Reviewerly/exHarmony huggingface dataset:
Frobenius Norm based 2DPCA

PCA is a classical feature extraction method. But PCA usually loses the structure information of the image. As the tensor version of PCA, 2DPCA could save the structure information and could be fast calculated. However, both PCA and 2DPCA utilize the square of Frobenius norm to describe the total scatter, which enlarges the influence of the outliers. In this paper, we utilize Frobenius norm instead of the square of Frobenius norm to describe the total scatter in the 2DPCA and develop Frobenius Norm based 2DPCA (F2DPCA) for feature extraction and face recognition. We give an efficient solution for F2DPCA. The experiment results show that F2DPCA is efficient and effective.
Analisa dan Implementasi Sistem Informasi Pengeluaran Kas Kecil Pada PT. Bank Bukopin Berbasis Web

The application of a petty cash disbursement information system in a company is very important because by applying the petty cash disbursement information system, the company can supervise and control the course of the company's operational activities so that it can run as it should. This study aims to find out how the petty cash fund accounting system applied at PT. Bank Bukopin West Bekasi, is it in accordance with SOP (operational standards) in the company, and to find out the weaknesses of the system that is already running. From the results of this study obtained a discussion that in the petty cash expenditure PT. Bank Bukopin West Bekasi is still done manually starting from recording data to storing other data relating to the petty cash disbursement process to reporting. The research method used by the author is to use field research, interview methods and library methods while the software development method used by the writer is the waterfall method with the SDLC model. So according to the research of PT. Bank Bukopin West Bekasi requires a system that is expected to produce better reports in support of petty cash activities. The programming language used in development is to use a MySQL database and an editor using Notepad ++. This research will discuss about a web-based petty cash expenditure information system that is how the submission process, reimbursement, capital and reports. The author's purpose of this research is a small cash expenditure information system with the hope that it can overcome the obstacles that have occurred in the small cash expenditure system manually, and can assist in the process of making reports.
Evaluating the Quality of Social Web Applications Using the LSP Method

Quality is an essential determinant of the success of every type of software and social Web applications are not an exception. It is therefore of great importance that the examination of the degree to which social Web applications meet predefined requirements related to particular facets of quality is performed effectively and frequently. With an objective to facilitate evaluation procedure and enable comparison of social Web applications at all levels of the quality model, we initiated a research into development of a methodology that will aggregate quality requirements into a single score. The work presented in this paper draws on the employment of the logic scoring of preference (LSP) method and outlines only some parts of the aforementioned methodology. After identifying quality attributes that constitute the requirement tree, elementary criteria for both objective and subjective performance variables were introduced. As a follow up, field experts were included in the study in order to determine weights of performance variables within particular performance subsystem. Finally, the appropriate logic aggregation operators were selected based on the relevance of performance variables
Using Combined List Hierarchy and Headings of HTML Documents for Learning Domain-Specific Ontology

HTML pages contain unstructured and diverse information.However, these documents lack semantics and are not machine understandable.Semantic webs aim to add formal semantics to web data, whereas ontology provides formal semantics to a domain and is thus considered a foundation of semantic webs.Domain ontologies can be constructed manually, but this process is tedious and inefficient.Thus, this study presents an ontology learning (OL) model to create domain ontologies automatically from a set of HTML pages.The key insight of this research is that it combines the list structure and headings of HTML pages to recognize the ontology vocabulary.The approach also incorporates synonym relationships with ontology and allows the semantic interpretation of ontology concepts.We implement the proposed OL approach to build sports ontology from a collection of sports domain HTML documents.The new sports ontology is tested using FaCT++ reasoner; results show no inconsistency in the ontology.Furthermore, experts evaluate the successful mapping of HTML lists and headings to the ontology vocabulary.The proposed OL approach performs effectively and achieves 92.7% and 95.4% precision values for list and heading mapping, respectively.
Live Forensics Method for Acquisition on the Solid State Drive (SSD) NVMe TRIM Function

SSD currently has a new storage media technology namely Solid State Drive Non-volatile Memory Express (SSD NVMe). In addition, SSD has a feature called TRIM. The TRIM feature allows the operating system to tell SSDs which blocks are not used. TRIM removes blocks that have been marked for removal by the operating system. However, the TRIM function has a negative effect for the digital forensics specifically related to data recovery. This study aimed to compare the TRIM disable and enable functions to determine the ability of forensics tools and recovery tools to restore digital evidence on the NVMe SSD TRIM function. The operating system used in this study was Windows 10 professional with NTFS file system. Typically, acquisition is conducted by using traditional or static techniques. Therefore, there was a need of a technique to acquire SSD by using the live forensics method without shutting down the running operating system. The live forensics method was applied to acquire SSD NVMe directly to the TRIM disable and enable functions. The tools used for live acquisition and recovery were FTK Imager Portable. The inspection and analysis phases used Sleutkit Autopsy and Belkasoft Evidence Center. This research found that in the recovery process of TRIM disabled and enabled, TRIM disabled could find evidence while maintaining the integrity of evidence. It was indicated by the same hash value of the original file and the recovery file. Conversely, when TRIM is enabled, the files were damaged and could not be recovered. The files were also not identical to the original so the integrity of evidence was not guaranteed.
Peningkatan Efisiensi Kerja Guru Melalui Pembuatan Aplikasi Rapor Berbasis Komputer

The domain of the activity is technology for the society whereas the focus is practical computer science for the society. The background of our activity is based on the needs of YPK junior high school in Malang city, Indonesia. The school need to develop computer-based school report card and also daily grade card for teachers. The method for software/application development is spiral model which consist of the cycle of system identification, risk analysis, and enhancement of the prototype to be an operational prototype. Evaluation of the product was based on the Computer System Usability Questionnaire (CSUQ) from IBM. The CSUQ using 5 scale of Likert scale contains three categories: 1) system usefulness (SYSUSE), 2) information quality (INFOQUAL), and 3) interface quality (INTERQUAL). The mean rank’s result in order from the greatest to the lowest is SYSUSE, INTERQUAL, and INFOQUAL, respectively. It was reported that SYSUSE category was superior to INFOQUAL (U = 3369.5, p = 0.0005). Overall, the user satisfaction score is 78.4%, which is in the “worthy” category
Study on an efficient hyper-chaos-based image encryption scheme using global bit permutation

BACKGROUND: The chaotic system with low dimensions has a low security compared to the high-dimensional chaotic system.Furthermore, major pixel-level permutations merely transform the pixel position and cannot change the intensity distribution of the original image.Bit-level permutation could change the intensity distribution, as it devotes more time to conduct bit-level computation.OBJECTIVE: In this study, we present a more efficient image encryption approach based on hyper-chaos and a global bit cycle shift (HC-GBCS).METHODS: According to the input image we adopted the SHA-256 secure hash algorithm to obtain the initial key, which served as the premier parameter of the chaotic system.Then we employed a 4D hyper-chaotic system for generating the chaotic series, on which we utilized global bit permutation to enhance the security of the encryption system.Finally, the diffusion process was conducted by using the generated chaotic series extended with a logistic map.RESULTS: Experimental results and analysis reveal that the presented approach encrypts plain images effectively and achieves high security and stability.CONCLUSION: The proposed method can deal with the problems inherently existing in encryption methods utilizing lowdimensional chaotic map.Furthermore, global bit permutation can transform the pixel distribution of plain images and enhance the cryptosystem security.
MEDIA AUDIO VISUAL SEBAGAI MEDIA PENINGKATAN KETERAMPILAN MENULIS TEKS DESKRIPSI DI SMP NEGERI 3 KOTA BOGOR

THE APPLYING AUDIO-VISUAL MEDIA TO THE IMPROVEMENT OF WRITING SKILL OF DESCRIPTIVE TEXT IN JUNIOR HIGH SCHOOL (SMP NEGERI 3 KOTA BOGOR)The research aims to find out the improvement of VII grade students of SMP Negeri 3 Kota Bogor in writing descriptive essays using audio visual media. The method used in this study is the Classroom Action Research (CAR) method. Data collection was carried out by the method of observation, field notes, tests, interviews, and student questionnaires. This research was conducted in two cycles. One cycle consists of four stages, namely: action planning, action implementation, observation, and reflection. The results showed an increase in the average value of students' understanding of writing descriptions through audio-visual media. During the first cycle, the average student score was 70.86 or are at the level of completeness 73.12%. While during the second cycle, the average student score was 79.89 or 90.74% completeness level. An increase also occurred in the motivation and activeness of students in learning and in completing assignments.
Correction to: An intelligent personalized web blog searching technique using fuzzy-based feedback recurrent neural network

While typesetting the article, the surname of the second author has been incorrectly published.
Near Duplicate Image Retrieval using Multilevel Local and Global Convolutional Neural Network Features

In this work, we present an approach based on multilevel local as well as global Convolutional Neural Network (CNN) feature matching to retrieve near duplicate images.CNN features are suitable for visual matching.The CNN features of entire image may not give accuracy in retrieval due to various image editing/capturing operations.Our retrieval task focuses on matching image pairs based on local and global levels.In local matching, an image is segmented into fixed size blocks followed by extracting patches by considering neighboring regions at different levels.Matching local image patches at different levels provides robustness to our retrieval model.In local patch extraction, we select blocks containing SURF feature points instead of selecting all blocks.CNN features are extracted and stored for each image patch and then followed by extraction of global CNN features.Finally, similarity between image pairs is computed by considering all extracted CNN features.Our similarity function is based on correlation and number of blocks found in matching.We implemented our proposed approach on benchmarking Holiday dataset.Retrieval results show remarkable improvement in mean average precision (mAP) on the dataset.
EDUKASI BUDAYA TOPENG MALANGAN MELALUI MEDIA INTERAKTIF BOARD GAME

Traditional arts have become part of an area or even become the identity of it. This happenned in Malang, where Malang has a distinctive art called the Topeng Malangan. Topeng Malangan is a performance art that combines dance and puppet shows. The identity of the Topeng Malangan which is already very attached to Malang is inversely proportional to its popularity amongs Malang people. Therefore, an interesting and understandable educational media is needed to introduce Topeng Malangan into Malang people. Iterative design method is used in the design of this educational media. This iterative method can be used for finding a suitable game that can be played by families, because exploration, trials, and evaluations are involved in this design process.
Japanese Sign Language Classification Using Gathered Images and Convolutional Neural Networks

A method to classify Japanese sign language (JSL) words using a gathered image generation method and a convolutional neural network (CNN) is proposed. The JSL words consist of words that are often used in information queries. Gathered images are generated based on the difference between the first image, which indicates the start position of a JSL word and target images, which indicate the motion position for a JSL word. The CNN is used to extract features from the gathered images. The JSL words are classified using a support vector machine. To show the effectiveness of the proposed method, we conducted experiments and computer simulations. We confirmed that the mean recognition accuracy for 10, 20, and 42 JSL words was 99.2%, 94.3, and 86.2%, respectively.
PROFESSIONAL FUNCTION OF PEDAGOGICAL STIMULATION FOR STUDENTS TO ASSIGN SOCIALLY MEANINGFUL EDUCATION

The paper aims to study the professional pedagogical function to stimulate students to assign socially meaningful education. The relevance of the professional function is justified. The attitude of the academic staff to accept that it is the professional function of teachers to stimulate students to acquire socially meaningful education is studied. Labor skills are identified and described as parts of the professional function. They are: to orient students in the content of education; to promote the importance of both social and personal education content; to create conditions for students to become aware of themselves as subjects of educational activity; to reveal information about the characteristics, abilities, personal resources; to develop value orientations, emotionalsensual sphere of students; to select and use incentives correctly; to show emotions correctly when using stimulation methods; to encourage students for initiative educational activities to develop socially meaningful education.
Kecenderungan dan Perubahan Hujan Ekstrem Harian di Pulau Madura

Madura subject to a high level of flood hazard. One of the main causes of flood is extreme rainfall. Global warming generates changes in the amount of extreme rainfall. This research is conducted to identify and to analyze the trends, changes, and randomness of 24-hour extreme rainfall data on Madura Island. The method used is a non-parametric method which includes the Median Crossing test, the Mann-Kendall test, and the Rank-Sum test at the significance level of α =0.05. The analysis was carried out on 31 rain gauge stations. The recording period observed is between 1991-2015. The results of the analysis show that based on the Median Crossing test, most rainfall stations have data originating from random processes. The result shows also that the maximum 24-hour extreme rainfall trend is significantly decreased in a few locations, while for the majority of other stations have no experience a significant trend.
Evaluation of the Korean Middle School English Textbook: Listening Skill

This study is done to find out how listening skill is presented in Middle School English 1 textbook published in 2018. In order to answer the research question, the writer used the criteria proposed by Cunningsworth (1995). This is a qualitative research in which the writer evaluated and analyzed by herself. The findings of this study show that listening skill in Middle School English 1 met the criteria proposed by Cunningsworth (1995). Keywords: textbook, textbook evaluation, curriculum
A Deep Multiscale Fusion Method via Low-Rank Sparse Decomposition for Object Saliency Detection Based on Urban Data in Optical Remote Sensing Images

The urban data provides a wealth of information that can support the life and work for people. In this work, we research the object saliency detection in optical remote sensing images, which is conducive to the interpretation of urban scenes. Saliency detection selects the regions with important information in the remote sensing images, which severely imitates the human visual system. It plays a powerful role in other image processing. It has successfully made great achievements in change detection, object tracking, temperature reversal, and other tasks. The traditional method has some disadvantages such as poor robustness and high computational complexity. Therefore, this paper proposes a deep multiscale fusion method via low-rank sparse decomposition for object saliency detection in optical remote sensing images. First, we execute multiscale segmentation for remote sensing images. Then, we calculate the saliency value, and the proposal region is generated. The superpixel blocks of the remaining proposal regions of the segmentation map are input into the convolutional neural network. By extracting the depth feature, the saliency value is calculated and the proposal regions are updated. The feature transformation matrix is obtained based on the gradient descent method, and the high-level semantic prior knowledge is obtained by using the convolutional neural network. The process is iterated continuously to obtain the saliency map at each scale. The low-rank sparse decomposition of the transformed matrix is carried out by robust principal component analysis. Finally, the weight cellular automata method is utilized to fuse the multiscale saliency graphs and the saliency map calculated according to the sparse noise obtained by decomposition. Meanwhile, the object priors knowledge can filter most of the background information, reduce unnecessary depth feature extraction, and meaningfully improve the saliency detection rate. The experiment results show that the proposed method can effectively improve the detection effect compared to other deep learning methods.
Supervised Filter Learning for Coronary Artery Vesselness Enhancement Diffusion in Coronary CT Angiography Images

A C TIn medical imaging, vesselness diffusion is usually performed to enhance the vessel structures of interest and reduce background noises, before vessel segmentation and analysis.Numerous learning-based techniques have recently become very popular for coronary artery filtering due to their impressive results.In this work, a supervised machine learning method for coronary artery vesselness diffusion with high accuracy and minimal user interaction is designed.The fully discriminative filter learning method jointly learning a classifier the weak learners rely on and the features of the classifier is developed.Experimental results demonstrate that this scheme achieves good isotropic filtering performances on both synthetic and real patient Coronary Computed Tomography Angiography (CCTA) datasets.Furthermore, region growing-based segmentation approach is performed over filtered images obtained by using different schemes.The proposed diffusion scheme is able to achieve higher average performance measures (87.8% ± 1.5% for Dice, 86.5% ± 1.3% for Precision and 88.5% ± 2.6% for Sensitivity).In conclusion, the developed diffusion method is capable of filtering coronary artery structures and suppressing nonvessel tissues, and can be further used in clinical practice as a real-time CCTA images preprocessing tool.
Research on Ecological Development of Foreign Language Journals—Based on Foreign language Teaching and Research

A foreign language journal is an ecosystem because each foreign language journal has different columns. This paper takes Foreign Language Teaching and Research as an example to analyze the ecological development of foreign language journals and give some suggestions on the future development of foreign language journals.
Exploring Local Wisdom in Buginese Ethnics: Language Politeness Phenomena of Tau Soppeng

The objectives of this research are to explore and to reveals the form and the characteristics of linguistic politeness, politeness strategies, and the realization of local wisdom found among Soppeng people (to Soppeng) one particular Buginese ethnics. This research applied ethnolinguistics viewed from pragmatics, semiotics, and politeness theories. To capture the data, this study used purposive sampling and snowball among native in Soppeng regency which agrees to be a part of this study. The method used is the method of listening with free engaged, recording, documentation, elicitation technique, and interview. The results of this research show the characteristics and the forms of linguistic politeness through some morphemes marked (such as prefixes ta), suffix pronouns (ta, ki, ni), some honorific vocabularies (such as pung, andi, daeng), some lexemes (iye, tabe, taddampengenga), some maxims of politeness principles; generosity, approbation, modesty, and sympathy, and four strategies of linguistic politeness i.e., bald on record, positive, negative, off-record strategy. In addition, this study also found the realization and the implication of local wisdom as a primary value such as ethics and language politeness, self-image, courage, solidarity, and cooperation.
Application of Agenda-setting, Framing and Propaganda during News Production Process

The present research is a meta-analysis of agenda-setting, framing and propaganda literature to highlight the application of these three approaches of media effects during news production process.An extensive literature review of these three theories was conducted.It is proposed through this article that the news content that is received by the consumers goes through a complicated process application of different theoretical approaches which help to shape up the final product of a news item and the final news product somehow becomes different then the first hand information.A process model of agendasetting, framing and propaganda is proposed during news production process.That helps to understand the links present in the above mentioned theoretical approaches
A New Framework of Moving Object Tracking based on Object Detection-Tracking with Removal of Moving Features

Object Tracking (OT) on a Moving Camera socalled Moving Object Tracking (MOT) is extremely vital in Computer Vision.While other conventional tracking methods based on fixed camera can only track the objects in its range, a moving camera can tackle this issue by following the objects.Moreover, single tracker is used widely to track object but it is not effective due to the moving camera because the challenges such as sudden movements, blurring, pose variation.The paper proposes a method inherited by tracking by detection approach.It integrates a single tracker with object detection method.The proposed tracking system can track object efficiency and effectively because object detection method can be used to find the tracked object again if the single tracker loses track.Three main contributions are presented in the paper as follow.First, the proposed Unified Visual based-MOT system can do the tasks such as Localization, 3D Environment Reconstruction and Tracking based on Stereo Camera and Inertial Measurement Unit (IMU).Second, it takes into account camera motion and the moving objects to improve the precision rate in localization and tracking.Third, proposed tracking system based on integration of single tracker as Deep Particle Filter and Object Detection as Yolov3.The overall system is tested on the dataset KITTI 2012, and it has achieved a good accuracy rate in real time.