Reviewerly/exHarmony huggingface dataset:
PONY: Predicting an Object’s Next_Location Using YOLO

There are more to images than just objects, given a sequence one can derive more data from then it just what objects are in frame. PONY is a proof of concept that enables the extraction of additional information from still images that are to be processed by an object detection algorithm. The module aims to provide a basic YOLO implementation short term memory. Memory that will help predict where a detected object will be based on its historical position. The study was tested on vehicular and pedestrian pre-recorded traffic data and live video feed as well. In the tests, it was found that tracking the motion by basing on historical position is doable. The module was able to predict the likelihood of where an object will be proceeding or be located next. The study proves that increasing future functionality of basic camera implementation in systems without specialized sensors is a possibility.
The potential to improve vision with AR

Millions of people have visual impairments that cannot be corrected by conventional eyeglasses. Can emerging augmented reality technology eventually be used to create “smart eyeglasses” that digitally enhance visual information for people with impaired vision? I will present work in which we use existing augmented reality systems to design visual enhancements aimed at assisting with key visual functions, such as recognizing objects and navigating buildings, and assess these enhancements using perceptual and behavioral studies.
Optimisation of sub-space clustering in a high dimension data using Laplacian graph and machine learning

There are many applications like business analytics, computer vision and medical data analytics, where an unsupervised approach of learning is used for the high-dimension data (HDD) clustering. The problem of the subspace clustering is modelled as a graph problem which has to retain the critical features from the N-dimension while applying a dimension reduction technique to maintain a higher accuracy and lower computational overhead trade-off. Most of the traditional approaches suffer from the efficiency degradation when applied to HDD. An optimisation of sub-space clustering is proposed in this paper for learning models using Laplacian graph on a HDD. The proposed model addresses the curse of dimensionality problem through Laplacian matrix function to minimise the data redundancy within sub-space. The traditional K-nearest neighbour (KNN) algorithm is improvised for the non-linear classification of subspace clustering on HDD clinical importance. The proposed system offers significant increment of 99% of accuracy in clustering operation.
Digital quantum simulation and pseudoquantum simulation of the <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"><mml:mrow><mml:msub><mml:mrow><mml:mi mathvariant="double-struck">Z</mml:mi></mml:mrow><mml:mrow><mml:mn>2</mml:mn></mml:mrow></mml:msub></mml:mrow></mml:math> gauge–Higgs model

We present a quantum algorithm for digital quantum simulation of the $\mathbb{Z}_2$ gauge-Higgs model on a $3\times 3$ lattice, which is based on Trotter decomposition, the quantum adiabatic algorithm and its circuit realization. Then we perform a classical demonstration, dubbed a pseudoquantum simulation, on a GPU simulator. We obtain useful results on this model, which suggest the topological properties of the deconfined phase and help to clarify the phase diagram. It is suggested that the tricitical point, where the second-order critical lines of deconfinement-confinement transition and of deconfinement-Higgs transition meet, seems to be on the the first-order critical line of confinement-Higgs transition, at a point other than the end of this critical line.
Neural Networks: Mathematical Remarks

The following sections treat mathematical topics that were presupposed in the text (Sect. 10.1 on straight line equations and Sect. 10.2 on regression), or side remarks, which would have disturbed the flow of the exposition (Sect. 10.3 on activation transformation in a Hopfield network).
First standalone headset for a new generation of mixed reality experiences

French startup Lynx has had a strong 2021 having redesigned its mixed reality (MR) headset earlier in the year followed by a successful Kickstarter that raised just over $800,000 USD. Founder Stan Larroque will give an update of Lynx-R1, a fully all-in-one (AIO) MR headset featuring a 2.1″ octagonal LCD panel, 1600 x 1600 per eye resolution at 90Hz with a 90° FOV, all powered by a Qualcomm XR2 chipset, 6GB RAM and 128GB internal storage that’s expandable via an SD card slot.
Promoting Equity, Improving Quality, and Modernizing Education Governance

AbstractIn the process of rapid urbanization, rural areas are under the great challenge to effectively improve educational quality, which aims at promoting the integrated development of compulsory education in urban and rural areas within counties. The Ministry of Education (MOE) has announced the “core competencies” of student development and the guidance on reforming the high school entrance examination to facilitate the implementation of quality education. At the same time, the serious problem of examination-oriented education and excessive extracurricular tutoring are negatively affecting the well-rounded development of young people. The huge gap in education development between urban and rural areas has become a constraint to improving education equity and quality. The co-existence of examination-oriented education and innovative education has led to a strong contrast between education’s ideal and reality. This highlights the reality that the education reform is entering the “deep-water zone” in a landscape of diversified social interests and stakeholders in the education industry. Moreover, our task to promote the modernization of education governance is extremely challenging.
EVALUATION OF EDUCATIONAL SUCCESS OF THE COLLEGE STUDENTS: THE TYPOLOGY

Introduction:Self-assessment of the educational success appears to be one of the stable regulators of educational activity. It determines the student's choice of a certain educational strategy, predicts his/her orientation towards the educational and professional future. Article presents the typology of students according to their level of success in education, and their educational strategies according to each type of students.Research Methods:The empirical basis is based on the results of a massive online survey of college students conducted in 2021 in a large industrial region of Russia (Sverdlovsk region), carried out at multistage sampling. A cluster selection of educational organizations was arranged in 8 administrative districts of the region. The questionnaires were published on the website of educational organizations. The sample was based on the open statistical data on the number of students in the Sverdlovsk region. The sample size was 1349 people. Results:The TwoStep cluster method was used to analyze the self-assessments of the educational success of college students. The division was made in the set of characteristics: “attitude to learning”; "The amount and quality of knowledge gained during training"; "The ability to apply the knowledge gained in practice"; “General academic achievement”. The result performed in two clusters: first (42%) is characterized by a high, and the second (58%) - a reduced level of self-esteem of students. “Unsuccessful” students appeared to be more passive in choosing a strategy for the future associated with the educational and professional spheres. In addition, 48% of “unsuccessful” students see education as dysfunctional, it does not guarantee success in life, high status, does not make life more interesting. For “unsuccessful” students, higher subjective risks of achieving formal results of educational activity (getting points, grades, and diplomas) are important. The adaptive capabilities of “unsuccessful” students are almost half that of “successful” students. They are more likely to face the problems of organizing and implementing the educational process. Conclusions:An analysis of the educational strategies of college students showed that the discrepancy between the institutional standards of student success correlates with the denial of the positive role of education in their lives and the orientation towards avoiding formal and non-formal education in the future. In the structure of this educational community, a special group of stigmatized “unsuccessful” students has formed, actively rejecting education as a type of activity. The emerging negative trends require special management decisions for the implementation of an individualized approach to the organization of educational activities of students in this group.
THE ROLE OF TEACHERS IN INCREASING THE READING INTEREST OF ELEMENTARY SCHOOL STUDENTS

The teacher's role is important in increasing students' reading interest, this is because students tend to prefer playing with peers rather than reading books, especially in today's modern era students use mobile phones. At online times like this, students use cellphones more often so students prefer to play games on cellphones and play tik tok rather than reading. The purpose of this study was to describe the teacher's role in increasing the reading interest of grade 3 students at SD Negeri 42 Pekanbaru, to describe the teacher's obstacles in increasing the reading interest of grade 3 students at SD Negeri 42 Pekanbaru. This research method uses descriptive qualitative research. The research subjects were third grade homeroom teachers and school principals. Collecting data using observation, interview and documentation techniques. The results of this study indicate that the role of teachers as creators, facilitators, motivators, evaluators and dynamicators is very important to increase the reading interest of elementary school students because teachers guide, encourage and monitor students. The obstacle is that the teacher still has not carried out several teacher roles such as the teacher has not carried out the teacher's role as a creator, the teacher's role as an evaluator, the teacher's role as a dynamist completely, this is due to the limited face-to-face learning, for the teacher's role as a facilitator and the teacher's role as a motivator. seems to have been done
Programmable NIC-based task offload framework

Using programmable NIC to offload network processing tasks such as checksum computation, virtual switching has become a common case in data centers. Such offloading mechanisms is able to help saving CPU cycles on servers, thus allowing data centers providing more computing resources to users for commercial benefits. However, recent research indicates that even with the offloading features above, data center servers still suffer from a great portion of CPU time being devoted to computing tasks that are unrelated to tenants. Such tasks include but not limited to data encryption and decryption, compression and decompression, etc. These tasks are common in modern data centers and cost a high amount of computational resources. Thus, in this paper, we propose a framework to offload those tasks onto programmable NIC, which will avoid high CPU usage on data center servers. On the one hand, the proposed framework is able to support multiple computing tasks running on the same programmable NIC at the same time. On the other hand, with a novel indexing mechanism, users are able to determine the order of different tasks at compile-time. Last but not least, the feasibility and advantages have been validated via our early stage experiments.
A Study of Student’s Academic Performance Using Artificial Intelligence: A Fuzzy Logic Approach

Student academic performance evaluation involves several components, each based on number of imprecise judgments arising due to human (teacher/tutor) interpretation. In this Book chapter, we explore the applicability of fuzzy logic and fuzzy expert system to student allocation problem that allocates new students to homogenous groups of specified maximum capacity, and analyze effects of such allocations on the academic performance of students. The book chapter also presents a Fuzzy set and Regression analysis based Dynamic Fuzzy Expert System model which is capable of dealing with imprecision and missing data that is commonly inherited in the student academic performance evaluation. This model automatically converts crisp sets into fuzzy sets by using fuzzy C-Means clustering algorithm method.
MOZAMBIQUE: No Clear End

Africa Research Bulletin: Political, Social and Cultural SeriesVolume 59, Issue 2 p. 23492A-23493C National Security MOZAMBIQUE: No Clear End First published: 14 March 2022 https://doi.org/10.1111/j.1467-825X.2022.10415.xRead 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. Volume59, Issue2March 2022Pages 23492A-23493C RelatedInformation
Beyond Sequential: Parallelism in Multicore and the Cloud

The dramatic increase in computer performance has been extraordinary, but not for all computations: it has key limits and structure. Software architects, developers, and even data scientists need to understand how exploit the fundamental structure of computer performance to harness it for future applications. Ideal for upper level undergraduates, Computer Architecture for Scientists covers four key pillars of computer performance and imparts a high-level basis for reasoning with and understanding these concepts: Small is fast – how size scaling drives performance; Implicit parallelism – how a sequential program can be executed faster with parallelism; Dynamic locality – skirting physical limits, by arranging data in a smaller space; Parallelism – increasing performance with teams of workers. These principles and models provide approachable high-level insights and quantitative modelling without distracting low-level detail. Finally, the text covers the GPU and machine-learning accelerators that have become increasingly important for mainstream applications.
Radial Basis Function Networks

Like multi-layer perceptrons, radial basis function networks are feed-forward neural networks with a strictly layered structure. However, the number of layers is always three, that is, there is exactly one hidden layer. In addition, radial basis function networks differ from multi-layer perceptrons in the network input and activation functions, especially in the hidden layer. In this, hidden layer radial basis functions are employed, which are responsible for the name of this type of neural network. With these functions, a kind of “catchment region” is assigned to each neuron, which mainly influences the output of the neural network.
Interpretability of Machine Learning versus Statistical Credit Risk Models

Model interpretability is important in the banking industry for three reasons: certain US regulations require creditors to provide consumers with the reasons for taking adverse action (reason codes) on their credit applications; model users want to understand the reasoning behind model predictions; and identification of bias and reinforcement of stakeholders’ trust in the model. In this article, the authors compare the interpretability of an XGBoost versus a logistic model in predicting the probability of default for a credit card customer. They conclude that (1) the reason codes of an XGBoost model and a comparable logistic model are similar, (2) reason codes generated by XGBoost are more trustworthy from the customer’s perspective, and (3) nonlinearity of XGBoost is unlikely to have a significant impact on reason code(s).
Study about the Pattern of Prime Numbers

Prime numbers are fundamental to the most common type of asymmetric encryption used today, namely Diffie-Hellman key exchange, Rivest-Shamir-Adleman cryptosystems, ElGamal Cryptosystem, Elliptic curve cryptosystems, etc.The prime numbers \(p\geq 5\) obey a pattern that can be described by two forms or geometric progressions \(6m+[5,7] \rightarrow m\in \mathbb{z}^+\) or \(6k\pm 1 \rightarrow k\in \mathbb{z}^+\) that facilitates obtaining them sequentially, being possible also to calculate the quantity of primes that are in the geometric progressions \(6k\pm 1 \), fore \(k\geq 1\) as it is described in this document.
Automatic License Plate Recognition for Distorted Images Using SRGAN

The quality of an image is always a limitation for automatic license plate recognition (ALPR) for its practical and accurate functioning. Distorted low-resolution (LR) images are one of the common issues encountered in ALPR systems. Most of the available algorithms in ALPR systems are effective under controlled circumstances or with intricate image capture systems. Authorities are looking for an improved ALPR system that is primarily concerned with dealing with distorted LR images. In this research, an improved ALPR system is proposed to generate high-resolution (HR) images from LR images using the super-resolution generative adversarial network (SRGAN). On a self-created Nepali dataset, both the networks (ALPR and SRGAN) are trained and assessed. Traditionally, for the identification of vehicles, images of license plates are localized, characters are segmented, and recognized. The accuracy of license plate recognition is heavily reliant on segmentation and recognition accuracy. ALPR with SRGAN comprises a super-resolution process in between. Super-resolution aids to improve the performance of the system by recreating detailed variation of the localized image, thus providing better end-to-end recognition.
Vasthu Shastra Using AI Rule Based Expert System (CLIPS)

Throughout the years, individuals have truly developed to utilize Vastu Shastra for better life. They have begun to value the idea a great deal. What is the explanation for individuals utilizing and acknowledging Vastu Shastra to such an extent? What makes this custom so interesting or so fruitful? Indeed, a ton of things. Vastu Shastra can truly improve an individual's life. It is very difficult to bring Vasthu consultant to your place as they charge huge consultation fee and also to rely on single Vasthu consultant report because in market different consultants will give different suggestions and remedies. There are so many tips and FAQ's available online for Free but that doesn't solve the problem that we are facing in real time scenario. This paper presents Virtual Vasthu Pandit where the user can answer several questions raised by Artificial Intelligence Expert Systems before he/she decide to purchase a particular piece of land or not. This virtual vasthu expert systems is developed after consulting several vasthu shastra experts and online resources that also tells several remedies in their existing flat and also whether that particular flat is suitable for him/her based on the owner date of birth. This virtual vasthu consultant will be cost effective and reliable. This paper is implemented using CLIPS (C Language Integrated Production System) which is a public domain software tool for building expert system. The implementation code of this expert system also shared at the end of this chapter.
Introduction

Connecting theory with practice, this systematic and rigorous introduction covers the fundamental principles, algorithms and applications of key mathematical models for high-dimensional data analysis. Comprehensive in its approach, it provides unified coverage of many different low-dimensional models and analytical techniques, including sparse and low-rank models, and both convex and non-convex formulations. Readers will learn how to develop efficient and scalable algorithms for solving real-world problems, supported by numerous examples and exercises throughout, and how to use the computational tools learnt in several application contexts. Applications presented include scientific imaging, communication, face recognition, 3D vision, and deep networks for classification. With code available online, this is an ideal textbook for senior and graduate students in computer science, data science, and electrical engineering, as well as for those taking courses on sparsity, low-dimensional structures, and high-dimensional data. Foreword by Emmanuel Candès.
Photonic TPU ASIC for AI acceleration

With Moore’s law and Dennard scaling now being limited by fundamental physics, the trend in processor heterogeneity suggests the possibility for special-purpose photonic processors such as neural networks or RF-signal & image filtering. Here unique opportunities exist, for example, given by algorithmic parallelism of analog and distributed non-van Neuman architectures enabling non-iterative O(1) processors with ps-short delay towards real-time decision making. Here, I will share our latest work on photonic information processors to include a photonic tensor core including multistate photonic nonvolatile random-access memory [Appl. Phys. Rev.], and a massively parallel Fourier-optics convolutional processor [Optica]. In summary, photonics connects the worlds of electronics and optics, thus enabling new concepts of efficient intelligence information processing via algorithm-hardware homomorphism empowered by the distinctive properties of light.
Teacher’s Techniques in Teaching English at Junior High School

This research aims to determine the techniques used by teachers in teaching English at SMPN 1 Barangka. The design of this study is qualitative descriptive using observation and interview. In collecting data through observation researcher used field notes to observe techniques applied the teachers in the teaching process and interview teachers. The subjects in this study was the seventh grade English teacher. The findings revealed that the techniques applied the teachers seventh grade are question and answer techniques, repetition drill techniques, memorization techniques, small group discussion techniques, and transformation drill techniques. These techniques aims to improve student’s English pronunciation, improve memory power or student’s English vocabulary, familiarize students using English, improve students understanding of teaching materials, and train student’s to think about solving a problem. The selection of the techniques was based on the student’s English skill.
3D Printed Materials in Water Treatment Applications (Adv. Sustainable Syst. 3/2022)

Water Treatment In article number 2100282, Nirupam Aich, Ashok Kumar Gupta, Chandra Sekhar Tiwary and co-workers review the key findings, potential outcomes, and future prospects of relevant research works, as well as suggestions regarding the function of 3D printed materials in water treatment applications.
Quantum Languages, Compilers, and Tools

At this point, we understand the principles of quantum computing, the important foundational algorithms, and the basics of quantum error correction. We have developed a compact infrastructure for exploration and experimentation, but it is at the gate level.