Reviewerly/exHarmony huggingface dataset:
Optimization of Cost: Storage over Cloud Versus on Premises Storage

In today's world of digitalization the most important object is data. There are numerous techniques available for retrieval of the data. To store this data over a large period of time various data hardware (DHW) are used. As the data is increasing day by day the more cost is incurred in storing the data. Data proliferation is the term used to refer the large amount of data that is created by government and nongovernment institutions either in structured or unstructured format. To minimize the maintenance cost generated by data proliferation IaaS as cloud computing service can be implemented. IaaS can be considered as virtualized service, which can be used to provide `as a service' to the users via cloud vendors. It provides the access of database resources on demand. One can `pay-as-per-use' of resource from the pool of resources and these resources can be virtualized in cloud based environment. To access the virtualized resources there are various approaches used. Private cloud approach is commonly used to maintain the integrity of the data.
Spectral Image Segmentation with Global Appearance Modeling

We introduce a new spectral method for image segmentation that incorporates long range relationships for global appearance modeling. The approach combines two different graphs, one is a sparse graph that captures spatial relationships between nearby pixels and another is a dense graph that captures pairwise similarity between all pairs of pixels. We extend the spectral method for Normalized Cuts to this setting by combining the transition matrices of Markov chains associated with each graph. We also derive an efficient method for sparsifying the dense graph of appearance relationships. This leads to a practical algorithm for segmenting high-resolution images. The resulting method can segment challenging images without any filtering or pre-processing.
Feature Extraction Methods in Person Re-identification System: A Technical Review

Intelligent surveillance is an emerging research area in the field of computer vision. Person re-identification is one among the tools involved in intelligent surveillance. Person re-identification is used to recognize and identify a person of interest captured by different surveillance cameras at different times and at different locations, when an input image is given. Automation of person re-identification is difficult in real time due to changes in pose, background, illumination and occlusion. Recent researchers have focused on developing discriminant, robust features, learning distance metric models or fusion of both for matching between the images of person. Our main objective is to provide the future researchers the importance of various state-of-the-art feature extraction techniques and deep learning approaches used in person re-identification, till date. Different algorithms with their strengths and accuracy percentage were summarized in a comparison table. Finally, unsolved problems in person re-id were listed that can be used as guidelines for future research.
Yale University Library Research Guides: Library Resources for Entering Research Workshops : Remote Access to Online Resources (VPN)

This guide highlights library resources for the students in the Entering Research Workshops summer program
OPPORTUNITIES FOR THE DEVELOPMENT OF CREATIVE ABILITIES OF THE FUTURE TEACHER AND STUDENT

This article discusses issues such as increasing the competitiveness of graduates on the basis of a competent approach to education, designing a creative educational process through the development of creative competence of teachers, creating its modern methodological support, and developing students' creative abilities. The content of the development of creative abilities of a future teacher of vocational education reveals the essence of such basic concepts as creativity, creative abilities, pedagogical creativity, and interactive pedagogical environment in the field of research.
MACHINE LEARNING FOR MECHANICAL ANALYSIS

It is not reliable to depend on a persons inference on dense data of high dimensionality on a daily basis. A person will grow tired or become distracted and make mistakes over time. Therefore it is ...
Learning Approaches of Grade 11 Students in Physics at Antipolo City Senior High School

Research on student learning at school can be very useful for improving teaching and learning. Not all learning is the same. Sometimes, for a number of reasons, students avoid the hard work of deep learning and instead fall back a surface learning practice. Blaming students due to their poor performance does not encourage them to engage in their lessons because it only prevented us from applying teaching strategies which may have a positive effect on their learning. Being able to identify these practices allows astute and conscientious educators to diagnose problem in the organization of courses or curricula. This study aimed to determine the learning approaches of students in Physics. Eighty senior high school students were used as the respondents. There were sets of questionnaires given to them to determine the different learning approaches of students in Physics. Based on the gathered data, 70%   of the populations have shown deep learning though, 30% of them showed surface learning. However, based on the tabulated data, the following skills were seen as weaknesses of students that need mastery. Their approaches to learning on these aspects are surface approach. [1] Interpretation of plotted graphs [2] Derivation of formulas [3] Sketching vector diagrams [4] Solving a variety of Physics problems. Based on the findings of the study, the researcher has come up with the following recommendation: [1] there must be more time on plotting of graphs (position versus time and velocity versus time) and as much as possible, there will be more practice exercises on plotting of graphs with interpretations. [2] The teacher needs to show the derivations of general formulas in front of the class. He/she needs to give more sample problems where students could be challenged to derive equations for unknown quantities. This could be done during class discussions. [3] The teacher needs more patience and dedication to guide her students on how to draw vector diagrams. [4] The teacher needs to help students review their Algebra and Trigonometry as tools to understand Physics. Selected topics in algebra and Trigonometry should be reviewed during first week of school days. [5]The teacher needs to discuss students’ weaknesses in Mathematics collaboratively with the Mathematics Teachers as feedback to prepare students in Physics course.
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HIPAA audit logs are a vital part of any conversation surrounding HIPAA compliance since they are required to ensure full and proper monitoring of the ...
Best Android Spy Apps To Spy On Android Phones

More apps are constantly being released as smartphone technology continues to expand at a rapid pace. On this page, I will tell you what are the best ...
Building Your IT Environment Vulnerability Health Checklist | Outer Edge

Theres an old saying that reminds us that a chain is only as strong as its weakest link. Whoever first came up with that phrase was talking about your ...
Betalt samarbete med… -En kvalitativ studie av hur influerare kommunicerar i marknadsförande inlägg på Instagram

Influencer marketing is one of the fastest growing trends within marketing in Sweden. By using a semiotic analysis, this study aims to analyze how influencers communicate through sponsored posts on ...
미술관 통역사의 직업 정체성에 관한 내러티브 탐구

This paper examines the process of how an art museum interpreter became familiarized with her duties and formed professional identity. For this study, Hyun-jung, an in-house interpreter for the director of a national art museum in Korea was selected as the research participant. Employing the method of narrative inquiry, her first 1.5 years at the art museum was carefully followed and observed. The data collected and analyzed includes in-depth interviews, log entries, participant’s work-related materials and self-portrait. A total of five core themes were identified as a result of the narrative analysis: Duties and Responsibilities; Context of the Art Museum; Mediation; Inner Conflicts and Identity Crisis; and Formation of Professional Identity. The research participant’s experience can be summarized as follows: Firstly, as an interpreter with no field experience, Hyun-jung was required to acquaint herself with the unfamiliar and abstruse subject called art. She was also exposed to whispering interpreting, a type of interpretation that she knew little of, resulting in a hard landing in her first job. Second, Hyun-jung found she needed to improve her flexibility and adaptability against the unpredictability in her work and meetings. This is because depending on the characteristics and the needs of the speakers, requirements for interpretation services changed, as well as the language direction, and the type of interpretation (whispering, consecutive, and sight interpretation) and her role as mediator and communication facilitator. Third, an art museum interpreter had to double as a secretary and an administrative assistant, which meant the traditional duties of an interpreter was comparatively reduced in Hyun-jung’s role. This resulted in much inner conflict and a thirst for professionality, and Hyun-jung found herself greatly discouraged and confused in terms of her professional identity. Fourth, through trial and error, Hyun-jung came to form her own strategies for interpretation, and eventually came to develop a sense of professional identity that fulfilled the expectations by the art museum: a mediator of cultures and catalyst for engaged communication.
Research on the Concerted Cultivation of Mathematics Teachers in Rural Primary and Middle Schools Based on the Trinity-----A Case Study of Cultivating the Guidance of Mastering Core Literacy of Normal Students Majoring in Mathematics

As basic education reform goes deep, a group of high-quality teachers with dedication is urgently needed for the reform and development of rural primary and secondary education. Therefore, it is urgent to train the normal students of mathematics major in normal colleges and universities into a high-quality and specialized mathematics teacher in rural primary and secondary schools with high integrity, solid professional foundation, outstanding ability of education and teaching and self-development. Firstly, this paper first introduces the significance of concerted cultivation of mathematics teachers in rural primary and secondary schools in colleges and universities based on trinity . On this basis, it further studies how to train the normal students of mathematics major in colleges and universities to master core literacy-oriented teaching skills, educational skills and research ability.
Training and Development A Way Forward For Sustainable Development: A Case Of Banking Sectors In Riyadh, Saudia Arab

This study highlighted the essence of training and development (T & D) and its impact on sustainable development (productivity and performance). The components of training and development like: (behavioral modification, education, on and off the job trainings) were the important predictors of sustainable development. Sustainable development is important tool for physical health, mental health and emotional stability. The data was collected from 10 commercial banks in Riyadh, Saudi Arab by distributing 100 questionnaires with simple random technique. The findings showed that there is positive impact of T & D on sustainable development. In last, further research and implications are given.
Protest Speech and Ironic Phrases in the October 25 Demonstrations: An Analytical Study of Protest Rhetoric and Ironic Phrases Posted on Social Networks of the October 25 Demonstrations

The protest speech is one of the methods of media discourse and raises a number of issues by expressing political views and opinions in a sarcastic manner. The study aimed to identify the most prominent topics that were addressed by the protest speech and ridicule in the demonstrations of October 25, and to study the methods adopted by the demonstrators in their letters by presenting their opinions and views, and to identify the forms and templates used by the protesters in their satirical treatment of the protest speech. The study reached the protest speech in the posted phrases, combining contradictions in terms of length, shortness, rhetoric, slang, and praise and defamation. The study also found that some of the speeches took on the character of depth as we want a homeland and some of the speeches tighten the demonstrators' resolve to continue until they achieve legitimate rights.
Searching for Multiple Equivalent Predictors from Oral Squamous Cell Carcinoma Dataset Using Statistically Equivalent Signature Algorithm

Selecting highly predictive features from the high dimensional dataset is a formidable task. The existing feature selection algorithms available today are not dealing with multiple equally predictive subsets of features. We strongly believe that there is other subsets of features as well, which can give equivalent predictive accuracy as that of state-of-the-art algorithms. Statistically equivalent signature (SES) is one such feature selection algorithm, which is centred on constraint-based learning of Bayesian networks. The proposed model selects equivalent subsets of features from oral squamous cell carcinoma (OSCC) dataset with the help of SES. To inspect the validity of SES algorithms output, we are using K-nearest neighbour (KNN), support vector machine (SVM) and neural networks (NN) on each subset of predictive features. Finally, the results of proposed technique is compared with support vector machine - recursive feature elimination (SVM-RFE). SES produces more stable accuracy as compared to SVM-RFE.
Physics Playground Design and Outline

For our third example project, we'll be tackling some new topics pertaining to the physics of the Unity engine. We'll implement a mouse-aimed camera with 3D movement for our player, including jumping, gravity, and wall jumping. We'll play with some objects using proper Rigidbody-controlled physics, giving our player a means of pushing and pulling them from a distance. We'll also tinker with joints to attach Rigidbodies to each other and “force fields” to play with adding forces to Rigidbodies and/or our player on the fly.
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FIU Libraries: Study Group Guidelines: Project Study Groups

Guidelines for forming and operating study groups for many purposes. Groups formed for a specific purpose, project, or out-of-class assignment.
Best Call Blocker Apps For iPhone

In this blog post, I will tell you what are the best call blocker apps for iPhone. There is a default call blocker app thats present on every iPhone. ...
Adversarial Mutual Information for Text Generation

Recent advances in maximizing mutual information (MI) between the source and target have demonstrated its effectiveness in text generation. However, previous works paid little attention to modeling the backward network of MI (i.e., dependency from the target to the source), which is crucial to the tightness of the variational information maximization lower bound. In this paper, we propose Adversarial Mutual Information (AMI): a text generation framework which is formed as a novel saddle point (min-max) optimization aiming to identify joint interactions between the source and target. Within this framework, the forward and backward networks are able to iteratively promote or demote each other's generated instances by comparing the real and synthetic data distributions. We also develop a latent noise sampling strategy that leverages random variations at the high-level semantic space to enhance the long term dependency in the generation process. Extensive experiments based on different text generation tasks demonstrate that the proposed AMI framework can significantly outperform several strong baselines, and we also show that AMI has potential to lead to a tighter lower bound of maximum mutual information for the variational information maximization problem.
Basics of Forming a Network of School Objects Network in Rural Administrative Area

The purpose of the article is to identify the basics of forming a network of school facilities of rural administrative district, to analyze the existing and most advanced means of forming a network of alternative teaching methods. Based on the existing network of school facilities, it is proposed to supplement the traditional network with an alternative system of education based on their interaction. In the course of the study, the current state of the education system, traditional and alternative teaching methods, and their influence on the formation of the functional space of DDZ and ZNZ were investigated. The current state of the network of preschool and school services of NovoSanjar district of Poltava region is analyzed. The study considered the factors and principles of forming a school education network. Methods of optimization of the network of preschool and school services of the district are formed and defined. The feasibility of using mobile-transforming structures in the formation of educational buildings and school buildings using mobile-transforming tools was analyzed during the study.
LibGuides: Digital Resources: Finding Ejournal articles and more

Digital Resources available to students and faculty at Louisville Presbyterian Theological Seminary
Acquisition and processing of facial motion capture data

Face capture technology is applied in the fields of film and television production, auxiliary teaching, visual communication and human-computer interaction. This paper introduces the Vicon Cara face capture system, the collection method of face motion capture data and the method of sound and image data processing. It mainly includes the introduction of the system hardware and software, the preliminary preparation of facial motion capture data collection, and the optimization and processing of the collected data. Finally, high quality data were collected at the early stage of the study to improve the efficiency of subsequent data processing and ensure the quality of data processing.
Analysis on Extraction of Common Foreground Object by Co-Segmentation

Co-segmentation is a subclass of segmentation used to segment out the common objects by assigning multiple labels to segment the targeted common things. Methods existing so far do not exhibit competitive results for any specific task. The key issue of the proposal selection-based co-segmentation problems lies in mining consistent information shared by the common targets. Due to uncertainty of the shared features, it usually requires manually selecting features or feature learning performed beforehand. The main goal is the comparison of an existing and proposed co-segmentation method. Proposed method (second method) focuses on reduction of running time. For each image, a multi-search strategy extracts target individually. Experiments are orchestrated on public dataset MSRC and iCoseg. Performance evaluation of both the methods is compared.
Can augmented reality supplement traditional human-machine interfaces?

In this master thesis, the possibilities and limitations of using handheld aug- mented reality (AR) as a complement to a regular human machine interface (HMI) are explored. This was done by developing a mobile application for An- droid and connecting it to a real machine, making it possible to perform actions on the machine through the AR application. A user study with 20 test subjects was conducted where the AR prototype was compared to a regular HMI. The majority of the test subjects preferred the AR interface over the regular HMI. System usability tests showed that it was easier to perform the actions through the AR application. The average time to perform each action was lower with the AR application. The main advantage of using AR turned out to be the possibility to display the data in a context, i.e. at the right machine component. A drawback with (handheld) AR is that the development tools might not be suitable for large scale applications at this stage. (Less)
Privately detecting changes in unknown distributions

The change-point detection problem seeks to identify distributional changes in streams of data. Increasingly, tools for change-point detection are applied in settings where data may be highly sensitive and formal privacy guarantees are required, such as identifying disease outbreaks based on hospital records, or IoT devices detecting activity within a home. Differential privacy has emerged as a powerful technique for enabling data analysis while preventing information leakage about individuals. Much of the prior work on change-point detection---including the only private algorithms for this problem---requires complete knowledge of the pre-change and post-change distributions. However, this assumption is not realistic for many practical applications of interest. This work develops differentially private algorithms for solving the change-point problem when the data distributions are unknown. Additionally, the data may be sampled from distributions that change smoothly over time, rather than fixed pre-change and post-change distributions. We apply our algorithms to detect changes in the linear trends of such data streams. Finally, we also provide experimental results to empirically validate the performance of our algorithms.
Grouping District / Cities in Papua Based Poverty Indicators

Abstract Welfare of the people is a very important thing in a country. One measure of the welfare of society is seen from indicators of poverty. The government conducts a long-term agreement in terms of encouraging change through SDG’s. One of the government’s target is less poverty in all its forms by 2030. The area in Indonesia which has the highest percentage of poor people in the provinces of Papua. Hence, the groups based Indicators of Poverty in Papua province using C-Means Clustering and Fuzzy C-Means Clustering. The indicators used in this analysis is an indicator of Health, Education Indicators and Household Characteristics indicator. Based on the analysis results obtained Fuzzy C-Means formed 5 group is the best method to classify District / Cities in Papua Province by minimumicdrate value. Areas that need to be the focus of the government to reduce poverty in Papua is the Puncak District.
Estimation of the Number of Vehicles by Regression Based on Parts Detection

This paper proposes a method to count vehicles from an in-vehicle camera image by regression based on car parts detection. In the case of an in-vehicle camera image, since vehicles are frequently occluded by other vehicles in traffic congestion, it is difficult to accurately count vehicles. Therefore, we propose a method to count vehicles by regression based on the number of visible car parts. For this, we make an estimator by learning the relation between the number of visible car parts and that of vehicles by Support Vector Regression. We evaluated our method using in-vehicle camera images recorded in an actual environment, where the proposed method performed better than counting detected vehicles.