Reviewerly/exHarmony huggingface dataset:
Seems like "going Indieweb" has given my ...

Seems like going Indieweb has given my online presence a huge boost by checking out the search results looking up myself;
A Conceptual Framework of Adaptive Mobile POI Recommendations

Many mobile applications that recommend attractive and customized POIs are often not adaptive enough for users who are actively traveling. Although almost all mobile applications and one concept of the mobile recommendation system have been able to adapt to users, in fact, the findings prove that this is only a small effort that mostly focuses on capturing user behavior during tourism activities. Instead, the Adaptive Mobile Recommendation System (AMRS) is proposed by carrying out all possible configurations that can improve adaptability in mobile applications. Furthermore, the AMRS was built as a new concept based on the Adaptive Tourist Recommendation System (ATRS) concept that was proposed in the past. AMRS takes advantage of the travel cycle and the concept of experiential learning as an unlimited effort of adaptivity that can be applied in a real way using the structure of the recommendation system.
Visual Object Detection System for Autonomous Vehicles in Smart Factories

Autonomous transport vehicles are very important for smart factories. Computer vision studies for autonomous vehicles in industrial environments are considerably less than that of outdoor applications. Recognition of safety signs has an important place in safe movement of vehicles and safety of humans in factories. In this study, we built a test environment for smart factories and collected a visual data set including some important safety signs for the safe and comfortable movement of the vehicles in smart factories. Then, we developed a visual object detection system using YOLOv3 deep learning model and tested it by using autonomous robots. In our tests, an accuracy of 76.14% mAP (mean average precision) score was obtained in the dataset we collected.
The Design of Two-Way Relationship Tourism Planning System with User Centered Design (UCD)

Tourist intending to go on vacation are always searching for information related to the place they will visit by website or travel application. The more and later information obtained, the better the preparation made by tourists on their tour enabling them to have a good travel experience then. A good tour preparation, however, needs to be supported by the latest information as occurred in tourist sites such as traffic conditions, weather conditions and the crowd of tourist attractions. The latest information about tourism objects needs to be facilitated with the information notification about what occurs in the tourist sites to be visited. In this paper, we present the results of research on how the prototype of a tourism planning system with a two-way relation that can make it easier for tourists to provide and obtain information from any various sources in regard to the attractions they will visit. The High Fidelity Prototype of tourism planning system with a two-way relation was made using the Adobe XD with the User Centered Design method and was evaluated using System Usability Scale. The results of System Usability Scale showed that the prototype is acceptable and meet the usability, easy to learn and useful.
Method for Adaptively Detecting Low Contrast Image of V-prism Refractometer

It is a critical issue of glass refractive index measurement that enhancing low contrast slit image. In order to solve this problem, the paper proposes a solution that is feasible and adaptive to enhancing low contrast image in engineering. The CLAHE algorithm is used to globally preprocess the slit image acquired by CCD in the meantime and adaptive smoothing filtering is used for filtering. The improved stretching window is used to suppress the brightness of the single line in the slit, and enhance the brightness of the slit image to improve the extraction accuracy of the single line. The experimental results show that the accuracy of glass refractive index measurement can be improved to ±5×10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-6</sup> in the case of low contrast image, which provides a new method of low brightness and low contrast for improving the measurement accuracy of V -prism refractometer and has a significant in its high precision measurement.
Fuzzy Modelling using Firefly Algorithm for Phishing Detection

A fuzzy system is a rule-based system that uses human experts' knowledge to make a particular decision, while fuzzy modeling refers to the identification process of the fuzzy parameters.To generate the fuzzy parameters automatically, an optimization method is needed.One of the suitable methods provides the Firefly Algorithm (FA).FA is a natureinspired algorithm that uses fireflies' behavior to interpret data.This study explains in detail how fuzzy modeling works by using FA for detecting phishing.Phishing is an unsettled security problem that occurs in the world of internet connected computers.In order to experiment with the proposed method for the security threats, a database of phishing websites and SMS from different sources were used.As a result, the average accuracy for the phishing websites dataset achieved 98.86%, while the average value for the SMS dataset is 97.49%.In conclusion, both datasets show the best result in terms of the accuracy value for fuzzy modeling by using FA.
THE EFFECT OF VIDEO ON READING COMPREHENSION AND READING INTEREST

The Objectives of this study were to get empirical evidence about the difference in reading achievement between students who were taught English by using Video and those who were not. The design of the study was a factorial design of 2 X 2. The samples of the study were taken from the eighth-grade students of SMPN 11 Kota Tangerang Selatan. The design used to take the samples of the study was Nonequivalent control group design.  There were two classes that became sample classes, they were 8.1 class and 8.2 class, each class has forty-one students so there were eighty-two students as a sample, 8.1 class was as a controlled class while 8.2 class was as an experimental class. The experimental class was given a video while the controlled class was not. There were two kinds of instruments used for the research. The first instrument was a test and the second one was a questionnaire. The test was aimed at measuring students’ reading comprehension while the questionnaire was aimed at measuring students’ reading interest. The results of the test were in the form of a gained score which was analyzed by using Anova with the significance level is 5%.  It was found that the mean score for experimental class was 23 and for controlled class was 22, meanwhile, the modus score of the experimental class was 22 and for control, class was 20 and then the statistical computation on the gained score revealed that the significance value of Video, Reading Interest and both interactions toward reading comprehension had significance value lower than 0.05 (>0.05) while the t-table value 5%. Keywords: Video, Reading Comprehension, Reading Interest
Addressing Stemming Algorithm for Arabic Text Using Spark Over Hadoop

Hadoop and Apache Spark are two popular big data frameworks that make two things different by working on two different logics. Hadoop distributes large amounts of data across multiple nodes which makes it not expensive in terms of hardware. Spark makes work with distributed data but does not rely on a distributed storage system. In this perspective we try to optimize existing stemming algorithm representing an essential step for language processing and analysis. We will focus on comparing between the results obtained using Hadoop and Spark, then implement a merger between the two frameworks. Towards the end of this paper a clear perception will be designed to benefit from advantage of the characteristics and performance of each of the two frameworks.
Review Proses Forensik Optical Drive Menggunakan Metode National Institute of Justice (NIJ)

Abstrak. Saat ini media penyimpanan telah banyak berubah, tidak hanya dalam bentuk yang lebih minimalis tetapi juga dalam jumlah kapasitas itu sendiri. Forensik digital saat ini merupakan bidang yang berkembang berdasarkan data pada penyimpanan media, dilakukan untuk berbagai keperluan seperti data yang diperoleh, kontaminasi data, kloning data, dan lainnya. Drive optik seperti CD dan DVD, termasuk media penyimpanan, digunakan untuk menyimpan data dalam bentuk file audio dan video. Dalam penelitian yang dilakukan pada drive optik khusus, CD-R / DVD dapat diperoleh melalui proses pencitraan untuk mendapatkan ruang yang tidak terisi yang berisi data yang sebelumnya diformat atau dihapus. Penelitian ini membahas proses pemulihan file yang telah diformat menggunakan alat Forensik Autopsi dalam proses pemeriksaan dan analisis. Pengambilan bukti digital pada objek penelitian dilakukan dengan metode forensik statis, sedangkan evaluasi dan analisis adaptor menggunakan metode forensik dari National Institute of Justice (NIJ) untuk mendapatkan bukti digital dari objek penelitian. Kata kunci: Bukti Digital, Forensik, National Institute of Justice, Optikal Drive Abstract. At present the storage media has changed a lot, not only in a more minimalist form but also in the amount of capacity itself. Digital forensics is currently a growing field based on data on media storage, carried out for various purposes such as data obtained, data contamination, data cloning, and others. Optical drives such as CDs and DVDs, including storage media, are used to store data in the form of audio and video files. In the research carried out on special optical drives, CDR / DVDs can be acquired through the imaging process to obtain unallocated space that contains data previously formatted or deleted. This research discusses the file recovery process that has been formatted using the Forensic tool Autopsy in the examination and analysis process. Retrieval of digital evidence on the object of research is done by static forensic methods, while the evaluation and analysis of adapters use the forensic method of the National Institute of Justice (NIJ) to obtain digital evidence from the object of research. Keywords: Digital Evidence, Forensic, National Institute of Justice, Optical Drive
The Use of Image Media on the Storytelling Ability of Class III Students In Anggadita III Elementary School

This study aims to determine the relationship between media images with the ability to tell stories of students on Indonesian subjects in Anggadita III Elementary School. This research is a type of qualitative research. Where the number of third grade students in Anggadita III Elementary School is 31 people and in this study the sample used was 3 students where 2 of them were students who were considered the most capable in telling stories while 1 other student who had storytelling skills was felt to be lacking . The collection technique in the study itself is to use through observation, interviews, and also documentation while the results of research and tests conducted using gamelan media have a considerable influence where of the 31 students only 5 people scored below 75. From the results of this study it can be concluded that image media can have an influence on students' storytelling abilities.
Review Paper on Novel Approach Improvising Techniques for Image Detection Using Deep Learning

Convolutional Neural Network (CNN) architecture is a class of deep learning or deep neural networks, used for analyzing visual information. Traditional CNN architecture has large datasets useful for image classification and recognition. But the datasets in CNN are limited and take time for scene recognition tasks. The time taken for recognizing images plays a crucial role in deep learning. As the datasets are large in number, the object should be compared with millions of images from the dataset, and the time for object recognition goes on increasing. Scene-centric data collection, semantic segmentation, feature selection, and use of residual learning framework to improve the object detection and recognition with respect to time and improve the dataset collection.
Design of a Unified Communications Service Using OpenStack Infrastructure

This paper focuses on a benchmarking of Cloud Computing Infrastructures and the implementation of a Unified Communications (UC) service at the Technical University of the North, through a study of protocols, audio and video codecs, servers for Communications, softphones for videoconferencing and messaging software, taking into account compatibility on mobile devices and PCs. A comparative analysis of several Unified Communications platforms such as Elastix, Cisco, and Avaya was performed, in the same way, it was done with Cloud Computing platforms with OpenStack, OpenNebula, and Eucalyptus. The current situation of the University’s data network was studied in order to determine if the characteristics and resources it has can support the services to be implemented, and how many resources each service demands, and an extension and user plan was created for UC services. In the end, it is shown that a server hosted in the cloud provides the availability and smooth operation of its services.
DEVELOPING AN ENGLISH LISTENING WORKBOOK FOR MULTIMEDIA DEPARTMENT OF VOCATIONAL HIGH SCHOOL

This study is aimed to develop listening supplementary materials in the form of a workbook for tenth grade students of multimedia department of vocational high school. This study used the research and development model adapted from Borg and Gall. The product developed that was validated by the expert validators included the workbook, answer key, tapescript and CD of the audio recording.
GERAKAN LITERASI MASYARAKAT KABUPATEN SUMEDANG COMMUNITY LITERACY MOVEMENT OF SUMEDANG REGENCY

This study discusses the process of formation and pattern of literacy movement activities at Forum Literasi Sumedang (FLS) as a catalyst of literacy based on society movement in human development effort. The purpose of this study is to know how the process of forum formation based on literacy, as well as the pattern of literacy movement activities implemented by the FLS as a catalyst of society movement based on literacy. This research uses qualitative method with case study approach. Technique of collecting data is done by observation, interview, literature study or documentation, and triangulation. The results of this study indicate that the formation of FLS begins with the motive to combine literacy activists to build a network (connection), so  the opportunity for the development of literacy movement in Sumedang Regency grew larger. The FLS creation process consists of problem identification, FLS concept formulation, preparation, and launching. The literacy movement activity model at Forum Literasi Sumedang has two patterns, first the FLS as the center or the center of movement, and the second is the FLS as the support system of the initiator community.
Development of system for people counting by image sequence processing

People counting provides valuable information on evaluating an event, marketing, and security. Therefore, it has been proposed that the systems count passing people by using a top-view camera installed at a high position in general. Here, we take into account that it can be easily installed anywhere, we propose a portable system for counting passing people by using a side view camera with a fisheye lens. In order to count passing people, we used a background subtraction method to detect moving region, and calculated its vertex. Furthermore, the direction of passing people was estimated by using optical flow. In the verification experiment, it was confirmed that the developed system could correctly recognize a walking direction and count the number of people.
Experiencing the moment : Enhancing surroundig awareness when walking

Todays technology provides the ability for people to interact with devices at all time, but it also makes them gaze down and loose touch with their surrounding while doing so. This project explored ...
An Effective Priority-Based Resource Allocation Approach in Cloud Computing

A cloud environment provides resources to the requesters “on demand” and whenever required. This attracts many users nowadays to use various services provided by the Cloud providers. The resources can be scaled up and scaled down as per the user’s needs. So, it’s very important to make effective resources utilization for different service providers. As providers provide on-demand service for its resources, it’s very important to make allocation of resources very efficiently so that the maximum users need are satisfied with good quality of services. To achieve this high efficiency, we proposed an approach which not only consider the user’s service-related requirement but also consider the provider’s sides parameter like resources, free or loaded machines, time duration of allotment. By considering all these facts from both sides, we can say that this novel priority-based allocation approach make efficient allocation of resources to the requester based on their dynamic needs.
Virtual experience, real impact : the influence of virtual reality on memory and behaviour

Virtual reality (VR) is increasingly applied in healthcare; e.g., as a form of medical education, or to facilitate treatment or rehabilitation. However, there are still many untouched opportunities. The aim of this thesis is to better our understanding of how healthcare can benefit from VR by exploring two novel VR paradigms. Part 1 of the thesis provides a fruitful basis for the use of VR to simulate exposure to psychological trauma and subsequent trauma symptoms. This ‘analogue model of psychological trauma’ provides a novel method to study the basic mechanisms underlying trauma symptom development, and to create and test interventions. Part 2 provides a framework for the use of ‘memory-related perceptual illusions’ to affect physical activity. This paradigm is based on how we memorize spatial representations of our environment and may be useful in the field of rehabilitation. Taken together, the work presented in this thesis stresses the relevance of establishing which manipulations VR allows for, testing their user effects, and exploring whether these manipulations can be of use in the field of healthcare. Such knowledge provides useful guidelines for the development of future VR applications.
Advanced Concepts: First-Order Nonlinear Circuits

In this chapter, some of the concepts introduced in Chap. 9 are extended to nonlinear first-order circuits, also making reference to potential functions for resistive circuits. In particular, some circuits with piecewise-linear nonlinearities (either original or obtained by approximation) are studied, showing the advantages of this kind of formulation, which makes it possible to find the solution analytically, whereas in the general case we usually have to resort to numerical solutions.
PDF Data Curation Primer

This work was created as part of the Data Curation Network “Specialized Data Curation” Workshop #2 held at Johns Hopkins University April 17-18, 2019.
Effective Training of RBF Networks

RBF networks seem to be an interesting and efficient alternative for traditional sigmoid-based neural networks. More sophisticated activation function makes a network more powerful but requires developing of new training methods. The paper presents a new more efficient training algorithm based on the second-order constructive ErrCor (Error Correction) algorithm. The effectiveness of the proposed approach has been confirmed by several experiments with both approximation and classification problems.
Evaluation of Different Algorithms on the RDDL Simulation Platform

Probabilistic and Parallel Planning (PPP) is a hot spot in AI planning in recent years. Relational Dynamic Influence Diagram Language (RDDL) is a new language used in PPP. For PPP problems, Real-Time Dynamic Programming (RTDP) and Upper Confidence Bounds (UCB1) Applied to Trees (UCT) algorithm are few approaches to find near-optimal solutions. However, there is no evaluation of the performance of these algorithms under the same platform. Different planners based on RTDP or UCT have different performance. It is hard to answer which algorithm is better. Fortunately, RDDLSim is a platform which implements a parser, simulator, and client/server evaluation architecture for RDDL. Empirically testing these algorithms on the same platform is necessary. In this paper, we evaluate the performance of RTDP and UCT in RDDLSim. Experimental results show that the performances of these two algorithms are domain specific. In several domains, RTDP is significantly more efficient than its opponent. While in other domains, UCT performs better.
Medical Bag based Cell Membrane Perforation System and Application to Animal Cells

Our photochemical cell membrane perforation method is new approach for mass cell processing, eg. cell therapy or regenerative medicine. It is speedy on dish instant process but to reduce the cost for cell therapy, it is better to handle the cells without special treatment on plastic dishes and avoid long time cell culture. So we are trying to establish a new cell processing system, designed for cell suspension and the suspension is handled within a medical bag like package, so the cell membrane perforation process becomes easy handling and can reduce a risk of contamination.
Data Reduction Using NMF for Outlier Detection Method in Wireless Sensor Networks

Nowadays, in wireless sensor networks (WSNs) field, the advances in electronics, wireless communications, and data processing have become an important reality. Wireless sensor networks are employed to eliminate problems occurred in health care, monitoring, agriculture, etc. Data reduction is considered as the best method that reduces dimensionality of the database. So, it helps outlier detection technique to classify data during training. In our work, we have constructed a newest data reduction process using non-negative matrix factorization (NMF). This method finds out the nature of data it is regular or outlier. Also, it can give a highest performance. Compared to various methods like Fisher Discriminant Analysis (FDA) and Principal Component Analysis (PCA), our method based NMF are considered as the most efficient and accurate for detecting outlier in WSNs. As real datasets, we use LUCE, Intel Berkeley and Grand St-Bernard. So based on the obtained results, our method is considered as a perfect one used in wireless sensor networks.
Correlation Motivation and Learning Outcomes on Application Simas Eric

The purpose of this study was to determine the correlation between motivation and learning outcomes of students in the application of Simas Eric. The method used is a correlational study. There were 30 respondents in class XI MIA MAN 1 Pekanbaru who participated in this study. The research data obtained directly from the sample using questionnaires and cognitive ability test instrument. Data analysis was performed using SPSS 16.0. The findings indicate that students have the motivation and learning outcomes are high on the application of Simas Eric. This indicates a positive and significant correlation between motivation and learning outcomes of students in the application of Simas Eric.