Reviewerly/exHarmony huggingface dataset:
Pancreatic Neoplasm Image Translation Based on Feature Correlation Analysis of Cross-Phase Image

CT arterial phase images can provide a powerful auxiliary to formulate pancreatic neoplasm diagnosis and treatment plans. In the absence of such images, we can use the image translation model convert CT images of other phases into CT arterial phase synthetic images. Under the supervision of manual labeling by experts or pixel-level labeling, the model can achieve better performance. However, for pancreatic neoplasm image translation, such labels are usually scarce. In this regard, we use the easily obtained paired but unaligned cross-phase real pancreatic neoplasm images as labels and constructs a cross-phase image feature correlation analysis-based image translation method (CFCA-IT). This method analyzes the image feature correlation between the synthetic images and real images and takes it as the training constraint of the translation model. Simulation experiments show that CFCA-IT can further improve the translation performance of the five state-of-the-art translation models.
A High-Level Track Fusion Scheme for Circular Quantities

As sensors get more and more integrated, signal processing functions, like tracking, are performed closer to the sensor. Consequently, high level fusion is on the rise. Presented here is a high level fusion scheme incorporating not only linear,but circular quantities as well. Monte Carlo experiments are used to verify our novel fusion operators that work as a weighted average for the Wrapped Normal and the von-Mises distribution. To further verify the new fusion operators, we implemented a full track level fusion scheme and tested it by fusing the measurements of two RADAR sensors.
SDLC Security Framework for Software Startups

A major issue for software startup firms failing to develop strong security programs is that the perceived start-up price to hold it out. Secure software Development Life Cycle (SDLC) framework used for software developers, in saving the project cost throughout the first integration of design. As several developers advocate, software organizations usually adopt atop-down approach to implement secure SDLC methodologies. Interview was finished with developers within the software startups presently used in industry to explore real-life software security practices throughout every stage of the development lifecycle. The aim of the proposed framework is to assist developers in startups to explore real-life software security practices throughout every stage of the development lifecycle.
Contact tracing

As the pandemic progressed globally, the need for countries to localize and contain the spread of COVID-19 has increased. Digital technologies employed to develop contact tracing applications were designed to allow both government health authorities and citizens to be informed about infected cases and trace down the contacts of infected people to test for the virus.
Exploring the Nexus between the Right to be Forgotten v Data Retention Laws in Nigeria

More people are becoming concerned about the value and security of their personal data—this has fueled conversations on data protection and made the formulation of privacy legislation a global phenomenon. Most privacy legislation require data controllers to retain data for particular periods but also give data subjects the right to be 'forgotten'.But how can the seemingly opposing requirements to “forget” and “retain” data be balanced? Which takes precedence--the right to be forgotten or the right to retain data?
Applying the RPBK22 Technique for Secure the Generalized Data

Nowadays, data is extremely important in the people's world. Recently, people have generated more data using internet media. As a result, this internet data lacks adequate protection and hackers may simply access it. This research work utilizes the RBPK22 method to overcome the difficulty. There are seven stages to implement this method. To find the mystery prime key S; To find the X1 and X2 values from prime numbers; To find the $$\overline{X}_{1}$$ and $$\overline{X}_{2}$$ values; To find the standard deviation values with the help of Step 2 and Step 3; To exchange a and b esteems from left in a matrix; To locate the T-test values and pair them that numbers from left to right; To exchange the odd and even equation a and b in a given lattice. The RPBK22 strategy gives extraordinary security, while appearing differently with ChaCha technique.
Cryptographic Strain‐Dependent Light Pattern Generators (Adv. Mater. Technol. 1/2022)

Cryptographic Magic Windows In article number 2101129, Francesco Pisani, Andrea Camposeo, and colleagues introduce stretchable and 3D printed cryptographic magic windows capable of generating complex patterns, including micro-QR-codes, by refraction of light in the visible range. The information carried by a light pattern, that is encrypted in the 3D topography of the magic windows, is unveiled by projection of the light pattern on a screen.
The Problems with the Definition of Artifacts Material (Geologists’ Help for Archaeologists)

Often archaeologists may face difficulties determining the rock type from which prehistoric artifacts are made, even using microscopy and various analytical methods. To help archaeologists give the correct name of the rock, the article describes various types of rocks with an emphasis on their macroscopic features: color, structure, size of the constituent particles. Igneous rocks are characterized as plutonic (intrusive) as well as poured to the surface—volcanic (effusive). Rocks of various compositions such as ultrabasic, basic, medium, and acidic are described. In each group, rocks of volcanic and plutonic facies are distinguished. Macroscopically, volcanic rocks differ from plutonic rocks in the presence of volcanic glass and porphyry texture. The unevenly grained texture of plutonic rock differs from the porphyry texture of volcanic rock by the presence of larger crystals in the background of a full-grained or a fine matrix. Rocks with high silica content usually have a light color and consist mainly of leucocratic minerals. Also, they are distinguished by high hardness. Rocks of ultrabasic and basic composition are composed entirely of dark-colored minerals or contain a small amount of leucocratic minerals (main plagioclase for the normal series rocks). For sedimentary rocks, their division by particle-size distribution and roundness degree is given. Macroscopically, they are usually characterized by a layered structure. A large section is devoted to siliceous rocks, which in ancient times were used for various purposes; visually they differ well by structural and textural features. For their full characterization, chemical analysis has been made. Photos of various types of rocks and their description are given. To diagnose rocks in the field, we use data obtained in the laboratory during a detailed study of them in thin sections and polished sections.
Native Hawaiian Library Services Grants (IMLS)

Federal Grants & ContractsVolume 46, Issue 4 p. 1-2 Grants alerts Native Hawaiian Library Services Grants (IMLS) First published: 17 January 2022 https://doi.org/10.1002/fgc.32156Read 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 onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume46, Issue420 January 2022Pages 1-2 RelatedInformation
Survey on Energy-Efficient Deep Neural Networks for Computer Vision

Deep Neural Networks (DNNs) are greatly successful in performing many different computer vision tasks. However, the state-of-the-art DNNs are too energy, computation, and memory-intensive to be deployed on most computing devices and embedded systems. DNNs usually require server-grade CPUs and GPUs. To make computer vision more ubiquitous, recent research has focused on making DNNs more efficient. These techniques make DNNs smaller and faster through various refinements and thus are enabling computer vision on battery-powered mobile devices. Through this article, we survey the recent progress in low-power deep learning to discuss and analyze the advantages, limitations, and potential improvements to the different techniques. We particularly focus on the software-based techniques for low-power DNN inference. This survey classifies the energy-efficient DNN techniques into six broad categories: (1)Quantization, (2)Pruning, (3)Layer and Filter Compression, (4)Matrix Decomposition, (5)Neural Architecture Search, and (6)Knowledge Distillation. The techniques in each category are discussed in greater detail in this chapter. Take-aways Surveys the recent progress in low-power deep learning to analyze the advantages, limitations, and potential improvements to the different techniques. Focus on the software-based techniques for low-power DNN inference
How many Clusters? - An algorithmic answer

Previous chapter Next chapter Full AccessProceedings Proceedings of the 2022 Annual ACM-SIAM Symposium on Discrete Algorithms (SODA)How many Clusters? - An algorithmic answerChiranjib Bhattacharyya, Ravindran Kannan, and Amit KumarChiranjib Bhattacharyya, Ravindran Kannan, and Amit Kumarpp.2607 - 2640Chapter DOI:https://doi.org/10.1137/1.9781611977073.102PDFBibTexSections ToolsAdd to favoritesExport CitationTrack CitationsEmail SectionsAboutAbstract Many algorithms for clustering high dimensional data assume that k, the number of clusters, is given. However, there has been little work on provably inferring k from the data. This paper gives polynomial time algorithms for finding k from the data assuming it satisfies certain natural deterministic conditions. Informally, we assume that there is a Ground Truth (GT) clustering of the data with the following properties: (i) Each cluster has a certain minimum size, (ii) the inter-mean separation of any two distinct clusters in the GT is large enough (although still weaker than what is typically assumed in the literature), and (iii) we define a novel “no large sub-cluster” (NLSC) property that characterizes the notion of a cluster by stipulating that there be no subsets of low “directional variance”. NLSC is indeed satisfied by large class of distributions including log-concave densities. The first major contribution is an algorithm for finding k where m, the minimum GT cluster size, is assumed to be known. This algorithm uses a novel rounding procedure which finds subsets of size m with low Directional Variance by rounding a SDP relaxation using Cheeger's inequality and it is shown that k is precisely the number of such sets whose means are well-separated. The harder problem of finding k when m not given is addressed by running the previous algorithm for each value of m to find candidate values of k and the corresponding k-clustering. The second major contribution of this paper is a test which certifies the correct candidate thereby yielding a polynomial time algorithm which finds k. Previous chapter Next chapter RelatedDetails Published:2022eISBN:978-1-61197-707-3 https://doi.org/10.1137/1.9781611977073Book Series Name:ProceedingsBook Code:PRDA22Book Pages:xvii + 3771
The Design and Implementation of Dynamic Costume Projection System

With the development of machine vision theory and the advancement of hardware technology, the application of 3D models and 3D reconstruction, medical treatment, and life is becoming more and more widespread. Projection mapping is one of the special applications in this field. Therefore, in this paper, we proposed a dynamic virtual costume system that use the Kinect V2 somatosensory device to acquire the human body grid structure based on the 3D depth image, preprocesses the depth 3D image to obtain a simplified grid, and use iterative closest point (ICP) algorithm to calculate the projecting virtual costume. We align the position of the points between physical human body 3D mesh and virtual costume 3D mesh. After aligning the virtual costume 3D mesh to physical human body 3D mesh, the final virtual costume is suitable for physical human body via rotation and translation. The projector would project the generated virtual costume onto human body. And the proposed system also showed that the ICP algorithm could be used with different object registration.
Software Fault Severity Prediction Using Git History Metrics and Commits

In this paper, we propose new software agnostic metrics extracted from Git history. We compared the proposed metrics to many traditional code-based metrics in terms of fault severity prediction. We used three Machine Learning Algorithms (Random Forest, SVM and Multilayer Perceptron) to build the prediction models. We used data (source code, source code metrics, fault severity information) collected from three different data sources. Results show that the proposed software agnostic metrics perform better in terms of fault severity prediction compared to traditional code-based metrics. They were able to achieve 84% of accuracy in fault severity prediction. We also introduced some terms extracted from commits and showed their effectiveness for fault severity classification.
Visualizing Spatial Data from Access Logs

In the last chapter, we talked about D3 and looked at concepts from making simple shapes to creating a bar chart out of those shapes. In the previous two chapters, we took a deep dive into R. Now that you are familiar with the core technologies that we will be using, let’s begin looking at examples of how, as web developers, we can create data visualizations that communicate useful information around our domain.
Mobile Robot Navigation System Based on Adaptive Selection of Action Models Acquired by Deep Reinforcement Learning in Unknown Real World

The purpose of study is autonomous mobile robot navigation in any unknown real environments. A proposed system is based on switching of action models according to situations around the mobile robot. Action models for predefined basic shapes are trained in advance by deep reinforcement learning. In addition, mobile robot selects suitable action model based on shapes around the robot. Autonomous robot navigation experiments were performed in two real environments that include the place mainly consisted of basic shapes and the other place including complicated shape. The results of the experiments are shown in this paper.
The Navigation System for Guidance Robots that Can Switch its Guidance Method Anytime

We have developed the guidance robot "EM-Ro" for the ECO35 muffler museum, and already realized in both the visitor-escort method with prepared route and visitor-following method to guide visitors as they move around. In this paper, the navigation system for guidance robots that can switch these guidance methods was developed successfully. The waypoint navigation is applied to both the visitor-escort and visitor-following method. Therefore, switching between the prepared or visitor-derived waypoints can make visitors choose the guidance method they prefer. Visitors are able to switch the guidance method anytime, by giving EM-Ro the request from the remote controller. The experimental results showed that the navigation system enable to switch guidance method seamlessly.
Pelatihan Uji Sentuh Jari Kaki Sebagai Upaya Peningkatan Ketrampilan Kader Kesehatan Dalam Mendeteksi Gangguan Sensasi Kaki

Background: Increased life expectancy will be followed by increasing problems if health care is not carried out properly. Problems will arise, one of which is endocrine system disorders such as diabetes mellitus which has complications. One of the complications of diabetes mellitus is diabetic ulcers on the feet by 7.5% of patients who experience impaired sensation which ultimately have to undergo amputation. This condition can be prevented early, such as by checking the sensation of the feet. This activity aims to increase the role of health cadres in detecting the incidence of neuropathy. Methods: In order to provide knowledge and skills of the toe touch test to 30 health cadres, the method chosen was training supported by guidebooks, videos and demonstrations. Results: There was an increase in the knowledge of cadres in good categories from 13% to 89% between before and after training. Meanwhile, the skills of the cadres showed that all of the training participants were skilled in doing the toe touch test. Conclusion: Improving the knowledge and skills of cadres can be pursued through training by combining the use of manuals, videos and demonstrations.
THE CONCEPT OF “PEDAGOGICAL STRATEGY” IN EDUCATION IN RUSSIA AND CHINA

The study systematizes the complex and extensive content of the concept of pedagogical strategy, which not only helps scholars realize its importance as a scientific concept, but also contributes to the improvement of the quality and effectiveness of teaching. The article reveals the essence of the concept of “pedagogical strategy” in the context of educational research in Russia and China, describing several views of the scholars on the content of this concept. It is emphasized that modern views of Russian and Chinese scholars on the concept of “pedagogical strategy” have both some common features and some obvious differences. Based on the analysis the following results are given: the commonality is that the pedagogical strategy has a definite goal and is developed in specific pedagogical conditions to perform a specific teaching task, including the choice of methods of teaching activities, preparation of materials and regulation of teacher and student behavior. The article examines the differences between the views of Russian and Chinese scientists on the essence of the concept of “pedagogical strategy”. In addition, the article discusses the similarities and differences in the interpretation of such concepts as “teaching strategy”, “educational strategy”, “pedagogical strategy”, “learning strategy”, “teaching idea”, “teaching design” and “teaching methodology”. Although the definitions of some of these concepts are different in specific words, they may have similar meanings and can be used as synonyms. At the same time, there are other concepts which names are similar, but they represent completely different phenomena. At the end of the article, the author analyzes several essential features of the concept of pedagogical strategies and points out the important role of this concept in describing the learning system.
PRRL: Path Rotation based Knowledge Graph Representation Learning method

Knowledge graph (KG) representation learning aims at embedding triples in the form of vectors. Their semantic similarity can be expressed through the distance of those vectors, and thus easily be computed for further application, such as knowledge completion. Early KG embedding methods, such as the TransE model, were mainly training with relationship of each individual triple, and ignore the relationships between multiple triples. Thus their representation result is subject to the integrity of the triples. Recently, some path-enhanced methods, such as PTransE and RPJE, adopt the path information composed of multiple triples as supplement relation information for training, which achieves better effect than those triples based methods. On the other hand, the performance of path-enhanced methods is still affected by the fact that they are hard to learn the symmetric relation pattern in both triples and paths. Thus we propose Path Rotation based KG Representation Learning method (PRRL), which maps entities and relations into complex vector space and defines both relations and paths (composed by sequence of relations) as a rotation from source entity to target entity. PRRL can model and infer a variety of relation patterns, including symmetry/antisymmetry, inversion and composition relations by representing the path with Hadamard product of relations. The results of experiment on multiple datasets show that PRRL is better than the baseline in the completion of the task of KG.
1871 Familiar problems of a bygone age [IET@150 history]

Having looked at today&apos;s challenges faced by the IET, its members and society, what were the seven key social and technology issues vexing the founding fathers of the IET 150 years ago? There is a familiar ring to the answers.
The Effect of ARTIFICIAL INTELLIGENCE and Child Life Guidance Subject on Pre-Service Teachers

Purpose: The purpose of this study is to investigate the effects of AI and child life guidance subject on pre-service teachers. Method: AI and child life guidance subject was conducted for one year. The feeling of contents of AI and child life guidance subject was investigated, the opinions of the students and the experience of operating the curriculum for children s life guidance for decades. The instructional design was reconstructed. AI and child life guidance subject was applied for one semester to 40 third - year university students attending , 10 of them were selected as research participants. For data collection, in-depth interviews were conducted with the 10 students who experienced. Qualitative content analysis were collected the opinions of the students and the experience to closely examine their thoughts and attitudes Results: Pre-service teachers reported the importance of AI and child life guidance subjects. They understood the AI robot to be used in the field well, acknowledged the value of the robot as an assistant teacher, and said that the method of cooperating with the robot is a future-ready capability. It was said that the AI movie seemed to have provided the motivation for the learning contents of AI and children s life guidance. Children s life guidance learning using robots became interested in the children s life guidance subject. Conclusion: First, If the teacher s competency of using robots, which is an assistant tool for tutors, is developed, pre-service teachers will be able to grow further in the AI era through efforts such as fostering professionalism, teachers should be nurtured to provide guidance by using big data of AI to focus on expanding children s thinking and social relationships. supporting children s thinking expansion, and providing positive life guidance. Second, In accordance with the direction of AI education policy, teachers should be nurtured to provide guidance by using big data of AI to focus on expanding children s thinking and social relationships. Third, A teacher s ability to guide children s life with delicate sensitivity that cannot be aided by robots will be an effective way to guide children s life. The use of robots will enable customized guidance for each child. Fourth, Teachers should develop the capacity of life guidance for child-led interaction to promote the development of children s autonomy. Fifth, Teachers should have an opportunity to check the political and cultural context of teaching-learning through self-reflection because the value and belief system of teachers also affect the interaction with children.