Reviewerly/exHarmony huggingface dataset:
A Proximal Algorithm for Estimating the Regularized Wavelet-Based Density-Difference

Density-Difference (DD) estimation is an important unsupervised learning procedure that proceeds many regression methods. The present work details a novel method for estimating the Difference of Densities (DoD) between two distributions. This new method directly calculates the DD, in the form of a wavelet expansion, without the need for explicitly reconstructing individual distributions. Furthermore, the method applies a regularization technique that utilizes both l2 and l1 norm penalties to robustly estimate the coefficients of the wavelet expansion. Optimizing the regularized objective is accomplished via a Proximal Gradient Descent (PGD) approach. Thus, we term our method Regularized Wavelet-based Density-Difference (RWDD) with PGD. On extensive simulated datasets, from complex multimodal to skewed distributions, our method demonstrated superior performance in comparison to other contemporary techniques.
Coreference Resolution with Hierarchical Pointer Networks Based on Pointing Methods

Coreference resolution is a type of discourse analysis task of natural language processing. The task entails a method of linking different words expressed in an arbitrary entity within a document. Pointer networks (Ptr-net) based on RNN encoder-decoder is capable of modeling the problem of a target class variable and learning and predicting a position corresponding to a given input sequence. A hierarchical RNN encoder-decoder is an extended model of the RNN encoder-decoder that performs encoding on a word-by-word basis for a given input sequence. It performs encoding on a sentence basis to predict the output result. Ptr-net suffers from performance degradation when the input is composed of multiple sentences, or when the length of the input sentence is long. To solve this problem, we propose a coreference resolution with a hierarchical pointer networks (HRPT) model based on pointing methods for all cases mentioned. The HRPT encodes word and sentence levels for the input sequence, consisting of multiple sentences. It uses both word and sentence-level information in the decoder. The pointing method for coreference resolution is a way of pointing to the position of the referenced word or the referenced pivot of the entity. Experimental results show that the proposed model is CoNLL F1 71.56%, which is 20.96% better than the rule-based model.
Automatic arm gesture recognition using information gleaned from maximum instantaneous Doppler frequencies

Radar has been recently employed for automatic hand gesture recognition for touchless interactive intelligent devices. Compared to hand gesture, arm gesture recognition can be more suitable for contact-less man-machine interaction with longer range separation. The larger radar cross-section of the arms, vis-a-vis hands, permits more remote interactive positions in an indoor setting. Further, the ability of using hand gestures for device control can sometimes be limited by cognitive impairments such the Parkinson disease. In this case, arm motions can be more robust to strong hand tremor and shaking. In this paper, we discriminate between dynamic arm motions using a Doppler radar sensor. The method considered is motivated by the clear contiguity of the arm signal back-scattering in the time-frequency domain. We use information gleaned from the arm micro-Doppler (MD) signature as the sole features and proceed to classify arm motions using the Nearest Neighbor (NN) classifier. In particular, we analyze the role of the maximum instantaneous Doppler frequencies and their distribution on classification performance. The proposed classification method favorably compares with other methods based on principal component analysis (PCA) and convolutional neural networks (CNN).
Stochastic approach optimizes a system’s wavefunction to improve computational efficiency

By breaking apart a large computation into smaller components, researchers can solve the Schrodinger equation for complicated systems.
EVALUASI SISTEM INFORMASI MANAJEMEN TERHADAP PERSEDIAAN OBAT PADA RUMAH SAKIT ADAM MALIK MEDAN

Adam Malik General Hospital Medan is a government company which is engaged in providing services, where its main activity is providing health services for the community. This study aims to determine the application of drug management procedures in drug supply management information systems at the Adam Malik General Hospital, Medan. This research uses primary research. Data analysis was performed using descriptive data techniques. The focus of this research is the procedure for purchasing drugs, procedures for receiving and storing medicines, procedures for distributing drugs, and procedures for calculating the physical supply of drugs. Based on the evaluation of drug supplies at the Adam Malik General Hospital in Medan, the procedures for purchasing drugs have been carried out effectively and efficiently, while in the system of receiving and storing drugs there is still a double task, the distribution procedure is in accordance with the FIFO principle, and the physical inventory calculation procedure (stock hospitalization) was done according to schedule. Drug inventory accounting system can run well if some improvements are made to the elements. In this study the elements that need to be corrected immediately are the hospital management must separate the function of receiving and storing medicines, and carry out routine physical examinations according to the schedule.
Crime Investigation Tracker Using Clustering Algorithm

The clustering algorithm is a method of distributing the population or data points into different groups in a way that data points in a single group are alike to each other in the same group and different from the data points from another groups. Simply, the objective is to isolate groups with similar qualities and allocate them into groups. This research, focus on K -means algorithm. Therefore, type of clustering algorithm used to cluster a group of data without categories. As, the clustering is a subjective phenomenon, that can be employed for accomplishing this objective to find and create group in the data with K as the representation of the number of the groups. Thus, the algorithm procedure uses a dissimilar set of guidelines for describing the relationship between data points and will be clustered together. Indeed, there are over 100 clustering algorithms recognized. However, a crime investigation tracker using clustering algorithm uses K -means algorithm to group the identical crime to be clustered accordingly type of crime recorded in the system. For the system, will be developed using Java programming to build the interface with MySQL as the database to provide a better management to store and retrieve the report. A methodology to develop the system is using Agile Unified Process (AUP) is consists of inception, elaboration, construction, and transition to conducts the current problem of system that various crimes have been increasing, unorganized reports in storage and interface less user friendly of the current system.
Fast carrier selection of JPEG steganography appropriate for application

In recent years, the improvement of the security of steganography mainly involves not only carrier security but also distortion function. In the actual environment, the existing method of carrier selection is limited by its complex algorithm and slow running speed, making it not appropriate for rapid communication. This study proposes a method for selecting carriers and improving the security of steganography. JPEG images are decompressed to spatial domain. Then correlation coefficients between two adjacent pixels in the horizontal, vertical, counter diagonal, and major diagonal directions are calculated. The mean value of the four correlation coefficients is used to evaluate the security of each JPEG image. The images with low correlation coefficients are considered safe carriers and used for embedding in our scheme. The experimental results indicate that the stego images generated from the selected carriers exhibit a higher anti-steganalysis capability than those generated from the randomly selected carriers. Under the premise of the same security level, the images with low correlation coefficients have a high capacity. Our algorithm has a very fast running speed, and the running time of a 2048 × 2048 image is less than 1 s.
Digital Image Watermarking technique for tamper detection and restoration

Watermarking of images not only ensures image authentication but also helps in recovery of the digital images when being tampered and manipulated during transmission. Although there are numerous algorithms proposed for the watermark embedding resulting in self-recovery of images, but they work efficiently for the uncompressed domain making images defenseless against image compression attacks including addition of noise. Therefore, in order to counter these problems in JPEG domain, we propose a method that ensures self-recovery of JPEG images along with the detection of tampered area efficiently. Original image is compressed by source code and is secured against tampering using channel code. Thus, image itself is compressed and used as the watermark for embedding. The proposed method is then effectively merged with the JPEG image resulting in robust performance against the attacks of noise and also improved quality of recovered image.
The relation between philosophy of creativity and education in the knowledge society

The aim of the article is to reveal a fundamental relation between the philosophy of creativity and education in the knowledge society. Knowledge society as a special social space of modern society is formed in the middle of the 20th century with a new system of educational organizations, therefore training a knowledge worker who is able to be productive in a rapidly changing knowledge and technological environment is one of the main challenges of modern education. The contemporary philosophy of creativity has an important impact on education in knowledge society. The creative nature of learning determines the knowledge worker’s ability to achieve social, technical and technological innovations, while research work forms a dynamic competence and socio-economic performance. The article stresses that creativity remains one of the most important educational goals of knowledge society.
The Effect Of Knowledge Management System For Academic Services With SECI Model

Based on the 1945 Constitution of the Republic of Indonesia – Article 37 of 2009 verse 8 states that a lecturer profession obliges to a minimum of 12 and maximum of 16 teaching credits in every semester according to his/her academic qualifications. Todays, Institute of Information Management and Computer Science (STMIK) Widuri has been applying a sharing knowledge process amid lecturers with the intention to assist them in academic position ladder management. However, problems are found during its implementation. First problem is infrequentTri Dharma practices (three principles of higher education; education, research and contribution to society)and reports being submitted by lecturers; the condition has resulted a statistic of STMIK active lecturers in general to decrease to 41.6%. Lack of information regarding Tri Dharma practices and its administrations known by its lecturers is the one missed to solve; a lecturer does not comprehensively understand what the stages are required in order to administer their academic position ladder. Second issue is there has been no media to facilitate lecturers to spread and share the knowledge and experience with the other fellow lecturers that the process of levelling up their academic tenures or positions become hampered. This means, the slower the process the longer it takes for them to move up to the next academic position ladder. As this is the case, the researchers propose aprototype of knowledge management system (KMS) utilizing SECI methodand gathering data through interviews, observations as well as literature studies. Software used is User Acceptance Test (UAT). Furthermore, the research has come up with a web-based KSM prototype with test percentage result76%; this means the system is accepted and matched the expectation.
Study on shape optimization method for gripping part using grasping motion simulation developed for evaluating gripping comfort

In this study, we developed a grasping motion simulation that is able to reproduce grasping motion and evaluate gripping comfort. Then, we proposed a shape optimization method using the simulation to search for a gripping part design that is comfortable to grasp. Topology optimization, which used element density as the design variable, was adopted to obtain an optimized shape for the gripping part. The initial shape was a cylinder FE model. The contact pressure concentration level, which has a negative correlation with gripping comfort, was set as an objective function to maximize the gripping comfort. A realistic contact pressure values during grasping a cylindrical object obtained from previous experimental study were set as constraint conditions to prevent an excessive contact pressure. The simulation result indicated low element density at the parts where contacts with the fingertips of the index finger and the middle finger occurred. In addition, high element density was observed at the part where contact with the proximal part of the palm occurred.
Motion detection of articulatory movement with paralinguistic information using real-time MRI movie

The goal of this study is to establish the analytical method of articulatory movement by real-time magnetic resonance images (rtMRI) without estimation of articulatory contours. We present the result of motion detection using a background subtraction method. As a result of applying the background subtraction method to the rtMRI data of one speaker, some motions were detected in tongue, lip, and lower jaw which are important places for speech generation. By the experiments with the movies of multiple speakers, we confirmed that it is possible to detect the motion of the basic articulatory movement, and some movements were different for each speaker. Furthermore, we adapted the proposed method for motion detection to the utterances aiming at the transmission of paralinguistic information. As a result, some similar movements to the previous research were observed.
Essay Writing Performances at the Tertiary Level:The Case of Indonesian EFL Learners

Some methods and approaches have been put into practice by stakeholders, including both teachers and lecturers in the teaching and learning process of English, specifically writing. Nevertheless, writing English is still burdensome for some learners, particularly EFL learners. For this reason, the survey study was conducted to point out the mistakes made by the students in composing an essay. Eleven EFL learners, coming from non-Anglicized linguistic and cultural backgrounds at the Institut Ilmu Keislaman Zainul Hasan Genggong, Probolinggo, East Java, Indonesia were taken out as the sample of this study. The major instruments distributed were writing prompts and a semi-structured interview. Their writing results were scored with the scoring scale adopted from Jacobs (1981), cited in (Weigle, 2002, p. 116). From the five components in writing, consisting of Vocabulary, Content, Language Use related to the ideas in the text, Organization of the text, and Mechanics, the results demonstrate that Language use (Tense, Preposition, Run-ons, and Articles)and Mechanics (Spelling, Punctuation, and Capitalization) are dominant errors committed by the EFL Learners in writing.
Objective function maximization by machine learning for gate-model quantum computers

We define a framework for objective function estimation and maximization of arbitrary computational problems in gatemodel quantum computers. The method significantly reduces the costs of the objective function estimation and provides an estimate of the new state of the quantum computer. The framework integrates an objective function extension procedure, a segmentation algorithm that utilizes the gate parameters of the quantum computer, and a machine-learning unit for the quantum state prediction. The results are particularly convenient for the performance optimization of experimental gate-model quantum computations.
A Critique on Power Spectrum – Area Fractal Method for Geochemical Anomaly Mapping

Power spectrum – area fractal (S-A fractal) method has been frequently applied for geochemical anomaly mapping. Some researchers have performed this method for separation of geochemical anomaly, background and noise and have delineated their distribution maps. In this research, surface geochemical data of Zafarghand Cu-Mo mineralization area have been utilized and some defects of S-A fractal method have been discussed. The surface geochemical data were transformed to the frequency domain using Fourier transformation and the S-A fractal method was performed on obtained Cu power spectrum. 4 geochemical classes were distinguished on the basis of fractal diagram then these classes were separated using various filters and their signals were analyzed separately by principal component analysis (PCA) and the situation of mineralization was interpreted. PCA shows the low frequency geochemical signals have strongly been affected by the Cu and Mo mineralization process. In the end, the Cu geochemical anomaly map based on this low frequency class was delineated using inverse Fourier transformation. The deep borehole that was drilled in the center of this obtained anomaly shows there is a mineralization zone at the depth. The disadvantages of S-A fractal method have been discussed using these obtained results.
LSC-North Harris Library Research Guides: Music: Starting Point

This is a guide designed to help students find quality resources when researching classical composers, music theory, performers, western art music, fok music and popular music.
PENGKLASTERAN DOKUMEN DENGAN MENGGUNAKAN ALGORITMA SUPPORT VECTOR CLUSTERING

Data processing documents also become an important issue at this time. Along with the increasing amount of data collected and stored in a database increases drastically. This data can come from a variety of sources such as financial applications, Enterprise Resource Management (ERM), Customer Relationship Management (CRM), and others. These data if can be used to support the decision-making process. This paper shows the result of clustering data derived from students' final assignment AMIK Tunas Bangsa Pematangsiantar using Support Vector Clustering method but it also displayed the data using the software RapidMiner clustering results with pengklasteringan time for 11:21 minutes with a gain that took the title in 1708 and classified database 311 who took the title of the classified web programming.
Study on region extraction that is robust for filets using x-ray CT sinogram

Reverse engineering, where we generate CAD data from real objects, is contributing for maintaining and improving the quality of products. Therefore, reverse engineering is necessary for manufacturing industry. However, since CAD data has a variety of shapes including filets, it is still difficult to generate robust and versatile CAD data from real objects. In this study, we propose a novel method for extracting regions including two key factors. 1) We calculate gradient of curvature from X-ray CT sinogram directly. 2) We conduct semi-automatic segmentation using Morse Theory. Our method enables us to extract regions better and this leads to obtain more robust and versatile CAD data.
Development of ISTP (Indonesian Student Test Platform) evaluation tool to analyze student competency

ISTP is a website platform designed and developed to provide evaluation services and quiz online. Through the program site, teachers and students are expected to adapt to the test method switching and value recapitulation from the Manual (offline) method to the digital (online) method. This website can be used easily by both teachers and learners. The purpose of this research is to obtain a description of 1) product development in the form of Evaluation of ISTP, 2) Feasibility evaluation tool (Indonesian Student Test Platform) through the process of study and validation Experts, 3) The response of learners as a user to the assessment tool of ISTP that has been tested. The reseach development applied thiagarajan’s 4-D model. It is start from the definition stage to the development stage. The study is test on the 24 students at SMA Negeri 1 Giri. The research instruments were the questionnaire of material review and media, the material and media validity sheet, and the questionnaire of students’ responses. The result of study suggest that the ISTP is very feasible. Therefore, it can be concluded that the ISTP is effectively applied as an alternative evaluation tool in SMA Negeri 1 Giri.
Assessment of the awareness of Cypriot accounting firms level concerning cyber risk: an exploratory analysis

Technology development has made a decisive contribution to the digitisation of businesses, which makes it easier for them to work more efficiently. However, in recent years, data leakages have shown an increasing trend. To investigate the level of awareness among Cypriot accountancy firms about cyber-related risks, we use the data from a recent survey of Cypriot professional accountants' members of Institute of Certified Public Accountants of Cyprus (ICPAC). The categorical nature of the data and the purpose of our research led us to use methods of multidimensional statistical analysis. The emergence of intense differences between accounting companies in relation to the issue as we will present is particularly interesting.
Linkages Between Financial Market Development and Economic Growth in Ethiopia

In this study we consider the link between financial development and economic growth from 1971 to 2009 in Ethiopia.Most theoretical and empirical works in the literature suggest that deeper financial market promotes economic growth.We take this hypothesis to the test of conducting descriptive and empirical study using Ethiopia's data.In the empirical analysis we estimate an investment equation applying the Stock Watson Dynamic OLS procedure.The result suggests that the financial development indicator positively and significantly explains investment suggesting that financial development and economic growth have direct and strong relationship.The argument that financial development and economic growth have positive linkages is supported by results of both descriptive and empirical analysis.But the argument that financial development determines economic growth appears to be inconclusive.The Granger causality test result suggests bidirectional influence between financial development and economic growth.
Extending deep learning to new classes without retraining

The focus of this article is extending classifiers from N classes to N+1 classes without retraining for tasks like explosive hazard detection (EHD) and automatic target recognition (ATR). In recent years, deep learning has become state-of-the-art across domains. However, algorithms like convolutional neural networks (CNNs) suffer from the assumption of a closed-world model. That is, once a model is learned, a new class cannot usually be added without changes in the architecture and retraining. Herein, we put forth a way to extend a number of deep learning algorithms while keeping their features in a locked state; i.e., features are not retrained for the new N+1 class. Different feature transformations, metrics, and classifiers are explored to assess the degree to which a new sample belongs to one of the N classes and a decision rule is used for classification. Whereas this extends a deep learner, it does not tell us if a network with locked features has the potential to be extended. Therefore, we put forth a new method based on visually assessing cluster tendency to assess the degree to which a deep learner can be extended (or not). Lastly, while we are primarily focused on tasks like aerial EHD and ATR, experiments herein are for benchmark community data sets for sake of reproducible research.