Reviewerly/exHarmony huggingface dataset:
Unsupervised Deep Transfer Learning for Intelligent Fault Diagnosis: An Open Source and Comparative Study.

Recent progress on intelligent fault diagnosis has greatly depended on the deep learning and plenty of labeled data. However, the machine often operates with various working conditions or the target task has different distributions with the collected data used for training (we called the domain shift problem). This leads to the deep transfer learning based (DTL-based) intelligent fault diagnosis which attempts to remit this domain shift problem. Besides, the newly collected testing data are usually unlabeled, which results in the subclass DTL-based methods called unsupervised deep transfer learning based (UDTL-based) intelligent fault diagnosis. Although it has achieved huge development in the field of fault diagnosis, a standard and open source code framework and a comparative study for UDTL-based intelligent fault diagnosis are not yet established. In this paper, commonly used UDTL-based algorithms in intelligent fault diagnosis are integrated into a unified testing framework and the framework is tested on five datasets. Extensive experiments are performed to provide a systematically comparative analysis and the benchmark accuracy for more comparable and meaningful further studies. To emphasize the importance and reproducibility of UDTL-based intelligent fault diagnosis, the testing framework with source codes will be released to the research community to facilitate future research. Finally, comparative analysis of results also reveals some open and essential issues in DTL for intelligent fault diagnosis which are rarely studied including transferability of features, influence of backbones, negative transfer, and physical priors. In summary, the released framework and comparative study can serve as an extended interface and the benchmark results to carry out new studies on UDTL-based intelligent fault diagnosis. The code framework is available at this https URL.
Saliency Detection Based on Non-convex Weighted Surrogates

Low rank and sparsity decomposition have shown potential for salient object detection. In existing methods, nuclear norm is used to approximate rank minimization and l1 norm is selected as sparse regularization. Two deficiencies, however, still exist for nuclear norm and l1 norm. First, both always over-penalize large singular values or large entries of vectors and result in a biased solution. Second, the existing algorithms very slow for large-scale applications. To address these problems, we propose a novel weighted matrix decomposition model with two regularizations: (1) Schatten-2/3 quasi-norm that captures the lower rank of background by matrix factorization technique, and (2) The l2/3 -norm that is capable of producing consistent salient object within the same image patches by effectively absorbing both image geometrical structure and feature similarity. In addition, we equip the weighting matrix with a high-level background prior map based on the color, location and boundary connectivity, which can indicate the probability that each image region belongs to the background. The proposed model can be solved by perform SVDs on two much smaller factor matrices. Experiments on three broadly used datasets by detailed comparisons show that our proposed approach has potential in salient object detection.
PENGEMBANGAN MEDIA PEMBELAJARAN MOBILE LEARNING BERBASIS ANDROID PADA MATERI INVERTEBRATA UNTUK SISWA KELAS X SMA

Teaching and learning activities in class require learning media that are able to convey material messages well. Learning media can be made by utilizing information technology, namely in the form of android-based learning media mobile learning. This research aims to (1) produce android-based mobile learing learning media in high school class X Invertebrate material that is good and worthy of being used as a learning media. (2) find out the response of users of mobile learning media, namely high school class X students to the learning media developed. This type of research is development research. Learning media developed using a development model proposed by Thiagarajan. The subjects of this study were 3 expert lecturers, 10 students in the limited trial and 20 students in the field trial. From the results of the study, product validity is in very good and valid criteria with a score of 83.64% in design aspects, 100% in material aspects, 93% in IT aspects, 83.33% in limited trials, 85.10% in field trials. This mobile learning media learning product is considered valid and feasible to be used to support biology learning activities.
COMPARATIVE ANALYSIS OF CONTROLLED HEALTHY AND MCI PATIENTS USING EEG STATISTICS

This paper describes the statistical analysis of EEG signals. EEG examination is carried out and compared between controlled healthy and Mild cognitive impairment (MCI) patients which may further develop dementia or Alzheimer disease. The statistical techniques provide the comparative analysis of EEG signal. The correct evaluation of EEG provides the extraction of valuable information which is important clinically. Also, extracting significant features from EEG is an important task for classification between various patients. The analysis of EEG data provides correct frequency rhythms. The relative Power spectral density values by Auto Regressive-Burg process cleared that; associated with the control group, the relative PSD is improved in the theta rhythmic range while expressively reduced in the alpha-2 rhythmic range.
A study on the adequacy of the level of vocabulary and meanings in the primary English textbooks revised in 2015

The purpose of the study is to examine the adequacy of the level of vocabulary and meanings used in the primary English textbooks. For this purpose, the vocabulary words and meanings in the English textbooks for 3 rd ~6 th grades were compared with the two criteria: one is the English Vocabulary Profile (EVP), the common standard for English, and the other is the Common European Framework of Reference for Languages (CEFR)-J Wordlist, which reflects the EFL context. The quantitative analysis compared the number of used vocabulary words and semantic levels by grade, and the qualitative analysis examined what vocabulary is beyond the elementary level, and what level of meaning is presented in the textbook. The results are as follows: first, the quantitative result showed that textbook vocabulary and meanings were mainly concentrated in the A1 and A2 levels throughout grades 3~6, while vocabulary and meanings from the B1 and B2 levels were generally used less, but increased in grades 5~6. Second, the qualitative result revealed a small number of vocabulary words and meanings used as not appropriate for the elementary level. Suggestions for selecting the vocabulary and meanings in the primary English textbook were made according to the level specified by the EVP and CEFR-J Wordlist.
Analysis of Efficiency Changes of IT-Service Companies Using DEA-Window

This study investigates and analyzes the efficiency of IT service providers over 7 years. It analyzes the efficiency of companies every year, predicts the direction of efficiency through trend analysis, and considers countermeasures accordingly. In addition, stability analysis is carried out by examining the fluctuation of the efficiency of the company for 7 years. It is possible to consider the measures against the sudden change of efficiency. The purpose of this study is to predict the efficiency and to cope with the change by considering the dynamic efficiency as well as the static efficiency of the enterprise. DEA-Window methodology is applied for this study.
Image Forgery Detection

Image forgery is a manipulation of digital image to hide or remove some meaningful information or object in the image. The detection of forged image is driven by need of authenticity and to maintain integrity also confidentiality of the image. “Image Forgery Detection” system is a system to detect the copy-move and copy-paste forged activity in an image. Copy-move image was the forged activity that happen by copying a region in an image and pasting it on another region in the same image, meanwhile the copy-paste image is creating a new image by replacing a region in two different image. By using existing algorithm of Simple Linear Iterative Clustering (SLIC) which to segment the host image into irregular blocks, Discrete Wavelength Transform (DWT) is to analyzed the frequencies of super pixel and Scale Invariant Feature Transform (SIFT) for the block-based feature extracted. The result finding from the module testing and test case was as expected result of the actual result.
Quantifying the effect of representations on task complexity

We examine the influence of input data representations on learning complexity. For learning, we posit that each model implicitly uses a candidate model distribution for unexplained variations in the data, its noise model. If the model distribution is not well aligned to the true distribution, then even relevant variations will be treated as noise. Crucially however, the alignment of model and true distribution can be changed, albeit implicitly, by changing data representations. Better representations can better align the model to the true distribution, making it easier to approximate the input-output relationship in the data without discarding useful data variations. To quantify this alignment effect of data representations on the difficulty of a learning task, we make use of an existing task complexity score and show its connection to the representation-dependent information coding length of the input. Empirically we extract the necessary statistics from a linear regression approximation and show that these are sufficient to predict relative learning performance outcomes of different data representations and neural network types obtained when utilizing an extensive neural network architecture search. We conclude that to ensure better learning outcomes, representations may need to be tailored to both task and model to align with the implicit distribution of model and task.
Website quality attributes for research data repositories in universities

espanolEl nuevo modelo de ciencia abierta requiere de una infraestructura adecuada para preservar y compartir los datos de investigacion. Ello ha implicado un desafio tanto para los investigadores como para las universidades y centros. Como respuesta se han creado mas de dos mil repositorios de datos en el mundo, un cuarto por parte de estas instituciones, con diferentes softwares especializados. El presente trabajo tiene como objetivo proponer atributos de calidad web para evaluar la interfaz de este tipo de sitios. Para ello se realizo una revision sistematizada de literatura con directrices internacionales, requisitos tecnicos y recomendaciones de expertos, detectando coincidencias. Como resultado se ofrece un protocolo de analisis especialmente formulado para repositorios de datos de investigacion, con parametros e indicadores sobre la interfaz de usuario, localizacion, acceso y reutilizacion, conservacion, difusion, evaluacion y compromiso institucional. A modo de conclusion se observa la necesidad de atender los aspectos especificos de este tipo de datos, relevando el papel de las bibliotecas universitarias para gestionarlos. EnglishThe new Open Science model requires an adequate infrastructure to preserve and share research data. This has involved a challenge for both researchers and universities and centers. In response, more than two thousand data repositories have been created in the world, a quarter by these institutions, with different specialized software. This paper aims to propose web quality attributes to evaluate the interface of this type of sites. For this, a systematic review of literature with international guidelines, technical requirements and expert recommendations was carried out, detecting coincidences. As a result, an analysis protocol specially formulated for repositories of research data is offered, with parameters and indicators on the user interface, location, access and reuse, conservation, dissemination, evaluation and institutional commitment. In conclusion, the need to address the specific aspects of this type of data is noted, highlighting the role of university libraries in managing them.
TÜRKİYE’DE İNTERNET ARACILI PAZARLAMA KAVRAMLARI KONUSUNDA YAZILAN LİSANSÜSTÜ TEZLERİN BİBLİYOMETRİK ANALİZ YÖNTEMİ İLE İNCELENMESİ

The purpose of this research is to raise the general profile of the graduate thesis work done at universities in Turkey on internet mediated marketing. The research questions are; how much internet marketing concepts are studied, which method is used as a research method, which techniques are used in data collection and which analysis techniques are used in data analysis. In addition, the purpose, method and results of the thesis will be examined. In addition, in the “conclusion and discussion” section of the theses, it will be discussed whether the results of the thesis are discussed with the literature and if there are any suggestions for further academic studies. The study includes 76 theses that are allowed to access on E-Marketing, Viral Marketing, Social Media Marketing, Database Marketing, Digital Marketing and Internet Marketing Ulusal at the National Thesis Center of Higher Education Council. The collected data were analyzed by bibliometric analysis method. As a result of this research, most of the thesis was written in social media marketing (25 theses). While 7 doctoral theses were prepared on internet mediated marketing concepts, 69 master's theses were prepared on the topic. Bahcesehir University (with 11 theses) takes the lead in the theses on Internet mediated marketing concepts. It has been determined that there are serious deficiencies in the summary and conclusions of most of the theses.
Library Guides: Readings Online User Guide: 3. Add your readings

Guide for academic staff using Readings Online. How to locate and add your course materials - whatever their format
Aplikasi E-Commerce Business to Consumer Kartu Undangan

This study aims to to build an E-Commerce Business to Consumer application for online invitation card sales utilizing internet technology and payment facilities through paypal. System development methods that are used are E-commerce with flow analysis, Data flow diagrams (DFD). Results of research is an information system that handles order transactions, payments that can be made through paypal facilities, delivery of goods and return facilities so that it can help customers to obtain information about the products offered by UD Printing Matahari, facilitate customers in the process of ordering products, and can help improve sales for the company.
Bat roosts in trees: a guide to identification and Assessment for Tree-Care and Ecology Professionals

"Bat roosts in trees: a guide to identification and Assessment for Tree-Care and Ecology Professionals." Arboricultural Journal, 41(4), pp. 244–245
An Empirical Study on the Digital Accomplishment of Postgraduates in Colleges and Universities Under the Background of “Educational Informationization”: Based on the University of Y survey

In today's world, with the rapid advance of science and technology, knowledge economy has emerged. Since the beginning of the party's 19, China's educational informationization has entered a new era of integration of innovation and intelligence—Education Informationization 2.0 era. “Educational informationization” has gradually become an important driving force for the development of China's economic and social innovation, how to effectively improve the level of digitalization, cultivate digital literacy, effectively promote the development of higher education today, has been paid more and more attention. Although people are no longer so unfamiliar with digital literacy, the research carried out in related fields has gradually deepened. However, the cultivation and formation of digital literacy is not overnight. Because digital literacy itself is not easy to be quantified evaluation, easy to form into paper text, can not be really implemented. At present, the research carried out by graduate students in colleges and universities is still insufficient, and it can not explain some problems. Based on the above situation, first of all, this paper discusses the concept and development of digital literacy, secondly, combined with the current situation of graduate students in Y University, design questionnaires, statistical data, summed up the problems existing in the digital literacy of graduate students, explore the causes of the problems, Finally, the existing problems, as well as the causes of the problems are analyzed, and the corresponding suggestions and countermeasures are given.
FROM IMAGE TO GRAPH-BASED DATA FOR PATH PLANNING

Path planning nowadays have been widely used even in our daily lives such as navigation of Google Maps or Waze. Path planning is one of methods that have been used in finding ways from one point to another. There’s varies approach to be used for path planning and one of the approaches that will be discuss in this report which is a study of graph-based data from an image of a maze-solving path project. This implementation of graph traversal, statistics and machine learning algorithms were a challenging part to be done. Input will be taken as an image and the process of converting the image to become a function by graph-based data methods have been taken as the important points to succeed this project by using the Image Processing Toolbox in MATLAB. This toolbox is used to filtering with the given pixels is encircling by the nearby pixels to be formed as the neighborhood and convert it into a graph with a set of matrices. This procedure also will then can be implemented to the robot for finding the free pathways in future project. Thus, the comparison of different methods of Dijkstra algorithm that have been used in past has been narrowed down to the subsystem that will be the guidance of this project to find the shortest pathway.
Unsupervised Learning: Using Unlabeled Data

Unsupervised Learning is a type of machine learning that acquires insight by inferring a function to describe hidden structures from unlabeled, uncategorized data. The classification or categorization is not included in the training observations. There is consequently no right or wrong evaluation of the learner and no evaluation of the accuracy of the learned insights that is output by the related algorithm used.
Recognition of 5-finger motion using EMG signals based on general object recognition

In this paper, we propose a system to estimate 5-finger motions based on recognition of a general object and operator’s EMG signals. DCNN recognizes the object to be grasped by the operator using a camera image, and then LSTM network estimates the 5 finger joint angles from the EMG signals. LSTM networks are prepared for each target object and they are switched to use according to the recognition result of DCNN network. In order to verify estimation accuracy of the proposed system, we conducted the experiments on five types of target objects. As a result, we revealed that the 5 finger joint angles were successfully estimated with high accuracy. The estimation accuracy improved compared with the case where the system did not use the result of object recognition.
A New Completeness Theory

In Chapter 5 , we identified several natural parameterized variants of our running example (the consistency problem for disjunctive answer set programming) whose complexity cannot be adequately characterized using the known parameterized complexity classes.
A Study on Data Analysis of Vector RDBMS Using Security Data

With the combination of ICT and manufacturing technology, Security Analystics has only recently been applied to industrial sites and public institution. Although Security data is increasing exponentially, it is difficult to grasp the hidden information in the process because of its huge amount. However, many analytical attempts have already been made using the Big Data Platform, and as a result, the analysis of production process data, which is the basis of Security and Safety, is progressing more and more efficiently. This paper also Sourced to study system model for quality defect analysis of Security Data Analysis. The proposed model is composed mainly of the data produced in the security data log for efficient analysis. The main equipment where log data is loaded is Web service segments such as Web servers and WAS, as well as firewalls, ips, DDos, and network equipment that control it in front of them. Artificial intelligence data analysis of log data is considered important, and schools and public institutions are also filtering out the vast amount of log data.In this paper, the correlation analysis between events was applied in order to obtain the information required through artificial intelligence techniques and large-scale data analysis. In addition, the Commission proposed a secure log data analysis system that builds a virtualization-based infrastructure for analysis of massive amounts of collected secure log data and uses Vector DBMS to collect and store data, which is much faster than traditional methods.
DETECTION AND LOCALIZATION OF SPLICING FORGERY IN DIGITAL VIDEOS USING CONVOLUTIONAL AUTO-ENCODER AND GOTURN ALGORITHM

In present days, individuals in the society are becoming increasingly relying on multimedia content, especially digital images and videos, to provide a reliable proof of the occurrence of events. However, the availability of powerful and user-friendly video editing tools makes it easy even for a novice to manipulate the content of a digital video which may be used as evidence during digital investigation. This has led to great concern regarding the trustworthiness of digital videos. A number of techniques have proposed in the literature for different types of digital video forgery detections. In this work, a hybrid technique for detecting and localizing splicing video forgery using convolutional auto-encoder and GOTURN (Generic Object Tracking Using Regression Network) is proposed. The parameters of the auto-encoder are learned during the training phase on original video frames. During the testing phase, the auto-encoder reconstructs the original frames with small reconstruction error and the forged frame with large reconstruction error. The forged material is then tracked in subsequent frames using GOTURN algorithm. The result of the experiments demonstrates that the proposed detection technique can adequately detect video splicing with an AUROC ( Area Under the Receiver Operating Characteristics ) value of 0.9307.
Knowledge Sharing in Online Environment among the Students of Farook College

Internet, nowadays, has become the pulse of knowledge sharing. Online environment provides sharing features, which promote the dissemination of ideas, opinions, reactions, interests, activities and other forms of user-generated content for other users to consume. This study is being carried out to understand the knowledge sharing in online environment among students of Farook College. A sample is selected by means of random sampling method to data collection. The size of sample is 234. It is evident that students of Farook College are aware of knowledge sharing through online environment. Majority of students use online environment to share knowledge for their academic purpose. Also, majority of the students prefer social media as online environment for knowledge sharing. Keywords: Knowledge, internet, social media, social networking sites, Wi-Fi Cite this Article Kadeeja Banu C.V .., Aswathi B. Knowledge Sharing in Online Environment among the Students of Farook College. Journal of Advancements in Library Sciences. 2019; 6(3): 9 19p.