Reviewerly/exHarmony huggingface dataset:
Verktøy som materiale

In this exposition I wish to point to a type of artistic research evolving around development of technology as artistic material, as an extension to the condition of possibility for an artistic expression. The well known distinction between research *for* and research *in* the arts, in my opinion becomes blurred in these type of works. Those tools developed to facilitate the artistic exploration constitute the base material for the artist, and the development of these tools are an intrinsic part of the artistic process. The examples are shown as recorded sound and video, and the technological material is thus still hidden from the reader. They can not see the material itself, just the traces it leaves. I would argue that the artistic process here starts with the investigation of potential, guiding the development of tools, and the tools will have certain affordances correlating with some aspects of the original artistic spark (desire). The artistic process of exploring said affordances will also in many cases lead to unexpected outcomes, in the interaction between human and machine, artist and tool
DUAL IMAGE STEGANOGRAPHY USING KEKRE'S LUV COLOR SPACE WITH IMPROVED IMPERCEPTIBILITY AND ROBUSTNESS

Steganography is an art of data hiding. It is an ancient technique used for secret communication.Security and privacy are important keys in communication. This paper has proposed a method which willperform dual steganography on a single RGB color image by maintaining the balance among imperceptibility,capacity and robustness. Dual steganography means hiding two secret images inside one single cover image. Inthe proposed method two secret color images are embedded inside single cover color image. For embedding firstsecret image Kekres LUV color space model and DWT is used and for second secret image RGB colorspace model with LSB steganography method is used. In order to increasing the security of the proposedmethod image scrambler algorithm is used that will scramble both secret images before embedding into thecover image and by using descrambling algorithm extract the original secret image. Proposed method is testedagainst various Steganalysis attacks and it gives better result compared to existing method. Various performancemetrics have been used like MSE, PSNR, SSIM and Correlation Coefficient.
ANALYSIS DEVELOPMENT OF E-GOVERNMENT ON PROVISION OF INFORMATION ACCESS IN CENTRAL JAVA’S PROVINCE LIBRARY

Globalization is a phenomenon where people expect a much more effective and efficient interaction than before, both directly and indirectly. The Provincial Government of Central Java utilizes technological advances in the current era of globalization to fulfill the needs of citizens. Central Java Province Library under the Departement of Archives and Central Java Library innovates by implementing the concept of e-government. Central Java Provincial Library oriented to public services. Where they provide an easy access for people who want to do library activities through e-government. The e-government programs owned by the Central Java Provincial Library include websites, iJateng, RFID, InlisLite, RBM, and other electronic facilities. The research method used is descriptive qualitative. Primary data is collected through interviews with government officials who are authorized and directly involved in e-government activities and field observations. Meanwhile, secondary data is collected through information available on the Central Java Province Library website and data obtained from the site. The results showed that the implementation of e-government was good, but in the development of e-government there were still some problems in Human Resources and existing facilities. It is recommended that the results of this study can be a boost in the development of e-government in the Central Java Provincial Library which is better than before, so that it can provide more optimal public services to the visitors.
Konsep Pengamanan Video Conference Dengan Enkripsi AES-GCM Pada Aplikasi Zoom

The conditions of the Covid-19 pandemic, which began to plague at the end of 2019, brought about major changes to the patterns of interaction in society. Activities that have been carried out directly have begun to shift to activities carried out online. The use of technology, especially in applications for online interaction patterns such as video conferencing applications, is an alternative. The Zoom Cloud Meeting application is widely used by people who initially had doubts about its security system. By implementing end-to-end encryption with AES-256-GCM, it has been able to convince clients on the information security side to keep using the Zoom Cloud Meeting application.
Research on the influence of the near vision area on the width of the astigmatism channel based on the minimization model

Freeform progressive addition lenses (PALs) are mainly divided into distance vision zone, near vision zone, astigmatism channel and peripheral astigmatism zone. The purpose of this study was to compare the effect of the width of the astigmatism channel by changing the near vision area of PALs on the basis of the minimal model method. The change of the near vision area was mainly achieved by changing the distribution function of the main curvature difference and the average curvature weight. Firstly, two weight distribution matrices of different near vision areas were designed, and the second-order partial differential equations of the minimized model were solved by the finite element method. The surface shape of two PALs was obtained. Secondly, the freeform verifier software (FFV) (ROTLEX, Israel) was used to simulate the shapes of the obtained surfaces, and used computer numerical control machine tools to process two groups of PALs. Finally, the Visionix VM-2500 lens measuring instrument was used to measure the PALs. The simulated and measured power and astigmatism distribution contours showed that the width of the astigmatism channel increased with the increase of the near vision area, however, the peripheral astigmatism was increased. Therefore, the near vision zone with an appropriate area can provide a reference for the optimal design of PALs.
Post-processing for Enhancing Audio Steganographic Undetectability

Currently, the conventional steganography method often only perform data embedding, without additional post-processing to enhance undetectability. In this work, we propose a new audio post-processing steganography model, which further hiding the traces to a certain extent. Specifically, we design the Signal-to-Noise Ratio (SNR) threshold to determine whether the current stego is suitable for adding disturbance or not, and use JS divergence to decide whether the added disturbance is kept or not, respectively. The designed two measures will process the traces frame-by-frame by adding appropriate disturbances on needed sampling points of the stego audio. Experimental results illustrate that, with the proposed post-processing, the undetectability can be successfully improved without affecting the message extraction.
An Analysis and Comparative Study of Data Deduplication Scheme in Cloud Storage

Data deduplication is another method for compressing the information and it is useful in productive utilization of storing the space and ends up being a superior strategy to deal with duplicate information. Deduplication permits unique or single data copies are stored in the database initially and sequential duplicates are delivered with interfacing indicator to the authorized stored replica of information. This paper analyses the deduplication scheme and comparison between them and the idea about the methodology also. The study showed is structured in smooth way to carry out the crisp of improvement in the deduplication schemes.
WIFROWAN: Wrapped Imbalanced Fuzzy-Rough Ordered Weighted Average Nearest Neighbor Classiﬁcation

In this paper we propose an ensemble method based on IFROWANN (Imbalanced Fuzzy-Rough Ordered Weighted Average Nearest Neighbor) algorithm to classify problems with imbalanced data. The ensemble generates many classifiers with different weight strategy and indiscernibility fuzzy relations. Classification is carried out selecting one of three strategies: I- to classify the new instance with the algorithm with best AUC in training. II- to average the memberships of the instance to the fuzzy-rough lower and upper approximation of each class given by the classifiers with best AUC. III- to average the memberships of the instance to the fuzzy-rough lower and upper approximation of each class of the all classifiers. Our method is validated by an extensive experimental study, showing statistically better results than 14 other state-of-the-art methods.
EOSC-SYNERGY. EU DELIVERABLE: D3.3 Intermediate report on technical framework for FAIR principles implementation

This deliverable introduces the provisional recommendations for assessing data FAIRness, and ‘FAIR enabling’ data repository features, coming from FAIRsFAIR. It also provides a roadmap for implementation of FAIR requirements, and details about architecture, requirements, and other technical considerations related to Software- and Service-Quality Assurance in line with the focus of the EOSC-SYNERGY project.
Multichannel Interactive Interface Model for Mobile Learning Terminal by Considering User's Requirements

In view of the problems of large response delay and poor security in current research methods of mobile learning terminal interactive interface, a multi-channel interactive interface model of mobile learning terminal considering user needs is proposed. According to the C/S model, the interactive interface model is hierarchically divided, which can effectively improve the information processing efficiency of the mobile learning terminal multi-channel interactive interface model. On this basis, the key modules of the model, such as resources, sharing, learning and examination, are designed to consider user needs, so as to realise the function that interviewees can answer questions in a more timely manner and feedback questions to questioners. The experimental results show that the success rate of illegal users is less than 0.05%, the retrieval delay of learning resources is between 50 ms-100 ms, and the retrieval delay of papers is between 120 ms-150 ms.
An Assessment on Credit Card Fraud Detection: Survey

Credit card fraud is a costly problem for many financial institutions, costing businesses billions of dollars a year. Many adversaries still escape fraud detection systems because these systems often do not include information about the adversary's knowledge of the fraud detection mechanism. This thesis aims to include information on the motivations of crooks and the knowledge base in an adaptive fraud detection system. In this thesis, we use a theoretical adversarial learning approach to classification to model the best fraudster strategy. We proactively adapt the fraud detection system to classify these future fraudulent transactions better. Therefore, this document aims to provide an over-supervised bird's-eye approach with a suitable feature extraction technique that improves fraud detection rather than mistakenly classifying an actual transaction as fraud.
Intelligent Sentiments Information Systems Using Fuzzy Logic

Sentiment analysis plays an important role in present era. Nowaday’s, Internet has become a source of text-based information on social media such as Twitter and Facebook. It is growing day by day, covering all the fields of knowledge. Today, sentiment Analysis has received a considerable attention to word opinion, and subjectivity in the human life. Sentiment analysis (SA) is an interesting and emerging field of research area of text mining also called as opinion mining. Today, more and more people are using these social media platform for expressing their feelings, emotions, and expressions toward sentiment information. This research paper proposed a model using fuzzy logic to express the feelings of users based on Indian railway services offered. The analyses show there is 25–35% of positivity toward service (s).
Perancangan Sistem Informasi Buku Kasus Berbasis Web Pada SMK Multi Media Mandiri Jakarta

Enforcement of rules and order in schools is one of the important things in order to build the character of discipline in students. One way for schools to enforce regulations is to implement a point system. Where every violation committed by students will be recorded and penalized in the form of points in accordance with the category of violation. Students who already have certain points will get action, either in the form of parents' summons, warning letters, or even expelled from school. But sometimes the authorities record student points for having incomplete, miscalculated, or even missing data, thus hampering the handling of violations when students are at a higher grade level. Therefore we need a web-based system that is integrated with the database to manage student violation point data. This system enables accurate and efficient data storage. The method used in the operation of the application is the waterfall, using data and procedures from the school.
Fixing Distortions on Images

People have long desired editing the defects on images and, removing or altering the corrupt regions of image data in a way that would not be detected by the neutral observer unaware of the original copy. Utilizing computers for such procedures have not only improved the quality of the work, but also eased the processes. However, notwithstanding in a computing environment, the procedures are still conducted manually. Image Inpainting method has enabled a faster and an automatic process. Video Inpainting on images can be done by using inpaint_telea and inpaint ns classes, which are both developed for Open CV Library.
Context-Aware Sensor Adaption of a Radar and Time-of-Flight Based Perception Platform

This paper presents an approach to enhance the perception quality of a multi-sensor system by considering the context information. The platform's context state is obtained by combining data from the perception sensors and from additional context sensors. This context information is then utilized to dynamically adapt the sensing/processing parameters to the current context. Additionally, the system is capable to detect a reduced perception performance of individual sensors caused by environmental influences.The proposed approach was implemented on a multi-sensor platform, equipped with Time-of-Flight (ToF) cameras, radar sensors and multiple context sensors. The static Robot Operating System (ROS) architecture of the existing platform was extended to support automatic parameter adaption during runtime. In order to demonstrate the approach with real-world data, the platform was exposed to different scenarios. The proposed approach results in a significantly increased perception quality compared to the output of a static implementation.
DESCRIPTION OF GRAPHS WITH ASSOCIATIVE OPERATIONS IN SET@L PROGRAMMING LANGUAGE

Usually, an information graph with associative operations has a sequential (“head/tail”) orparallel (“half-splitting”) topology with invariable quantity of operational vertices. If computationalresource is insufficient for the implementation of all vertices, the reduction transformationsof graphs with basic topologies do not allow for the creation of an efficient resource-independentprogram. In fact, the “half-splitting” variant is characterized by irregular connections betweeniterations, and the “head/tail” structure has an increased data duty cycle in the reduced form.In this paper, we propose to transform the topology of a graph with associative operations into acombined variant with sequential and parallel fragments of calculations. The resultant combinedtopology depends on computational resource of a parallel computer system, and such transformationprovides the improvement of specific performance for the reduced computing structure.The considered topology contains isomorphic subgraphs with the “half-splitting” topology, whichinclude the maximal number of hardwarily implemented operational vertices, but the processing ofintermediate data is performed using the “head/tail” principle. The computing structure for thecombined topology has minimal latency and includes one basic subgraph and one vertex withfeedback. This vertex is obtained as a result of the “head/tail” block reduction. We develop analgorithm for the conversion of the initial sequential graph to various combined topologies or tothe limiting case of the “half-splitting” topology with regard to available hardware resource.Within traditional methods of parallel programming, it is possible to describe the variety of topologiesonly as a set of separated subprograms. To create an efficient resource-independent program,we propose the application of the Set@l programming language. We describe the“head/tail” and “half-splitting” principles as the attributes of set processing methods in Set@l.Resource-independent program uses these types and parallelism attributes for the modification oftopology and further reduction of performance in the corresponding aspects.
An Efficient Watermarking Process Based on Three-Level DWT and FFT Technique

Digital image watermarking has become an interesting research field to face the issues created by the increasing use of Internet for distribution of digital data. For the couple of decades, authenticity of digital data has been concern for everyone. Digital image watermarking plays a vital role in protection of copy rights. In frequency domain watermarking, discrete cosine transform (DCT)-based watermarking process is most common because the majority of image compression methods are developed in DCT domain. This research presents a robust discrete wavelet transform (DWT) and fast Fourier transform (FFT) manner-based digital watermarking (DW). In the initial stage, split the original (cover) image into two horizontal and two vertical sub-bands using 3-DWT-FFT sub-band using changing their values. In this thesis, the embedding and extraction technique for watermarking is presented based on DWT & FFT transforms. In this technique, the embedding and de-embedding of the watermark is much easier than other transform techniques. Various values of PSNR’s, MSE’S & NC’s are analyzed for watermarked image quality and extracted watermark quality.
Embodied Meaning Making: An Approach to Analyzing and Designing Ambient Media

Embodied cognition believes that the interaction between body and environment plays a major role in understanding the world. Despite growing research interests in the experiential aspects in HCI, less work has been done on exploring approaches to designing meaningful experience in the context of ambient media. Building on embodied interaction and cognitive semantics, this paper proposes an embodied methodology to designing ambient media based on interpretive and empirical studies. We applied the approach to design and build an ambient media work Reading Door. Experiments were conducted to collect empirical data on participants’ experience. Thematic analysis indicates that interacting with an interactive ambient media facilitates constructing the embodied metaphor that maps from bodily action to conceptual meaning. The findings also show that the embodied approach offers useful guidance for designing meaningful experience with ambient media. Three design principles were proposed to strengthen the approach and expected to inform future studies.
Implementasi Metode Simple Additive Weighting dan Machine Learning Untuk Rekomendasi Produk Skin Care Berbasis Android

Skin health, especially facial skin, is important because the face is the main attraction seen by others. This is closely related to the use of skincare products or skin care products that are used daily. Before determining which skincare product to use, it is very important to know the conditions and problems of facial skin. To make it easier to find out skin conditions and problems, researchers created an android-based application called using the Machine Learning and Simple Additive Weighting methods. In the application, Machine Learning plays a role in providing information on skin problems based on the results of feature extraction using the Gray Level Co-Occurrence Matrix (GLCM) method whose feature extraction results will be classified by the K-Nearest Neighbor method through inputting images on facial skin using the cellphone camera feature. Meanwhile, the simple additive weighting method is used to provide recommendations for skincare products based on the criteria for skin problems, skin types, age and product price ranges to be recommended. The implementation of the Hi Beautiful application is made using the open source Android Studio application. The results of tests carried out on the Hi Beautiful application include information on skin problems and recommendations for skincare products in the form of cleanser, toner, serum and moisturizer.
Attendance Monitoring Using Computer Vision

Monitoring attendance is a very important aspect in any environment where attendance is crucial. However, many of the available attendance monitoring methods are time taking, disturbing and it requires more human intervention. The proposed system is aimed at developing a less disturbing, cost-effective, and more efficient automated student attendance management system using neural networks. In this framework, CNN is used as a classifier to recognize the facial images captured using Raspberry Pi. This system enables accurate attendance. Its targeted users are educational institutes. Hence, this prototype avails an effective solution for replacing an existing system with an embedded attendance system.
A Density-Based Prototype Selection Approach

Due to the increasing size of the datasets, prototype selection techniques have been applied for reducing the computational resources involved in data mining and machine learning tasks. In this paper, we propose a density-based approach for selecting prototypes. Firstly, it finds the density peaks in each dimension of the dataset. After that, it builds clusters of objects around these peaks. Finally, it extracts a prototype that represents each cluster and selects the most representative prototypes for including in the final reduced dataset. The proposed algorithm can deal with some crucial weak points of approaches that were previously proposed regarding the setting of parameters and the capability of dealing with high-dimensional datasets. Our method was evaluated on 14 well-known datasets used in a classification task. The performance of the proposed algorithm was compared to the performances of 8 prototype selection algorithms in terms of accuracy and reduction rate. The experimental results show that, in general, the proposed algorithm provides a good trade-off between reduction rate and the accuracy with reasonable time complexity.
ANALYSIS OF ROTATION AND SCALE INVARIANCE FOR PROXIMITY MEASURES IN TARGET DETECTION

The problem of stability of object detection in images using proximity measures is considered. The purpose of the work is to determine the degree of invariance of various proximity measures for detecting objects by reference when rotating and zooming the scanned image. The proximity measure that is most resistant to these geometric transformations of the image is found out. The proximity measures are analyzed: correlation, comparison, Chamfer Distance. The target location is based on the coordinates of the extremum of the target function. Modeling is performed in the Matlab software package. A database of thirty television images was created to test the proximity measures. Test images contain the required objects and imitations of both complex and simple backgrounds. It was determined that all considered proximity measures steadily determine the target with small turns and scaling factors.