Reviewerly/exHarmony huggingface dataset:
A Novel Image Clustering Algorithm Based on Supported Nearest Neighbors

Unsupervised image clustering is a challenging task in computer vision. Recently, various deep clustering algorithms based on contrastive learning have achieved promising performance and some distinguishable features representation were obtained only by taking different augmented views of same image as positive pairs and maximizing their similarities, whereas taking other images’ augmentations in the same batch as negative pairs and minimizing their similarities. However, due to the fact that there is more than one image in a batch belong to the same class, simply pushing the negative instances apart will result in inter-class conflictions and lead to the clustering performance degradation. In order to solve this problem, we propose a deep clustering algorithm based on supported nearest neighbors (SNDC), which constructs positive pairs of current images by maintaining a support set and find its k nearest neighbors from the support set. By going beyond single instance positive, SNDC can learn more generalized features representation with inherent semantic meaning and therefore alleviating inter-class conflictions. Experimental results on multiple benchmark datasets show that the performance of SNDC is superior to the state-of-the-art clustering models, with accuracy improvement of 6.2% and 20.5% on CIFAR-10 and ImageNet-Dogs respectively.
Research on the application of antiartificial intelligence in the military field

Military intelligence needs to be more rigorous and accurate than the application of artificial intelligence in daily production and life. This chapter introduces antiartificial intelligence technology. Artificial intelligence is a new technical science that researches and develops theories, methods, technologies, and application systems for simulating, extending, and expanding human intelligence. Antiartificial intelligence is the theory, method, and technology that can counter the opponent's artificial intelligence algorithm and equipment from the angles of data, algorithm, and hardware under the condition of human-machine cooperation. Antiartificial intelligence includes disabling the artificial intelligence of the opponents, misleading their artificial intelligence, obtaining their real intention of the artificial intelligence, and even carrying out counterattack.
The essence of intelligence is not data, algorithms, computing power, or knowledge

This chapter expounds the views on the essence of intelligence, explains the key difficulties in the current research of man-machine hybrid intelligence, and introduces the difficulties encountered in the application of artificial intelligence in the landing process and the side effects in the scene of using artificial intelligence. Finally, some examples of man-machine combat are summarized, and some suggestions are put forward for human pilots.
The essence of intelligence

This chapter introduces the different understanding and practice of intelligence caused by the differences between Eastern and Western cultures. By summarizing the past and present life of intelligence, this chapter combs the important technical viewpoints and academic schools in the development mileage of artificial intelligence. At the end of this chapter, the shortcomings of current AI are put forward, and the new development of AI technology in the future is prospected.
Deep situation awareness

This chapter introduces the origin of situational awareness, explains the three-level model of situational awareness, and puts forward a further concept of deep situation. The deep situation awareness is “the perception of situation awareness, which is a kind of human-machine intelligence, combining both human intelligence and machine intelligence.” It refers to a property (referring, feeling) and is related to the relationship between them (referred, perception). It can understand the original meaning, but also understand the overtones. It is a kind of expectation-selection-prediction-control system with information correction with autonomous and automatic aggregation effects and compensation, featured with both self-organization, self-adaptation and other organization, mutual adaptation, both partial quantitative calculation and prediction and global qualitative calculation and evaluation awareness.
NEURONAL PLASTICITY AS A PREVENTION TO ALZHEIMER'S DISEASE: AN INTEGRATIVE REVIEW

Introduction: Neuronal plasticity is the brain's ability to perform activities and readapt itself from a stimulus caused by the external environment. Related to that, understands that with the human aging process, the organism tends to develop diseases, amongst them, those involving the cognitive processes, in case, like the Alzheimer´s Disease. Therefore, this work have the objective of discuss the importance of the neuronal plasticity and your relation with the Alzheimer’s Disease. Method: An integrative review was made in order to analyze the available studies on SciElo, PubMed, VHL and SciVerse Scopus databases, from the neuronal plasticity, memory and Alzheimer descriptors. Articles in Portuguese and English languages were used, with the publication period between the years 2000 and 2020. Results: Two of the three studies about the inclusion criteria reported positive results with relation to the clinical condition, mood, learning and memorization of the elderly subjected to the realization of activities that stimulate the neuronal plasticity, so that stimulate the brain, memorize, learn or relearn something new. For that, was introduced to the patients’ routine the involvement of repeated practice of tasks like games performed on the computer, the psychoeducation, beyond varied techniques of behavior changes and lifestyle, incorporating cognitive interventions with the aid of physical exercises. The last study used did not show any significant results that demonstrated the effectiveness of intervention in multiple domains and health counseling in the development of neuronal plasticity in the studied groups. Conclusion: With the present article, was possible conclude that stimulate the brain for new activities provokes the stimulation of synapses on the memorization and learn processes, contributing with the prevention of the onset of Alzheimer’s Disease.&#x0D; Keywords: Neuronal plasticity. Memory. Alzheimer.
A Knowledge Graph Link Prediction Model with Combined 1D and 2D Convolutional Embeddings

Traditional knowledge graph link prediction models use translation operations to obtain shallow knowledge of entities and relations, and some models utilize convolutional neural networks to extract nonlinear structures and deep knowledge of entities and relations. Linear translation models cannot mine and model deep and potential knowledge, while nonlinear convolutional neural network models give rise to the loss of most of the shallow knowledge. This paper proposes the 1D and 2D convolutional combined embedding model CombE to relieve these problems effectively. In our method, we leverage 2D convolution operations to facilitate the interaction between entities and relations to capture the potential knowledge. In order to enable total fusion of element-level embeddings, we perform vector multiplication operations on entity and relation embeddings to generate a 2D matrix. In addition, we use some 1D convolution filters over input embeddings to capture the surface and shallow knowledge. Finally, we add the results obtained from the two parts element-wise and save them. Experiments show that our method is superior to other recent methods.
S. A. PODOLINSKYI IN THE ENERGETIC INTERPRETATION OF THE EVOLUTION OF NATURE AND SOCIETY

Serhii Andriyovych Podolinskyi (1850—1891) — a researcher of nature, natural philosopher, doctor, public figure and publicist, lived a short life. Still with the main works of S. A. Podolynskyi is almost unknown to the scientific community. Great Ukrainian scientist V. I. Vernadskyi was inspired by the scientific works and ideas of S. A. Podolinskyi. And the characteristics of S. A. Podolinskyi as a “forgotten scientific innovator”, which was given to him by V. I. Vernadskyi at the beginning of the 20th century, remains largely fair even today. The article was prepared for the 150th anniversary of the “energy concept” of S. A. Podolinskyi and dedicated to the history of his work “Work and its relationship to the distribution of energy” (1880). A number of issues of the distribution of solar energy in the universe are covered. The data on the value of S. A. Podolinskyi in the energetic interpretation of the development of nature and society. Analysis of each section of the article by S. A. Podolinskyi in the context of the impact of work on the distribution of solar energy on the Earth’s surface. Ideas of S. A. Podolinskyi, presented in his work “Man’s work and its attitude to the distribution of energy” testify not only to the priority of domestic science on many issues of natural science, the relevance of which is realized only in our time, but also retain methodological value in the world context. In the work of S. A. Podolinskyi’s reader will find an example of the formulation and approach to solving an interesting and necessary problem in the scientific field, which are characteristic of outstanding and original scientists. The most important is the opening of S. A. Podolinskyi that the development of living organisms on the Earth’s surface occurs under the influence of solar energy. That is why the name S. A. Podolynskyi is deservedly mentioned among the predecessors of V. I. Vernadskyi, who studied the energetics of living matter and the formation of the doctrine of the biosphere and noosphere. The importance of the work of S. A. Podolinskyi is considered and its further prospects in the development of scientific research on the use of energy.
Create Inclusive Content with Accessibility Tools

Women in Higher EducationVolume 32, Issue 2 p. 12-12 Accessibility Tools Create Inclusive Content with Accessibility Tools Donna Talarico, Donna TalaricoSearch for more papers by this author Donna Talarico, Donna TalaricoSearch for more papers by this author First published: 08 February 2023 https://doi.org/10.1002/whe.21245Read 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 onEmailFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume32, Issue2February 2023Pages 12-12 RelatedInformation
Generation of 8 × 8 S-boxes using 4 × 4 optimal S-boxes

Substitution boxes (S-boxes) have a very important role in the recent developments of block ciphers as it provides the nonlinearity for the ciphers. To resist different kinds of attacks, S-boxes must be constructed very cautiously. There are some schemes which are known to design S-boxes, interestingly these are based on evolutionary heuristics. In this paper, we have proposed a new approach for the construction of 8 × 8 S-boxes from the existing 4 × 4 S-boxes. We have used these 4 × 4 S-boxes in the design because of their good cryptographic properties. Evaluation of the proposed S-boxes properties is done by the SET Tool fa toolbox for S-box analysisg (Picek et al., 2014) and compared them with the S-boxes of mCrypton, Twofish, Kalynapi1, MD and Safer ciphers. The results show that the S-box generated by our approach has good cryptographic properties and these S-boxes can be used as one primitive for data encryption.
Review on Pathology of Blood and Blood Related Diseases

Clinical pathology is a field of study through which we diagnose and analyze disease and disorders using tissues of our body and fluids produced by human body. It requires knowledge in many fields like biochemistry, microbiology, hematology and etc. It is a very crucial in the medical field as it is most often the primary step in treating a patient. As it gives information an identification of the disease the patient is suffering from and take the necessary protocols to treat him efficiently. The tests done are performed in a lab or a medical center. The tests usually require a wide array of equipment and chemicals. The tests are carried out by trained professionals who can use the equipment correctly to produce accurate test results. There are many divisions of clinical pathology some of are 1. Chemical pathology 2. Immunopathology 3. Clinical microbiology 4. Hematopathology.
Perancangan Sistem Informasi Stok Barang di Gudang Toko Viola Berbasis Website

Viola shop is a wholesale and retail store in Salawati that offers a variety of products in the form of basic necessities, stationery, handyman equipment and so on. The purpose of this research is to design a website and a guidebook for the stock information system at the Viola Store Warehouse. The type of research used is research and development and the development model used is the prototype model. The trials used were blackbox trials and field trials. The subjects of this research are warehouse officers, shop owners, 3 students and 7 customers or the public. Based on the results of the research on designing a stock information system at the Viola Store Warehouse, the results of expert validation obtained very good conclusions, therefore researchers could conduct field trials to respondents. The results of field trials with the assessment of system quality aspects get an average of 3.6 percentages of 90% and get very good conclusions, navigation aspects get an average of 3.4 percentages of 84% and get very good conclusions, and aspects of user satisfaction get an average average 3.8 percentage 95% and get a very good conclusion. The ease of understanding the guidebook by the respondents got an average score of 3.8 and a percentage of 94% with a very good conclusion. The results of this study indicate that the design of an inventory information system at the Viola Store Warehouse based website and guidebook is feasible to use
Perancangan Desain Sistem Basis Data Pengelolaan Aset

Galuh University is a private university that has 7 faculties, 1 Postgraduate Program, Institute for Research and Community Service (LPPM), Internal Quality Assurance Agency (BPMI), Libraries and Cooperation Offices. Of the many places in Galuh University, it becomes a problem that must be faced in asset management. The management of these assets still relies on the role of humans who cannot collect a lot of asset data. If the person forgets it will be a problem especially regarding the type of asset that makes the payment and if it is late, it will be subject to sanctions or fines. This research is to make it easier to calculate the number of assets and record the maintenance of these assets. This asset management application will be web-based using the PHP programming language and MySQL as the database. The results of this study are in the form of a database design which will later be implemented on a website that can be accessed by asset managers who will record asset maintenance and also as a reminder of asset maintenance at Galuh University
Overview of Cryptography

Until very recently, the term "cryptography" was almost always used to refer to "encryption," which is the act of transforming plaintext or conventional information into an unintelligible form (called cipher text). Decryption is the opposite, or the process of returning plaintext from the unintelligible cipher text. The encryption and reversing decryption operations are carried out by a pair of algorithms known as cyphers (or cyphers). The algorithm and, in each case, a "key" work together just to regulate the precise operation of a cypher. The key, which is required to decrypt the cipher text, is a secret that should ideally only be known by the communicants. It typically takes the form of a short string of characters that the user can remember. A "cryptosystem" is the ordered list of elements with a finite number of potential combinations in formal mathematics.
Enhancing the depth perception of DSA images with 2D–3D registration

Today, cerebrovascular disease has become an important health hazard. Therefore, it is necessary to perform a more accurate and less time-consuming registration of preoperative three-dimensional (3D) images and intraoperative two-dimensional (2D) projection images which is very important for conducting cerebrovascular disease interventions. The 2D-3D registration method proposed in this study is designed to solve the problems of long registration time and large registration errors in 3D computed tomography angiography (CTA) images and 2D digital subtraction angiography (DSA) images.To make a more comprehensive and active diagnosis, treatment and surgery plan for patients with cerebrovascular diseases, we propose a weighted similarity measure function, the normalized mutual information-gradient difference (NMG), which can evaluate the 2D-3D registration results. Then, using a multi-resolution fusion optimization strategy, the multi-resolution fused regular step gradient descent optimization (MR-RSGD) method is presented to attain the optimal value of the registration results in the process of the optimization algorithm.In this study, we adopt two datasets of the brain vessels to validate and obtain similarity metric values which are 0.0037 and 0.0003, respectively. Using the registration method proposed in this study, the time taken for the experiment was calculated to be 56.55s and 50.8070s, respectively, for the two sets of data. The results show that the registration methods proposed in this study are both better than the Normalized Mutual (NM) and Normalized Mutual Information (NMI).The experimental results in this study show that in the 2D-3D registration process, to evaluate the registration results more accurately, we can use the similarity metric function containing the image gray information and spatial information. To improve the efficiency of the registration process, we can choose the algorithm with gradient optimization strategy. Our method has great potential to be applied in practical interventional treatment for intuitive 3D navigation.
Expert System for Diagnostic Damage to Motorcycle Cvt Using Website Based Forward Chaining Method

Over time, many people who previously did not use automatic motorbikes turned to automatic motorbike users because the way they were used was very easy and different from other types of motorbikes. Behind the easy way of using it, there are many problems that arise in automatic motor components, especially on the CVT. Not everyone understands the problem with the CVT. Some users prefer to take their motorbikes to both official and non-official workshops. So the development of an expert system, is a computer science that works like an expert. Forward Chaining method, a forward search method that begins with a fact will later produce a conclusion. The results show that an expert system for diagnosing automatic motorcycle damage using the forward chaining method helps users anticipate damage so that there will be no greater and sustainable damage.
Genetic Algorithm Based Optimization in Solving Multi Robot Task Allocation Problems

As the world moves on in the direction of automated production lines and advanced robotics, there is a need to solve the problems of task allocation to robots to maximize efficiency based on parameters that change from situation to situation. This paper imparted knowledge on basic-intermediate problem-solving techniques to solve problems in the MRTA category. Problems we need to solve are decisions to make or tasks to complete. The Framework of making decisions based on existing data falls under Artificial Intelligence. While the second part of doing tasks comes under the Framework of Robot Process Automation, for which machines already know what to do (Programmed), But need user input as to where to go to do the tasks in question. The purpose of this work is to learn about the different types of problems and how to solve them in the best possible way. This work implemented mixed linear programming with saving matrix methodology that minimized the total distance and path of robots in coordinating the robot environment, thus minimizing the idleness of the robot.
Cognitive aging and combined interventions: self-efficiency as a device to improve brain function

Cerebral neurodegeneration may be associated with functional changes, being able to generate cognitive decline, a decrease in the skills that make up brain function. The main objective of this study is to evaluate how self-efficacy belief, personal development and mood states are related to neurocognitive aging. The present study is based on the quasi-experimental and longitudinal development model. The study sample consisted of 33 elderly people with a mean age of 71 years (SD = ± 6.32), spaced from 61 to 89 years of age. Six instruments were applied for data collection, namely: Sociodemographic Data Sheet, Addenbrooke Cognitive Examination, Personal Development Scale, General Self-Efficacy Scale - Revised Version, Geriatrics Depression Scale and Beck Anxiety Scale. Statistical normality tests were used at a significance level of 5% (p ≤ 0.05). Regarding the results, the sample is statistically significant in relation to four variables, namely: memory (p = 0.00), verbal fluency (p = 0.00), cognition (p = 0.00) and self-efficacy (p = 0.00); moreover, from the difference between groups related to cognitive interventions (Stimullus + MEMO), based on the self-efficacy construct, for example, it is possible to notice that the self-efficacy variable (p = 0.03) manifests statistical significance. It is concluded that the sense of perceived efficacy can be used as a device to mediate neurocognitive gains, being able to improve brain function, supported by combined interventions.
HC-Net: A hybrid convolutional network for non-human primate brain extraction

Brain extraction (skull stripping) is an essential step in the magnetic resonance imaging (MRI) analysis of brain sciences. However, most of the current brain extraction methods that achieve satisfactory results for human brains are often challenged by non-human primate brains. Due to the small sample characteristics and the nature of thick-slice scanning of macaque MRI data, traditional deep convolutional neural networks (DCNNs) are unable to obtain excellent results. To overcome this challenge, this study proposed a symmetrical end-to-end trainable hybrid convolutional neural network (HC-Net). It makes full use of the spatial information between adjacent slices of the MRI image sequence and combines three consecutive slices from three axes for 3D convolutions, which reduces the calculation consumption and promotes accuracy. The HC-Net consists of encoding and decoding structures of 3D convolutions and 2D convolutions in series. The effective use of 2D convolutions and 3D convolutions relieves the underfitting of 2D convolutions to spatial features and the overfitting of 3D convolutions to small samples. After evaluating macaque brain data from different sites, the results showed that HC-Net performed better in inference time (approximately 13 s per volume) and accuracy (mean Dice coefficient reached 95.46%). The HC-Net model also had good generalization ability and stability in different modes of brain extraction tasks.