Reviewerly/exHarmony huggingface dataset:
Toward Latent Cognizance on Open-Set Recognition

Open-Set Recognition (OSR) has been actively studied recently. It attempts to address a closed-set paradigm of conventional object recognition. Most OSR approaches are quite analytic and retrospective, associable to human’s system-2 decision. A novel bayesian-based approach Latent Cognizance (LC), derived from a new probabilistic interpretation of softmax output, is more similar to natural impulse response and more associable to system-1 decision. As both decision systems are crucial for human survival, both OSR approaches may play their roles in development of machine intelligence. Although the new softmax interpretation is theoretically sound and has been experimentally verified, many progressive assumptions underlying LC have not been directly examined. Our study clarifies those assumptions and directly examines them. The assumptions are laid out and tested in a refining manner. The investigation employs AlexNet and VGG as well as ImageNet and Cifar-100 datasets. Our findings support the existence of the common cognizance function, but the evidence is against generality of a common cognizance function across base models or application domains.
Conquering the challenge of quantum optimization

Hyped as the solution to many problems – both hard and easy – quantum-enhanced optimization is a burgeoning research field. But with untrainable circuits, “barren plateaus” and deceptive local minimas, nature itself may prevent the use of quantum solutions for hard problems, as Pradeep Niroula explains.
Protection Guidelines for Blockchain Based Digital Identity

Digital identity provides mechanisms for personally identifying information (PII) to be asserted and verified in digital services and transactions. To utilize the full potential of digital identity in to enable personalized services and efficient transactions, blockchain technology is being proposed as the means to achieve the holy grail. While it certainly has promise, the growing number of threats on the blockchain ecosystem and the traditional identity management system call for a systematic approach towards securing the identity management based on blockchains. We study the existing attacks and the known vulnerabilities and the possible hypothetical attacks which might get executed via these vulnerabilities. We analyze these attack scenarios with respect to the attacker’s costs and benefits and the defender’s mitigation costs and damages. Finally, we propose design considerations for the architects towards securing their implementation of the blockchain based digital identity systems.
Research on application of image ranging technology in geotechnical test

In order to explore the application of image ranging technology in geotechnical test, taking simple shear test as an example, the deformation measurement method of root-soil composite was studied, and the concrete realization steps and optimization measures of image ranging technology were described. Through comparative analysis, the results show that the image ranging technology can better monitor the law of shear deformation of shear boxes, and the error is basically controlled within 10%. The research results can further enrich the displacement monitoring methods of laboratory model tests.
Technical Aspects of Sentiment Analysis of Online News Sources

While the theoretical foundations for this thesis mainly come from the domains of business administration and economics—to be expected in a business administration thesis—the research in this project has made it necessary to develop extensive software packages, whose foundations are described in the following sections.
Wavelet domain self synchronization digital audio watermarking algorithm based on channel information

With the increasing piracy and infringement of digital audio media, the copyright protection of digital audio media has attracted more and more attention. Digital watermarking is an important means to solve the problem of audio media copyright protection. The digital watermarking applied to copyright protection requires high robustness. How to improve the anti attack ability of audio digital watermarking methods, especially the robustness of audio watermarking, has become an urgent problem to be solved. A wavelet domain self synchronization digital audio watermarking algorithm based on channel information is proposed. This algorithm is a blind detection algorithm, which does not need the original audio signal. The algorithm introduces the idea of coefficient mean quantization. After the audio signal is decomposed by wavelet, the low-frequency coefficients are mean quantized and watermarked. The idea of embedding synchronization signal is introduced, and the embedding position of watermark is located by using synchronization signal to resist attacks such as translation and cropping. Experimental results show that the algorithm has strong robustness and anti-attack.
Implementing an Arabic Question Answering System Using Conceptual Graphs

Semantic representation of texts is very useful for several applications, such as question answering. In this paper, we use the conceptual graph formalism to represent text contents. This representation is shown to be a useful intermediate step for question answering in Arabic language.
Gentueri Viral Transport Medium

Biomedical Safety & Standards: April 01, 2022 - Volume 52 - Issue 6 - p 47 doi: 10.1097/01.BMSAS.0000824396.36818.1b
A Parallelized Qubit Mapping Algorithm for Large-scale Quantum Circuits

Quantum computers are superior to existing classical supercomputers in terms of run time for specific tasks, and various studies on quantum computers are in progress. Despite this, there is a significant gap in technology between available technologies and actual quantum computers on the noisy intermediate-scale quantum-scale. Currently, various quantum algorithms have been implemented and verified using quantum simulations. Therefore, the runtime performance of a quantum circuit can be verified in the same environment as a real quantum machine. A quantum compiler compiles quantum circuits. When a quantum circuit is compiled, logical qubits in a quantum circuit should be mapped to physical qubits, called qubit mapping. As qubit mapping is an NP-Complete problem, the compilation time increases exponentially according to the number of qubits. Therefore, various studies on effective qubit mapping techniques have been developed to accelerate the execution time. This paper proposes a new parallelized Qubit mapping algorithm. The proposed method consists of three-step processes: one circuit is divided into several circuits; the SABRE enhanced algorithm is executed on each circuit in parallel and then merged. The performance was evaluated using 10 benchmarks. The experimental results revealed an acceleration of up to 6.42x and an average speed up of 4.8x, with an average overhead of 1.03x in terms of the number of gates obtained. The proposed method outperformed the well-known modern qubit-mapping algorithm in terms of the execution time with exponential speedup improvement.
Consolidation Success Story

Journal AWWAVolume 114, Issue 2 p. 5-5 Departments Consolidation Success Story First published: 04 March 2022 https://doi.org/10.1002/awwa.1859Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume114, Issue2March 2022Pages 5-5 RelatedInformation
The Relationship Between Self-Regulated Learning and Academic Achievement on the College Students of Universitas Muhammadiyah Sidoarjo, Indonesia

This study aims to determine the relationship between self-regulated learning and academic achievement of students of the Madrasah Ibtidaiyah Teacher Education Study Program, Faculty of Islamic Religion, University of Muhammadiyah Sidoarjo. The type of research used in this study is a quantitative method with a correlational approach. The variables in this study are self-regulated learning as the independent variable and academic achievement as the dependent variable. The population in this study were 108 students. The author uses the method of issac and michael with a level of 5% so that the total population that is used as a sample according to the issac and michael table is 84 students. The sampling technique used is stratified random sampling. Data collection uses a Likert model scale, namely the self-regulated learning scale. And use the cumulative grade point average or GPA to see student academic achievement. Analysis of the research data using correlation techniques using SPSS 25 for windows. The analysis in this study obtained a correlation coefficient of rxy = 0.376 which has a significance value of 0.000, which means that there is a positive relationship between self-regulated learning and academic achievement. It can be concluded that the higher the self-regulated learning, the higher the academic achievement of the students of the Madrasah Ibtidaiyah Teacher Education Study Program, the Faculty of Islamic Religion, University of Muhammadiyah Sidoarjo, with an effect magnitude of 42.7%. Keywords: Self regulated learning, Academic Achievement, Students, PGMI
SailFish Optimizer Algorithm to Solve the Traveling Salesman Problem

The traveling Salesman Problem is NP-hard and a well-known problem in combinatorial research. In order to find the right solution, the best-known methods are to make a list of all possible solutions, but the disadvantage of this method is that the resolution time becomes excessively long. To deal with these obstacles, researchers are working on a new methods class named meta-heuristic, to try solving a wider range of these unresolved problems. A recent one called Sailfish optimizer algorithm (SFO), which is inspired by nature, in particular based on the behavior of sailfish hunting. In this work, we present a first adaption of this algorithm for discrete case and especially to resolve travelling salesman problem, the obtained results show the efficiency of the proposed adaptation to solve some instances of this problem and the results was compared with other metaheuristics methods.
Testing Prospects' Readiness

The Major Gifts ReportVolume 24, Issue 4 p. 6-6 Articles Testing Prospects' Readiness First published: 02 March 2022 https://doi.org/10.1002/mgr.31901Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume24, Issue4April 2022Pages 6-6 RelatedInformation
CUDA-OpenGL GPU-based real time beam tracking by MEMS phase SLM

CUDA-OpenGL interoperability enables to drastically reduce the computational time for CGH calculation and display on Spatial Light Modulators via HDMI display channel. The fast calculation method enables on-the-fly diffractive beam steering by Micro Electro Mechanical System based phase light modulator with YOLOv4-tiny model based object recognition to do AI-based dynamic beam tracking in order to trace the object of interest.
Personal Digital Health Assistants

Personal Digital Health Assistants (PDHA) are applications that can run on a computer or mobile device. They acquires, stores, and analyzes health information and communicate with remote servers. They are utilized by patients or their caregivers. Many systems are available.
Unconscious Experience

The coming into being of psychic reality may be understood from the standpoint of a developmental monistic ontology whereby there is a progressive unfolding of desire into an organizing and unifying process system we equate with the unconscious ego as an impersonal executive-synthetic agency. This agency is merely formal, hence it is not a personal agent or subject in any proper sense, which is commonly ascribed to human consciousness or selfhood. The unconscious abyss is initially immersed in its own corporeal sentient embodiment and awakens as appetitive motivational longing, its initial being-in-relation-to-lack. The abyss erupts from its self-enclosed original unity as pulsional desire. Such desirous rupture is in response to feeling its need, urge, or craving to experience and satiate the lack, which takes various initial forms that eventually breach into consciousness as ego proper. Originally, desire takes itself as its initial object through a form of pre-reflective self-consciousness the author refers to as unconscious apperception, the pure experiential self-sense belonging to precognitive unconscious thought. The development of unconscious subjectivity ultimately follows an organic process based on a series of dialectical mediations beginning as unconscious apperception and culminating in self-conscious reflection, the sublated domain of conscious human experience. Yet this initial rudimentary process of desirous rupture and apperception constitutes the birth of the human psyche, for mind is an epigenetic, architectonic self-organizing achievement expressed as a dynamic, self-articulated complex totality or psychic holism. Unconscious mind is a series of spacings that first instantiate themselves as a multitude of schemata, which are the building blocks of psychic reality. A schema is a desirous-apperceptive-ideational unit of self-experience that is teleologically oriented and dialectically constituted. Schemata may be viewed as microagents with semi-autonomous powers of telic expression that operate as self-states as they create spacings within the unconscious. Schemata may take various forms, from the archaic to the refined, and instantiate themselves as somatic, sensuous, affective, perceptual, and conceptual (symbolic) orders within the psyche, each having their own intrinsic pressures, valences, intensities, intentional and defensive strategies, and unconscious qualia. It is here that the author wishes to offer a potential answer to the mind-body problem.
Cellular refractive index and thickness recovery via unsupervised learning framework.

This work presents an AI-driven framework to extract the biological tissue's refractive index and thickness maps from a single RGB image. This approach is based on a physical light-trapping surface and an unsupervised inverse search projector which projects given RGB pixel to the sample's refractive index and thickness at the corresponding coordinate.
Improved Interpolation-Based Reversible Audio Data Hiding Using Sample Dispersion and Value Shifting

Since the last decade, data transmission has kept developing faster than ever. With the support of online systems and mobile devices, the development of data transmission is also followed by up-to-date or newer applications. However, this development of data transmission is not without risk. Many users are still negligent in maintaining their data privacy, leading to disclosing their private data. Therefore, data security is needed to ensure the safety of the private data being transmitted. Data hiding is one of the methods introduced in data security. In this research, private data are embedded inside an audio cover to be retrieved safely from the receiver. Nevertheless, the capacity of private data and the similarity level of embedded audio files become a significant problem. We focus on extending the capacity of private data by utilizing an interpolation-based approach and optimizing the similarity level by dispersing the embedding space and shifting the embedded value to be as close as possible to the original audio file. The experimental results show that this approach can obtain a similarity level of 103.5 dB when embedding 100 kb of data and fall to approximately 88.15 dB when embedding 300 kb of data.
Privacy Preservation Technique Based on Sensitivity Levels for Multiple Numerical Sensitive Overlapped Attributes

In today’s world, information is a hot topic to discuss and explore. We all strive to get more information and utilize it for advancement. Data is the main object to get information. Data is considered as a big data nowadays as it contains a massive amount of information. Knowing the benefits of knowledge does not mean an adversary cannot use the same information to harm an individual. Protecting data from the intrusion of an adversary can be done through Privacy Preserving Data Publishing Methods. When there is a combination of sensitive data in a data set that is correlated to each other, several models are not efficient for protecting data. We propose a novel model K-MNSSOA for preserving data privacy based on the concept of K-anonymity in this paper. An in-depth study of the K-MNSOA model for Privacy Preserving Data Publishing is presented in this article, which protects sensitive data privacy breaches even when the set of data has multiple overlapping sensitive numerical attributes. Using this model, levels of sensitivity are designed, and generalization is performed on overlapping attributes based on the sensitivity in sensitive attributes.
Compact entanglement sources for portable quantum information platforms

We discuss two novel entanglement sources utilizing spontaneous parametric downconversion in periodically poled waveguides. Using quasi-phase matched KTP crystals, we have demonstrated a post-selection-based polarization entangled degenerate source at 810 nm, as well as a post-selection-free non-degenerate collinear source producing entangled photons at 810 nm and 1550 nm. The sources exhibit high brightness and state quality – with the non-degenerate source achieving fidelities and purities up to 99% – with clear paths for further improvement. Furthermore, they are compact, stable, and need little alignment when set, critical for practical quantum communication and network applications. Lastly, their small size, weight, and power (SWaP) makes them an attractive option for mobile platforms, e.g., with drones or satellites.
A Comprehensive Evaluation of Cryptographic Ciphers on Secure Publish/Subscribe Communications for IoT Devices

The Internet of Things (IoT) is the concept of connecting the electronic objects we use in our daily lives to the Internet and allowing them to communicate with one another. These devices can collect a large amount of data, monitor objects, reduce workload, and boost efficiency by saving resources. All of these scenarios highlight the significance of security. Cryptography is an important aspect of information security in today’s society. Cryptography is the technique of transforming information and using codes to make encrypted conversations so that only the people for whom the information is intended are processed. Cryptographic algorithms can be used in a variety of ways. In an ideal world, a low-cost, high-performance encryption method would be needed. In our study, we applied and analyzed in detail the cost and performance of the widely used cryptographic algorithms 3DES, AES, Blowfish, CAST5, RC4, and RSA on Raspberry Pi 4 an IoT based devices to secure the publish/subscribe communication method used for the communication of these devices.
Coyote Optimization Algorithm with Linear Convergence for Global Numerical Optimization

In particular, the popularity of computational intelligence has accelerated the study of optimization. Coyote Optimization Algorithm (COA) is a new meta heuristic optimization. It is pays attention to the social structure and experience exchange of coyotes. In this paper, the coyote optimization algorithm with linear convergence (COALC) is proposed. In order to explore a huge search space in the pre-optimization stage and to avoid premature convergence, the convergence factor is also involved. Thus, the COALC will explore a huge search space in the early optimization stage to avoid premature convergence. Also, the small area is adopted in the later optimization stage to effectively refine the final solution, while simulating a coyote killed by a hunter in the environment. It can avoid the influence of bad solutions. In experiments, ten IEEE CEC2019 test functions is adopted. The results show that the proposed method has rapid convergence, and a better solution can be obtained in a limited time, so it has advantages compared with other related methods.
Accelerating the cloud with quantum

Azure Quantum. The power of Azure, accelerated by Quantum. This is the present and future of cloud computing. A quantum-classical compute fabric that holds the promise of helping to remake our global economy, by offering new capabilities to help solve some of our planet's biggest challenges--in energy, climate, agriculture, and health--and across a broad span of industrial sectors, including computational chemistry, materials science, and nuclear and particle physics. Quantum computers are accelerators to large-scale classical compute and receive instructions and cues from classical processors. The success of quantum computation requires seamless integration in a high-performance cloud, to enable hyperscale workloads with complex classical pre- and post-processing. It also requires scaling up; to achieve the full promise, we need a leadership-class quantum machine with more than 1M physical qubits. I'll share the types of problems such a quantum machine will accelerate in the cloud, and how you can program and develop towards these advances today with Azure Quantum. I'll also share how quantum ideas are being emulated to enhance classical solutions, enabling quantum impact right now. Welcome to the quantum era of computing.
Play Up the Importance of Your Mission Statement

Nonprofit Communications ReportVolume 20, Issue 4 p. 3-3 Educating the Public Play Up the Importance of Your Mission Statement First published: 03 March 2022 https://doi.org/10.1002/npcr.31916Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume20, Issue4April 2022Pages 3-3 RelatedInformation