Reviewerly/exHarmony huggingface dataset:
Efficient Self-embedding Data Hiding for Image Integrity Verification with Pixel-Wise Recovery Capability

Due to the powerful image editing tools, image integrity protection is becoming important, for instance, in a court of law, news reports, insurance claims or telemedicine. Digital image watermarking is a technique for detecting, localizing and recovering of tampered image but capability and accuracy of performance by the existing methods are still issues especially when tampering rate is relatively high. This paper proposes a novel blind fragile watermarking mechanism for effective image authentication and recovery. In the proposed scheme, not only the probability of detection and localization of tampering is increased because of embedding appropriate authentication code in the proper position but also there is an efficient post-processing of recovery in a way that any pixel has treated differently leading to higher quality of recovered image. Furthermore, embedding more fragile authentication code with a smaller number of bits can help to provide a second opportunity for content recovery while the quality of watermarked image is preserved. Thus, better results have been achieved in terms of accuracy of detection and the quality of recovered image after higher tampering rate compared with some of the state-of-the-art schemes.
Klasterisasi Data Rekam Medis Pasien Menggunakan Metode K-Means Clustering di Rumah Sakit Anwar Medika Balong Bendo Sidoarjo

The use of information management systems that are owned by hospitals is still limited to being used only for the operation of daily patient service transactions and making reports only. The use of SIMRS is not optimal, it should pile the data stored in the database server can be used to generate new information if we dig deeper with the IT approach. This study uses data mining techniques with K-Means clustering method to cluster the patient's medical record data. The results of this study produce column 4 clusters consisting of districts, diagnoses of diseases, age and sex.The results of this study produce column 4 clusters consisting of districts, diagnoses of diseases, age and sex. Cluster 1 produced many patients consisting of 79(15%) female patients, Cluster 2 produced many patients consisting of 214(50%) male patients. Likewise Cluster 3 produced 89(17%) female patients. people and cluster 4 produced many patients consisting of 152(28%) female patients.The grouping of patient medical record data produces new information about the pattern of grouping of disease spread in each district based on the patient's medical record data from Anwar Medika Hospital as much as 534 data with a completion time of 0.06 seconds
Penentuan Jenis Tanaman Berdasarkan Kemiringan Lahan Pertanian Menggunakan Adopsi Linier Programming Berbasis Pengolahan Citra

The slope is a measure of the slope of the land relative to the flat plane which is generally expressed in percent or degree. Agricultural land that has a slope of more than 15 ° can be more easily damaged. In this study, a value of 2.5 ° was used in determining the normal slope. The process of implementing a decision support system used linear programming adoption in determining the slope angle of the land, rotation of the slope of the land and determining whether or not the normalization of the input image was necessary or not. The purpose of this research is to determine the time needed to determine the type of plant based on rotation or the angle of setting determined by the user. The results of the study are the greater the height and width of an object the longer the time needed to determine the type of plant, land price or slope of the land. The results of the study were obtained in five tests. Tests 1 and 2 images with height and image width ranged from 150-480 obtained time for normalization of 15-30, testing 3.4.5 images with height and image widths ranging from 322 and 788 requiring 54- 108. Keywords: Slope, Adopting Linear Programming, Decision Support Systems
Optical distortion evaluation based on the Integrated Colour CCD Moiré Method

Camera calibration is an important part of high-precision optical measurement, which is especially difficult in the micro-nano field. Based on the integrated correlation calculation and CCD moiré method, this paper describes the development of a lens calibration technique called the Integrated Colour CCD Moiré Method (ICCM). The CCD moiré fringes, formed by superimposing a periodic optical signal of a specimen grating with a CCD target array or a Bayer filter array, significantly enlarges the deformation modulated by lens distortion and the calibration plate attitude (i.e. the rotation angle relative to the camera coordinate system). To measure lens distortion using CCD moiré, the deformation pattern that is governed by the lens distortion, specimen grating attitude and carrier was used to construct a CCD fringe image. If the constructed CCD fringe image based on the trial lens distortion and rotation angles have a maximum similarity to the captured CCD moiré image, the lens distortion and rotation angles are correctly inversed. Particle swarm optimisation algorithm was selected to search for the true value so that the accuracy and robustness could be improved. Numerical experiments verified that the ICCM method developed in this work can simultaneously inverse the lens distortion, rotation angle and the grating pitch with high precision. The lens distortion of the metallographic microscope has been successfully characterised by the developed method with an 833 nm pitch grating. Simulations and experiments showed that ICCM is an intuitive, accurate, anti-noise and robust distortion calibration method.
Interferometric grazing incidence test of rough steep convex spherical and aspherical surfaces: first simulations and experimental proof of principle

In the past, grazing incidence interferometry has been applied for rough plane, cylindrical, acylindrical, and general rod-like surfaces using diffractive beam splitters. Here, we demonstrate that also rough convex steep rotational symmetric spherical or aspherical surfaces can be measured along one meridian in a single step using diffractive beam splitters and phase-shifting techniques. The extension to the whole surface can be attained by successive meridional measurements of the surface under test by azimuthal adjustments. The principle of the method is given and for a spherical ball lens as an extremely curved surface simulated, and experimental data are presented. The features of the interferogram are discussed, and the experimental evaluation of a single meridian including the unwrapped phase data is shown.
Automated Infrastructure Inspection Based on Digital Twins and Machine Learning

One of the key challenges in our modern society is the provision of safe transport infrastructure. Infrastructure managers are subject to regulations requiring major infrastructures to be periodically checked for damage before it becomes a safety hazard. In the standard structural inspection, specially qualified civil engineers travel to the object to be inspected on site. Notes, sketches and photos are prepared for the subsequent report. The inspectors are introduced to non-directly accessible locations with special, heavy inspection equipment. During such a test the object is not or only partially usable, which leads to interruptions, delays, traffic jam and thus considerable non-availability costs. In recent years, approaches of a drone-based structural inspection are increasingly noticeable. These are mainly limited to a visual inspection of the created optical images. By using new technologies, a more objective and faster structural inspection can be carried out at a lower cost. In order to achieve the highest possible level of automation, the actual test is no longer performed on the real object, but on a digital twin of the construction. The assessment of damages and reporting is carried out automatically.
Visual Representations and Comprehension: The Exploration of Image-Word Relations and Types of Design

Visualisation has been used for decades as a strategy to help readers construct meaning from reading passages. Teachers across the globe have introduced visualisation mostly to primary students with native language background. They used the strategy to understand their own language. Little is known how this strategy works for university students who learn foreign language. Visualisation can be done internally (by creating mental imagery) and externally (by drawing visual representation). The product of visualising texts by using both models can be further investigated to find out if the meaning represented is appropriate to the meaning written in the text. This study therefore aims at exploring meaning by analysing the visual representations drawn by 26 English Education Department students of Syiah Kuala University after they read a narrative text. The exploration was conducted by looking at the image-word relations in the drawings. To do so, we consulted Chan and Unsworth (2011), Chan (2010) and Unsworth and Chan (2009) on the image-language interaction in multimodal text. The results of the analysis have found that the equivalence, additive and interdependent relations are mostly involved in their visual representations; and these relations really help in representing meanings. Meanwhile, the other three relations which are word-specific, picture specific and parallel are rarely used by the students. In addition, most students created the representations in a form of a design which is relevant to represent a narrative text. Further discussion of the relation between image-word relations, types of design and studentsâ€™ comprehension is also presented in this paper.
A Lut-Based Method to Estimate Clear-Sky Instantaneous Land Surface Shortwave Downward Radiation and its Direct Component from Modis Data

Land surface shortwave downward radiation (SWDR) is generally defined as incident solar energy over land surfaces in the shortwave spectrum (300-3000nm). As one of important parameter of the land surface radiation budget (SRB) and many land process models, it is usually required as part of the input variables to address a large variety of scientific application issues in fields of agricultural management, climate trends, ecological forecasting, reusable energy production, public health and so on. Currently, regional or global SWDR can be estimated from polar-orbiting or geostationary satellite observations based on empirical or physical-based retrieval models. These remote-sensed SWDR products with fine spatial resolution provide us valuable information about a series of critical Earth science problems and enable us to gain more insight into the planet we live on. In this paper, an improved method was proposed based on a look-up table approach via MODTRAN-5 simulations to estimate clear-sky instantaneous SWDR and its direct component from TOA radiance of Moderate Resolution Imaging Spectrometer (MODIS) observation. Ground measurements from seven SURFRAD sites are used for validating the algorithm and the result shows good accuracy. This approach is suitable for producing clear-sky instantaneous SWDR and its direct component at the spatial resolution of finer than 5 km.
Phase Unwrapping Algorithm Based on Improved Weighted Quality Graph

Interferometric synthetic aperture radar (InSAR) has become the primary means to obtain digital elevation models(DEM) on the earth's surface, including several key steps such as removal of flatten effect, filter processing, and phase unwrapping. Due to atmospheric interference, etc., the distribution of azimuth and range to phase quality on SAR images is uneven. Thus, this paper proposes a method based on weighted quality graph to guide phase unwrapping, which considers the difference of the contribution weight of spatial noise to the range and azimuth of the quality graph. The weighting method is used to eliminate the error of the range direction and the azimuth direction, form a new quality graph, and guide the phase unwrapping. In order to solve the problem of slow speed of traditional methods, this paper introduces the method of heapsort to improve the speed of phase unwrapping.
Second Language Interference towards First Language Use of Japanese Learners

There have been many studies on first language interference towards learners’ second or foreign language learning, but not many on the otherwise. This study investigates the effects of learning Japanese as a foreign language towards learners’ first language use, Indonesian. The data for this qualitative study were obtained from five Japanese learners who had different backgrounds of Japanese learning. Observation and interview were used as the research instruments to collect the data in this study. The results were found that the learners showed foreign language effects; grammatical aspects and borrowing. In short, learning a foreign language (FL) influences learners’ first language (L1), which means that learning Japanese language had affected the learners’ first language, Indonesian. It can be concluded that learning a second or foreign language may interfere a learner’s first language.
Competence-oriented Tasks as a Means of Formation the Future Teacher’s Professional Activities

The aim of the article is to consider the issues of using the competence-oriented tasks to increase the effectiveness of the future teacher’s professional training and his professional activities. The experience of conducting classes using competence-oriented tasks in the Dagestan State Pedagogical University is presented. Methods . Observation, conversation, testing, pedagogical experiment. Result . In the course of participation in classes using the competence-oriented tasks, students are developing general professional and professional competencies. Conclusion . The use of competence-oriented tasks contributes to increasing the motivation of learning, interest in the study of subjects of psychological and pedagogical cycle, increases their level of professional competence in general and the effectiveness of training for professional activities.
An Industry Study of Blockchain Technology’s Impact on Trade Finance

Blockchain’s transformational potential has been heralded across several industries, with some enthusiastic voices comparing its foreseeable impact to that of the essential internet communication protocol TCP-IP. Several enterprises have since adopted distributed ledger technology (DLT)-based approaches as part of their operational procedures, with a view on blockchain as a magic bullet for addressing existing operational inefficiencies, improving transparency, and creating new products. However, in the absence of large-scale feasibility studies and data-based quantifications of the impact of blockchain-based technologies, companies are jumping into early-stage proof-of-concept (POC) projects without clearly-defined key performance indicators or goals for the expected return on investment; efficiency claims and reports of lessons learned are similarly lacking. A quantitative assessment of (1) the nature of a successful application of blockchain technology for supply chain and trade finance, and (2) the current market’s perceived benefits, key challenges, and expected horizons of blockchain is therefore sorely needed. Here we present an empirical study of the industry’s perception of blockchain-based innovation and potential for value creation for supply chain and trade finance. Our survey results show that, while industry experts across all regions view the technology and the value it can provide to streamline and simplify trade finance processes favorably, none of the study’s participants have yet realized any financial or customer-value benefit. Indeed, despite predictions, no tangible savings appear to have been realized to date. Furthermore, while initial technical proof-of-concept (POC) implementations of blockchain have been executed without major difficulties, we find that challenges associated with broader-scale adoption remain unaddressed. Notably, coordinating the simultaneous adoption of a shared solution by different stakeholders remains a formidable challenge, thus hampering the potential large-scale adoption of blockchain technology.
Applications of Augmented Reality Apps in Teaching Technical Skills Courses

Teaching technical skills courses is an integral element in most educational systems, however, the skills students need to acquire have been changing radically over the past 100 years. This change continues, as technology increasingly penetrates everyday life, demanding to acquire new skills. In many countries, technical education starts in primary school and the basics of technical literacy are taught to pupils aged 6–14. In the Czech Republic and Slovakia, future primary teachers are required to develop novel teaching approaches to develop technical literacy and skills for pupils aged 6–14 in a rapidly evolving digital world. This chapter aims to highlight the possibilities of using extended and augmented reality applications in technical education for the preparation of future teachers.
SceneCam: Using AR to improve Multi-Camera Remote Collaboration

During multi-camera remote collaboration on physical tasks, as the name implies, multiple cameras capture different areas and perspectives of a task space. It can be challenging for the remote user to obtain the right view of the local user and to understand the spatial relationship between the disjointed views of task space areas. We present SceneCam, a prototype with which we use AR to explore different techniques for improving multi-camera remote collaboration by making optimal camera selection easier and faster for the remote user and by making the spatial relationship between task space areas explicit. To this end, SceneCam implements two camera selection techniques: nudging the remote user to select an optimal camera view of the local user, and automatic selection of an optimal camera view of the local user. Furthermore, SceneCam provides the remote user with two focus-in-context views - exocentric and egocentric views - that visualize the spatial relationship between the multiple task space areas and the local user.
Construction of Two Dimensional Cubic-Tent-Sine Map for Secure Image Transmission

A fusion two dimensional Cubic Tent Sine (CTS) map is formulated and its dynamic range is analysed. To explore its application in secure electronic data transmission, an image cipher is developed under the architecture of confusion and diffusion. A new dual form of chaos series based confusion with fast and efficient method is employed in this cipher. Chaotic key image with excellent random behaviour is utilized for diffusion phase. The proposed cryptosystem entails higher key space and single round structural design to achieve fast and efficient cipher. The random evaluation of CTS proves that the generated key series has more complicate chaotic conduct. Simulation outcomes demonstrates that the proposed cipher possesses better performance than other image ciphers. Security assessment proves the cipher strength that can resist against various attacks.
Linear mixed-effects model for longitudinal complex data with diversified characteristics

The increasing richness of data encourages a comprehensive understanding of economic and financial activities, where variables of interest may include not only scalar (point-like) indicators, but also functional (curve-like) and compositional (pie-like) ones. In many research topics, the variables are also chronologically collected across individuals, which falls into the paradigm of longitudinal analysis. The complicated nature of data, however, increases the difficulty of modeling these variables under the classic longitudinal framework. In this study, we investigate the linear mixed-effects model (LMM) for such complex data. Different types of variables are first consistently represented using the corresponding basis expansions so that the classic LMM can then be conducted on them, which generalizes the theoretical framework of LMM to complex data analysis. A number of simulation studies indicate the feasibility and effectiveness of the proposed model. We further illustrate its practical utility in a real data study on Chinese stock market and show that the proposed method can enhance the performance and interpretability of the regression for complex data with diversified characteristics.
Multiscale ship detection based on dense attention pyramid network in SAR images

The scales of different ships vary in synthetic aperture radar (SAR) images, especially for small scale ships, which only occupy few pixels. So ship detection methods currently face difficulties in detecting multiscale ships. A novel method for multiscale ship detection in SAR images based on Dense Attention Pyramid Network (DAPN) is proposed in this paper. It can extract multiscale and salient features by DAPN, which densely connects Convolutional Block Attention Module (CBAM) to each feature map from top to down of the pyramid network. Then the fused feature maps are fed to the detection network for multiscale ship detection. Experiments on SSDD dataset show a better performance of this method to detect multiscale ships in different scenes of SAR images.
Application of BP Neural Network in Network Fault Diagnosis

There are various deficiencies in network fault diagnosis methods but the need for fault diagnosis is further increasing. In order to adapt to the current development needs, the paper applies the artificial neural network concept to network fault diagnosis. Aiming at the slow convergence speed of traditional neural networks and the tendency to fall into the local optimal solution, first we attempt to add the momentum factor and then adopt rough set preprocessing data. The simulation results show that the improved algorithm has a certain advantages for the original BP algorithm, and it has a certain value for future fault diagnosis research.
A COMMUNICATION AID SYSTEM BY FEATURE EXTRACTION OF ELECTROOCULOGRAPHIC SIGNALS

People with serious movement disabilities due to neurodegenerative diseases have problems in their communication with others. Considerable numbers of communication aid systems have been developed in the past. Especially, some of the systems driven by eye movements are thought to be effective for such people. Electrooculographic (EOG) signal reflects the eye movement and the specific pattern of eye movement can be seen in EOG signals. This paper proposes a communication aid system by extracting the features of EOG. The system consists of a computer, analog-to-digital converter, biological amplifier and two monitors. Two monitors, one for a system user and the other for other people, display the same information. Five items are presented in the monitor, and a user selects those items according to the situation in the communication. Selection of the items is done by combining three eye movements: gaze at left, gaze at right and successive blinks. Basic concept of the communication aid system was designed by taking into account the current state of a subject’s movement disability. Then, the design of a screen and the algorithm for detecting eye movement pattern from EOG were determined by using the data of normal healthy subjects. The system worked almost perfectly for normal healthy subjects. Then, the developed system was operated by a subject with serious movement disability. Parts of the system operation were regarded as satisfactory level, and some miss-operation were also seen.