Reviewerly/exHarmony huggingface dataset:
From Information and Quantum Physics to Consciousness and Reality

How does the world around us work and what is real? This question has preoccupied humanity since its beginnings. From the 16th century onwards, it has been periodically necessary to revise the prevailing worldview. But things became very strange at the beginning of the 20th century with the advent of relativity theory and quantum physics. The current focus is on the role of information, there being a debate about whether this is ontological or epistemological. A theory has recently been formulated in which spacetime and gravity emerges from microscopic quantum information, more specifically from quantum entanglement via entanglement entropy. A latest theory describes the emergence of reality itself through first-person perspective experiences and algorithmic information theory. In quantum physics, perception and observation play a central role. Perception, interaction with the environment, requires an exchange of information. Via biochemical projection, information is given an interpretation that is necessary to make life and consciousness possible. The world around us is not at all what it seems.
A Singular Value Decomposition Based Low-Computational Zero-Watermark Algorithm For Digital Right Management

Digital rights management (DRM) is a systematic approach used for protecting the exclusive rights in the digital mass media. It uses a set of technologies to control doubling and reproducing exclusive rights for the digital works and software. The digital watermarking is one of the powerful technologies that play a vital role in numeral rights management. In this paper, a low-computational zero watermark (ZW) algorithm has been projected. It depends on the singular value decomposition (SVD) and implemented on standard cameraman, Barbara, Lena and living room images without attack and with various attacks. The significant feature of this algorithm is that it does not fuse any watermarking in the given source image and hence the result of the zero-watermark algorithm is looking very similar to the source image. This zero-watermark property is obtained by using SVD approach in which the ZW sequence is computed in accordance with the equivalence of prior digits of major remarkable worth in every slab. The implementation consequences shows highest similarity measures of 0.8658 for cameraman image. Further, the computational cost of the algorithm is calculated as 4.442 msec of execution time for all the images under watermark embedder and watermark extractor phases. The PSNR values are calculated for the watermarked images for testing the robustness in the algorithm that is proposed, and the observations have shown the promising results against attack.
Detecting Online Spams through Supervised Learning Techniques

With more customers utilizing on the online review surveys to educate their administration basic leadership, assessment of reviews which economically affect the reality of organizations. Obviously, crafty people or gatherings have endeavored to manhandle or control online review spam to make benefits, etc, and that tricky recognition and counterfeit sentiment surveys is a subject of continuous research intrigue. In this paper, we clarify how supervised learning strategies are utilized to recognize online spam review surveys, preceding showing its utility utilizing an informational index of lodging reviews.
Density Based Spatial Clustering Application with Noise by Varying Densities

Cluster algorithms are used for grouping up of similar points to form a cluster. It has seen mostly in Machine Learning algorithms. The most popular density-based algorithm is DBSCAN. DBSCAN can find the clusters, irrespective of its shapes and sizes of a cluster. DBSCAN algorithm can easily detect the noise in a clustering dataset. In the proposed algorithm we developed a model based on the existing dbscan algorithm. In the developed algorithm we focus mainly on the epsilon parameter value. Whenever the dbscan algorithm fails to form a cluster we increase the epsilon value by half of its original size. We repeat this step until a cluster is formed. Whenever a cluster is newly formed we change existing epsilon parameter value by adding the 10 percent of the previous used epsilon parameter value. We use epsilon for varying the density of a cluster. So, we can use the dbscan algorithm with the varying density values for developing a cluster. We applied this algorithm on the various datasets.
Tutorial on Using Machine Learning for Activity Recognition Via a Smartphone

This article provides a tutorial for developing a simple machine learning application in Python. More spe-cifically, the paper considers daily activity recognition using sensors of a smartphone. For development, we used TensorFlow, Skikit learn, NumPy, Pandas, and Matplotlib. The paper explains in detail the main steps of the application development, including data collection and pre-processing, design of the neural network, learning process, and use of a trained model. The overall accuracy of the developed application when recognizing the activity is about 95 %. This paper can be useful for students and specialists who want to start work on machine learning.
A review on existing learning techniques applied in solving optical character recognition problem

Optical character recognition is treated as the classical problem in image processing that can be widely used for application areas related to computer vision. This process is highly dependent on the languages, as well as various formats of information like hand written/printed/sculptured documents as input. The chief operations that can be performed while handling this task are training the system and predicting the characters based on the trained knowledge. Conventionally, classification and regression mechanisms are used for this purpose. Due to the recent advents in technological progress, the same mechanism was served with the help of modern machine learning and deep learning concepts. The main agenda of this paper is to create awareness among the researchers by discussing existing mechanisms related to solve optical character recognition using various machine learning and deep learning concepts.
Modern Language Range Mapping for the Study of Language Diversity

Research regarding the ecology and evolution of languages has advanced rapidly in recent years, increasing demand for digital spatial location data for individual languages. However, language mapping and geographic information system (GIS) data creation has not kept pace with this demand. To date, language range information is typically contained in small, private regional datasets, paper maps and published illustrations, or in a very small number of global digital datasets. Each of these sources has advantages and disadvantages, and though these considerations may not be apparent to all data users, they can have significant impacts on research results. Mapping of language ranges is a particularly complex problem in regions where colonial histories have had dramatic effects on language diversity, language locations, and the relative representation of colonial and indigenous perspectives. Here we consider how the creation of digital language range data can better meet the needs of researchers interested in language diversity, discuss how better standards for data quality and transparency can be implemented for digital language range maps, and present a map of North American language ranges that has resulted from the use of these procedures and standards.
A Novel Text Representation Model to Categorize Text Documents using Convolution Neural Network

This paper presents a novel text representation model called Convolution Term Model (CTM) for effective text categorization.In the process of text categorization, representation plays a very primary role.The proposed CTM is based on Convolution Neural Network (CNN).The main advantage of proposed text representation model is that, it preserves semantic relationship and minimizes the feature extraction burden.In proposed model, initially convolution filter is applied on word embedding matrix.Since, the resultant CTM matrix is higher dimension, feature selection methods are applied to reduce the CTM feature space.Further, selected CTM features are fed into classifier to categorize text document.To discover the effectiveness of the proposed model, extensive experimentations are carried out on four standard benchmark datasets viz., 20-NewsGroups, Reuter-21758, Vehicle Wikipedia and 4 University datasets using five different classifiers.Accuracy is used to assess the performance of classifiers.The proposed model shows impressive results with all classifiers.
ONTOLOGICAL ARGUMENTS

Abstract This is a short introduction to ontological arguments. It begins with a brief characterization of ontological arguments that proceeds mainly by way of example. The rest of the discussion is given over to consideration of what looks like a very simple ontological argument. This consideration turns up many of the issues that arise when more complex ontological arguments are examined.
Two-way covert quantum communication in the microwave regime

Abstract Quantum communication addresses the problem of exchanging information across macroscopic distances by employing encryption techniques based on quantum mechanical laws. Here, we advance a new paradigm for secure quantum communication by combining backscattering concepts with covert communication in the microwave regime. Our protocol allows communication between Alice, who uses only discrete phase modulations, and Bob, who has access to cryogenic microwave technology. Using notions of quantum channel discrimination and quantum metrology, we find the ultimate bounds for the receiver performance, proving that quantum correlations can enhance the signal-to-noise ratio by up to 6 dB. We show that security can be reached by covering the carrier signal through the presence of the thermal noise in the environment. We complement our information-theoretic results with a feasible experimental proposal in a circuit QED platform. This work makes a decisive step toward implementing secure quantum communication concepts in the previously uncharted 1 − 10 GHz frequency range, in the relevant scenario when the available power is severely constrained.
Towords Secure Data Management using Blockchain in Iot Enabled Environment.

The Internet of Things (IoT) is continuously a reality nowadays. By and by, some key difficulties still must be constrained to run express consideration all together that IoT arrangements extra help the developing interest for associated gadgets and furthermore the administrations advertised. Because of the potential importance and affectability of administrations, IoT arrangements should address the security and protection issues enveloping these gadgets and furthermore the data they gather, create, and process. As of late, the Blockchain innovation has increased much consideration in IoT arrangements. Its essential utilization circumstances ar inside the cash space, where Blockchain makes a promising applications world and may be utilized to tackle security and protection issues. Be that as it may, this developing innovation has an incredible potential inside the most various mechanical territories and may impressively encourage achieve the Internet of Things read in a few angles, expanding the limit of decentralization, encouraging connections, empowering new exchange models, and permitting self-sufficient coordination of the gadgets. The paper aims to provide ideas about Blockchain’s structure and activity and, for the most part, to examine how this innovation is used to provide security and protection in IoT
A Research For Tracking Overspeeding Vehicles

In this paper, we proposed an idea to estimate the speed of the vehicle and track over the speeding vehicle. We use two sensors one at the initial point and the other at the tracking point. When the sensor senses the moving vehicle it captures the image and a time recorder will record the time. We will compare the two frames captured at the two points if the frames match we estimate the time. If the estimated time is less than initially fixed time-limit then the vehicle is considered to be over speeded and will track that vehicle.
Principles of Kabir Wealth Curve&lt;strong&gt; &lt;/strong&gt;

The authors developed a wealth curve (bell curve) that can predict a group of individual&amp;rsquo;s wealth based on the crossover interaction effect of the average intelligence quotient (one's ability to perform, comprehend and learn) and emotional awareness (emotional ability to recognize and make sense of emotions). To move towards the right on the X-axis of the Kabir wealth curve (e.g. accumulate more wealth), individuals have to improve emotional awareness and choose a professional career path that lands higher income. Similarly, those facing social injustice can accumulate more wealth by improving emotional awareness, which will help them navigate challenging environments.
Peningkatan Literasi Digital Era New Normal: Studi Kasus Pembelajaran Daring Mahasiswa Akuntansi UPN Veteran Jawa Timur

Abstract The rapid development of ICT and the digital world has changed many things. Education in the new normal era must innovate to integrate ICT. This study aims to determine the digital literacy competence of Accounting students FEB UPN Veteran East Java; and Formulating strategies to improve digital literacy competencies for Accounting students of FEB UPN Veterans East Java. In addition to digital infrastructure, it is necessary to design learning models such as curriculum that is integrated with digital literacy (Stein and Graham, 2014). European Commission Digital Competency Framework 2.1 (Carretero, Vuorikari &amp; Punie, 2018), covers five aspects, namely information/data literacy; communication/collaboration; digital content creation; security; and problem solving. This research method uses mixed methods (survey/interview). Quantitative and qualitative data analysis. The results showed that from the five aspects of digital literacy competence, Accounting students of FEB UPN Veteran Jatim were categorized both in the aspects of Information/data literacy and Communication/collaboration. Next is the aspect of creating digital content; Security; and Troubleshooting, need improvement. Strategies to improve digital literacy competence are to direct students to: think critically; using digital media; manage online identity; managing digital distractions; digital experience practice; and get out of your comfort zone.
Risk Preferences and Risk Perception Affect the Acceptance of Digital Contact Tracing

Digital contact-tracing applications (DCTAs) can control the spread of epidemics, like the COVID-19 pandemic. But people in Western societies fail to accept DCTAs. Understanding the low acceptance is key to policymakers who support DCTAs to avoid harsh nationwide lock-downs. In a preregistered study in a representative Swiss sample(N=757), we compare the role of individual risk perception, risk preferences, social preferences, and social values in the acceptance of and compliance with DCTA. The results show a low acceptance of DCTAs but high compliance with the measures recommended by DCTAs. Risk preferences and perceptions, but not social preferences, influenced accepting DCTAs; a high health risk perception and a low data-security risk perception increased acceptance. Additionally, supporting political measures, technical abilities, and understanding the DCTA functionality had large effects on accepting DCTAs. Therefore, we recommend highlighting personal health risks and clearly explaining DCTAs, focusing on data security, to enhance DCTA acceptance.
Welcome to the September Issue [From the Editor]

Welcome to the September 2021 issue of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">IEEE Geoscience and Remote Sensing Magazine</i> ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">GRSM</i> )! We have a number of feature articles in this issue, covering topics ranging from a tutorial on synthetic aperture radar (SAR) beamforming, to a review of the Earth-observation constellation, to several articles on techniques for processing various types of remote sensing data. These will be followed by a report on our annual International Geoscience and Remote Sensing Symposium (IGARSS) conference, held virtually this year. Finally, a few of our regular columns will update you on the activities of our members and Chapters throughout the world.
A Novel Zero-Watermarking Scheme Based on NSCT-SVD and Blockchain for Video Copyright

Abstract With the advent of information era, issues about video copyright continue to emerge. In the grey industrial chain of piracy, the film industry is a major disaster area so far. The current protection schemes for video copyright are inefficient and costly so that video industry still has to face the infringement. Research on a simple and efficient protection technology of video copyright is urgent. To address the inefficiency and irregularity of the current protection schemes for video copyright, this paper proposes a simple and efficient protection scheme for video copyright based on zero-watermarking and blockchain. The results show that the proposed key-frames extraction method of proposed scheme performs well and achieves low-cost protection of video copyright in pratical environment. In addition, video zero-watermarking algorithm of proposed scheme works well with blockchain. Proposed scheme improves some extent on the database centralization and evidential difficulties of traditional video zero-watermarking schemes, and it is more reliable, simpler and more effective than traditional video zero-watermarking schemes.
INCREASING WRITING SKILLS FOR PBSI STUDENTS' SCIENTIFIC WRITINGS WITH THE JIGSAW MODEL IN 2020/2021

This research aims as a step to improve learning outcomes of students' scientific writing skills through the Jigsaw model. This research is motivated by the lack of knowledge and abilities of early level students in writing scientific papers, especially papers. Research data collection was carried out with a test instrument. The population taken was 34 Indonesian Language Study Program students. The initial design of the study was carried out using pre-tests. The treatment is done by using the Jigsaw model. To find out the results of the treatment, posttest was given. The method used in this research is classroom action research, where class action research is carried out using only one treatment cycle. Based on the results of the study stated that learning outcomes by applying the Jigsaw model can improve learning outcomes writing skills scientific paper papers. The results obtained from the average pretest of 70.25 compared with the average posttest results was 85.5. These results indicate that there is a significant improvement using the application of Jigsaw learning models. Learning that applies the Jigsaw model can be used for students more active in learning.
Model independence

Particle physicists are planning the successor to CERN’s Large Hadron Collider – but how will they deal with the deluge of data from a future machine and the proliferation of theoretical models? Michela Massimi explains why a new scientific methodology called “model independence” could hold the answer
Gold deposits in the Earth's history

The distribution of the main gold deposits in the history of the Earth is considered. Primary heterogeneity of the Archean crust by gold bearing is shown. The main gold ore metallogenic epochs are characterized. Links of gold deposits with VMS and Cu-Ni in the early periods of the Earth (Archaean-Proterozoic) and, in addition, with deposits of W, Mo, Cu, Sb, Hg and Sn in the Phanerozoic are shown. An analysis of the distribution of mineralogical and geochemical types of the actual Au mineralization also showed significant diversity for the Phanerozoic compared with Precambrian. These data reflect the mantle-crustal origin of Au mineralization as a whole and indicates an increase in the contribution of the crust matter to the balance of Au mineralization with the age of the Earth. The well-known interruption in the formation of Au deposits (1.70.8 billion years) was discussed, which was caused by the stable craton regime of the long-existing Columbia (Nuna) Rodinia supercontinent.
An Effective Systemfor Storing Data and Resources using Cloud Computing

Because the orbited enrolling development makes amidst the most recent decade, redistributing facts to cloud relationship for cause of limit changes into a surprising perspective, which positive situations in sparing undertakings on noteworthy data upkeep and the board. Regardless, because the redistributed appropriated placing away isn't simply strong, it raises security stacks at the most succesful procedure to see statistics deduplication in cloud at the same time as reaching constancy assessing. In this paintings, we spin round the issue of secure goodness analyzing on cloud statistics. Specifically, going for conducting the two facts stability and deduplication in cloud, we advocatecozy systems, unequivocally SecCloud and SecCloud+. SecCloud provides a looking with an assistance of a MapReduce cloud, which empowers customers to make facts stamps earlier than shifting equivalently as audit the uprightness of data having been checked in cloud. Separated and beyond work, the estimation by customer in SecCloud is fantastically faded amidst the record trading and taking a gander at stages.
A Fuzzy Brain Emotional Learning Classifier Design and Application in Medical Diagnosis

This paper aims to propose a fuzzy brain emotional learning classifier and applies it to medical diagnosis.To improve the generalization and learning ability, this classifier is combined with a fuzzy inference system and a brain emotional learning model.Meanwhile, different from a brain emotional learning controller, a novel definition of the reward signal is developed, which is more suitable for classification.In addition, a stable convergence is guaranteed by utilizing the Lyapunov stability theorem.Finally, the proposed method is applied for the leukemia classification and the diagnosis of heart disease.A comparison between the proposed method with other algorithms shows that this proposed classifier can be viewed as an efficient way to implement medical decision and diagnosis.
A Case Study of 5S Implementation in Inspection Process

5S is a lean tool which involves workplace organization and is implemented to reduce the searching time of aproduct.The methodology adopted in this paper is the 5S pillar approach: Seiri, Seiton, Seiso, Seiketsu, Shitsuke to increase the overall efficiency of the process.The result of implementation of each step of the 5S methodology at XYZ Limited is also shown in this paper. The 5S methodology is applied to solve the problems in inspection department of the forging industry producing several crankshafts with the aim to eliminate losses in the company. The existing problem of the company is dealt with is messy tool setting, bad working environment and inefficient process flow. The company cannot meet customer's demand and works inefficiently, because everyone in the company is not used to a clean working environment and all inventory interrupts the process flow; therefore the major objective of this study is to help company not only to rearrange but also reset the working environment and enhance the process flow by using 5Stools.After implementing of 5S in the inspection department the time saving is 39.60% and also certain process wastes are reduced.The inspection department in the workplace became neat and effective.