching rules, especially the setting of examination models, should be based on the students' specific learning needs.Based on this, this paper studies and discusses the optimization of the examination model of the second foreign language teaching.
Parlameter – a Corpus of Contemporary Slovene Parliamentary Proceedings

The paper presents the Parlameter corpus of contemporary Slovene parliamentary proceedings, which covers the VIIth mandate of the Slovene Parliament (2014-2018). The Parlameter corpus offers rich speaker metadata (gender, age, education, party affiliation) and is linguistically annotated (lemmatization, tagging), which boost research in several digital humanities and social sciences disciplines. We demonstrate the potential of the corpus analysis techniques for investigating political debates. The corpus architecture allows for regular extensions of the corpus with additional Slovene data, as well as data from other parliaments, starting with Croatian.&#x0D;
Vehicle Insurance Calculator Using Augmented Reality

The important factor to calculate insurance is to inspect the damage of a vehicle for that the client has to migrate to the insurance company and have to wait for the arrival of the inspecting person. To make this ease for the client, he does not need to wait until the insurer calculates the amount of insurance to recover the damage happened. The core technique of this process is augmented reality. Once the dent images are uploaded then it produces the predicted cost. This predicted cost is produced as per the percentage of dent calculated using augmented reality image processing. Then as per the insurance claimed by the client, it is mapped with the amount calculated using augmented reality. This paper presents an innovative approach to detect vehicle’s body damage and cost estimation for the vehicle insurance with using 2D images
A Qualitative Study on Cooperative Learning Experiences of Undergraduate Students Participating in a Fieldwork Class

본 연구는 수도권 소재 사립 I대학교 사범대학 사회교육과 전공 선택과목이자 현장답사 과목인‘지역 문화의 탐구’에 참여한 대학생들의 협동학습 경험을 탐색한 것이다. 특히, 현장답사는 모둠별로 수행되기 때문에 강의실에서만 이루어지는 협동학습의 양상과는 다를 것이라는 전제를 갖는다. 현장에서의 체험을 통해 학습이 이루어진다는 점에서 일반적인 협동학습 보다 학습자들 간의 긴밀한 소통과 책임의식이 요구된다. 이런 점에 착안하여 연구문제를 첫째,‘필드웍 수업에 참여한 대학생들의 협동학습 경험은 어떤 의미인가?’, 둘째, 성공적인‘필드웍 협동학습의 요인은 무엇인가?’로 설정하였다. 연구문제를 해결하기 위해 수업에 참여한 대학생들을 대상으로 FGI 방법을 활용하여 자료를 수집하였다. 연구결과 첫째, 대학생들의 필드웍 협동학습 경험을 표상하는 의미는‘함께 성장하기’로 나타났다. 이에 따른 소주제 는‘지식확장의 계기’,‘공동의 학습 목표 달성’으로 도출되었다. 둘째, 필드웍 협동학습 성공의 핵심요 인은 4가지로 도출되었으며, 집단 내적인 요인으로‘학습자 간의 상호작용’,‘긍정적인 의사소통’과 집단 외적 요인으로는‘교수자-학습자 간의 상호관계’,‘체계적인 수업 설계’이다. 본 연구의 시사점은 필드웍 학습이 지니는 현장성으로 인해 강의실에서 수행하는 일반적인 협동학습에 비해 학습자들은 상호 간의 친밀감을 높이는 전략을 사용하고 있다. 또한, 협동학습이 단순히 서로 의존하고 협력하여 학습효과를 증진시키는 방법을 넘어 학습자들로 하여금‘함께 성장하기’ 대열에 참가하여 동반 성장을 경험할 수있는 계기를 제공함을 확인하였다.This study explores the cooperative learning experiences of undergraduate students who participated in the class ‘Exploring the Local Culture’ which was a field trip course in the department of Social Studies Education at ‘I’University. This study presupposes that it will be different from the existing cooperative learning aspect because it conducts the field work rather than cooperative learning which is performed only in the classroom. The course ‘Exploring the Local Culture’ is an experiential cooperative learning course aimed at exploring activities, so it requires more close communication and responsibility between the members of the cooperative group than most university classes. Based on this context, we set up two research questions: First, “What are cooperative learning experiences of undergraduate students participating in fieldwork class?” Second, “What do undergraduate students consider as successful factors of fieldwork cooperative learning?” In order to solve these research questions, we collected data by conducting FGI interviews with undergraduate students who participated in the class. The results of the study are as follows: First, the significance of undergraduate students’ experience of cooperative learning in fieldwork showed that they ‘grow together’. The sub-categories were derived from ‘opportunity of knowledge expansion’ and ‘achievement of common learning goals’. Second, the core factors of the success of fieldwork cooperative learning were derived from four factors: ‘interactions among learners’, ‘positive communication’ as internal factors and ‘interaction between teacher and learners’, ‘systemic instruction design’ as external factors. The implication of this study is that the fieldwork learners have a strategy to increase the intimacy of learners’ mutuality compared to general cooperative learning, that is, cooperative learning in the classroom. In addition, we confirmed that cooperative learning provides an opportunity for learners to participate in the ‘growing together’ and experience coexistent growth beyond learning methods that simply rely on each other and cooperate to enhance learning effects.