Reviewerly/exHarmony huggingface dataset:
Solving optimal carrier frequencies of a CGH null compensator through a double-constrained searching method based on iterative ray-tracings

Interferometry based on a computer-generated hologram (CGH) null compensator is a general method for high-precision metrology of aspherics. Because the most commonly used CGHs are the Ronchi type with only two quantization steps, tilt and defocus carrier frequencies must always be introduced to separate the disturbing diffraction orders (DDOs). Determining the amount of carrier frequencies is a pivotal but difficult issue in the CGH design process. Previous studies have only drawn qualitative conclusions or obtained some approximate results under specific conditions. This paper proposes a double-constrained searching method based on iterative ray-tracings, which can directly and accurately give the optimal combination of tilt and defocus carrier frequencies, as long as the aspheric under test is a concave one and has an analytical expression. The optimal carrier frequencies solved by the proposed method will minimize the line density of the CGH on the premise of separating all DDOs, which will reduce the cost and difficulty of fabrication as much as possible. The proposed method is almost error-free and holds a clear advantage over the previous methods in terms of versatility. Several typical design examples are presented to verify the feasibility and versatility of the proposed method. Its accuracy is also verified through making comparisons of the ray-tracing results between another method and Zemax models based on these examples.
Reducing neural architecture search spaces with training-free statistics and computational graph clustering

The computational demands of neural architecture search (NAS) algorithms are usually directly proportional to the size of their target search spaces. Thus, limiting the search to high-quality subsets can greatly reduce the computational load of NAS algorithms. In this paper, we present Clustering-Based REDuction (C-BRED), a new technique to reduce the size of NAS search spaces. C-BRED reduces a NAS space by clustering the computational graphs associated with its architectures and selecting the most promising cluster using proxy statistics correlated with network accuracy. When considering the NAS-Bench-201 (NB201) data set and the CIFAR-100 task, C-BRED selects a subset with 70% average accuracy instead of the whole space's 64% average accuracy.
A Lightweight Wearable American Sign Language Translation Device

Abstract A lightweight wearable American Sign Language translation device is presented consisting of optically communicating rings worn on each finger and wireless devices worn on each fingernail. The device is similar in principle to glove based sign language translation devices except it does not require the user to wear an entire glove. Each ring is constructed from optically clear resin containing three infrared transponders, controlled by a microcontroller unit worn on the wrist. The fingernail units are also cast in clear resin and contain circuitry to receive and respond to infrared light, and house three small SR60 watch batteries. The system uses a microcontroller to flash all LEDs in succession and create matrix sensor readings from each LED, resulting in a 15x15 matrix corresponding to a signed gesture, recognized by an Artificial Neural Network. This system is expected to be able to recognize 24 of the 26 letters of the ASL alphabet and be extended to recognize arbitrary ASL signs with the integration of an accelerometer. The system currently recognizes 9 letters (A, B, D, F, K, N, O, T, X) with intention to build on this novel method of gesture recognition to construct a full-fledged ASL translator. The system is currently useable as a low-encumbrance gesture-based input system for arbitrary device control.
The perception of vocal aesthetics in digital art

The active use of new digital technologies in the art of music is becoming the basis of a new aesthetic perception. The possibilities of digital technology to transform the voices of performers make it relevant to consider the role of vocal aesthetics in digital music art. This study aims to investigate the features of vocal aesthetics perception in digital art. The perception of musical works as pleasant or unpleasant correlates with the psycho-emotional state of the listener; thus, to study the psycho-emotional impact of synthesized vocal without instrumental accompaniment, the authors used Kunin projective physiognomic test (1977), the WAM (Well-being, Activity, Mood) technique (1973), and the Wessman-Ricks self-assessment of mental state technique (2004). The study involved 182 students and teachers of Music College, Ningbo University, China. The study of the psycho-emotional state of respondents before and after listening to synthesized vocal compositions allowed the authors to indirectly evaluate the aesthetic perception of digital music art. After listening to the vocal digital fragment, which included both major and minor fragments of different tempo and rhythm, the overall mood in the group of respondents significantly improved: good mood was detected in 26.9% of cases, and very good - in 11.5%. The positive impact of listening to a vocal digital song on the well-being, activity, and mood of the respondents correlates with its positive aesthetic impact. The research confirms that aesthetic properties are directly dependent on the listener's point of view, aesthetic experience is a matter of value and emotion, and aesthetic feeling arises as a result of an unconscious process and is associated with the normalizing effect of digital vocal composition on the psycho-emotional state of the respondents.
Digital transformation catalyzed by COVID-19 pandemic: challenges and solutions

The article presents a case study of digital transformation at Sofia University “St. Kliment Ohridski”, Bulgaria, catalyzed by COVID-19 pandemic. First, it summarizes challenges related to education and research, administrative processes, regulations, and culture from different perspectives – management of the university, professors and students. Next, the paper presents solutions, implemented as the answers of the challenges in order for transformation to happen in technological and non-technological directions. In the discussion section, we discuss the choices made to realize the digital transformation at Sofia University and the reasons behind them. In the final part of the paper, we conclude summarizing the main point of our case study and present expectations and perspectives for the future.
Research on the effect of incident polarization phase on transverse spin splitting of reflected beam

In this work, the theoretical relationship model between the incident polarization phase and transverse spin splitting (TSS) shifts of photonic spin Hall effect (PSHE) is established. Based on the established model, the effect of the incident polarization phase on the TSS is systematically studied, and several characteristic laws are summarized. These findings can help people better understand PSHE. In addition, it is found that, no matter what the incident angle and polarization angle are, the TSS shift at polarization phase equal to ±90° is larger than that at other polarization phases. It can even reach several microns under certain incident angle and polarization angle, and is almost an order of magnitude larger than the usual TSS shift, which is generally tens to hundreds of nanometers. This provides a new way for enhancing PSHE. Furthermore, when the polarization phase is 90° or −90°, under a certain polarization angle, slightly adjust the polarization angle, the TSS shift will change sharply and its direction will be reversed. This interesting finding has great application value in the field of photon manipulation.
Use of Machine Learning to Detect Lung Cancer

Lung cancer has become one of the most common causes of cancer in both men and women. A large number of people die every year due to lung cancer. The purpose of this project is to detect early signs of lung cancer and improve accuracy and sensitivity. Different features are extracted from the input image and based on the calculations, result from the support vector machine is obtained as cancerous cells are present or not. The stages included in this are pre-processing, segmentation, feature extraction and classification. In pre-processing the noise and blurriness of image removed. In segmentation the image is segmented using DWT techniques. The features extracted using GLCM matrix. The extracted features are Entropy, Co-relation, energy, contrast and Dissimilarities. SVM uses hyper plane algorithm to detect whether the given image is ‘Malignant’ or ‘Benign’
Blockchain and Distributed Autonomous Community Ecosystems: Opportunities to Democratize Finance and Delivery of Transport, Housing, Urban Greening and Community Infrastructure

This report investigates and develop specifications for using blockchain and distributed organizations to enable decentralized delivery and finance of urban infrastructure. The project explores uses cases including: providing urban green, street or transit infrastructure; services for street beautification, cleaning and weed or graffiti abatement; potential ways of resource allocation ADU permitting and land allocation and homeless housing. It establishes a general process flow for this blockchain architecture involves: 1) creation of blocks (transactions); 2) sending these blocks to nodes (users) on the network for an action (mining) and then validation that that action has taken place; and 3) then adding the block to the blockchain. These involves potential for creating new economic value through proof of work which can be issued through a token (possibly a graphic Non-fungible Token), certificate or possible financial reward. We find that encouraging trading of assets at the local level can enable creation of value that could be translated in the sustainable “mining actions” that would fund the basis of an alternative, local cryptocurrency.
Developing PDP model by using malware detection techniques for securing cloud storage data using cryptanalysis

This model advocates detection plus protection better than the existing one. This model will first detect the malware and then remove the unwanted (delinquent systems) one. It will mention the number of systems corrupted by the source (type of attack). After detection it will indicate the measures to be taken for the correct functioning of the system. The future effect of existing model is questionable as it can't mention or detect the number of systems corrupted and also the type of corruption. This article commends a replacement model for existing device. It offers numerous vital blessings along with higher identification of malicious software program, more desirable forensics capabilities and amended deploy ability. This conjoins detection techniques, static signatures examine and Dynamic analysis detection. With this procedure, existing models provide approx 35% better detection coverage and with new model, we will try to enhance the detection coverage percentage.
Self-directed Use of Digital Devices for Out-of-class English Learning

Twenty-first-century teaching and learning provide online resources accessible to foster learning experience across time and spaces in an informal context. Hence, enhancing learners’ voluntary adoption of digital devices is crucial to augment the promising assistance of technology for English language learning. This study sheds some light on English for Specific Purposes (ESP) learners’ voluntary digital devices for out-of-class language learning. A total of 267 Indonesian ESP learners participated in this study through a survey and semi-structured interview to examine how they were involved in informal digital learning of English beyond the classroom. The results showed that the learners used digital devices for both intentional learning to strengthen coursework and incidental learning to expand access to the target language. It was also found that the learners frequently employed digital devices for personalized aspects of the language rather than authenticity and connectivity. As for the digital device selection, the learners mostly preferred mobile phones to computers and tablets to carry out out-of-class English language activities. These results provide fruitful insights for educators on supporting ESP learners to engage in informal digital learning of English and achieve possible synchronicity between teachers' designed digital activities and learners' actual learning practices.
An Intelligent Classification System for Trophozoite Stages in Malaria Species

Malaria is categorised as a dangerous disease that can cause fatal in many countries.Therefore, early detection of malaria is essential to get rapid treatment.The malaria detection process is usually carried out with a 100x magnification of thin blood smear using microscope observation.However, the microbiologist required a long time to identify malaria types before applying any proper treatment to the patient.It also has difficulty to differentiate the species in trophozoite stages because of similar characteristics between species.To overcome these problems, a computer-aided diagnosis system is proposed to classify trophozoite stages of Plasmodium Knowlesi (PK), Plasmodium Falciparum (PF) and Plasmodium Vivax (PV) as early species identification.The process begins with image acquisition, image processing and classification.The image processing involved contrast enhancement using histogram equalisation (HE), segmentation procedure using a combination of hue, saturation and value (HSV) color model, Otsu method and range of each red, green and blue (RGB) color selections, and feature extraction.The features consist of the size of infected red blood cell (RBC), brown pigment in the parasite, and texture using Gray Level Co-occurrence Matrix (GLCM) parts.Finally, the classification method using Multilayer Perceptron (MLP) trained by Bayesian Rules (BR) show the highest accuracy of 98.95%, rather than Levenberg Marquardt (LM) and Conjugate Gradient Backpropagation (CGP) training algorithms.
Logistic Map and Exponential Scaling Factor based Differential Evolution

Differential evolution (DE), an important evolutionary technique, enhances its parameters such as, initialization of population, mutation, crossover etc. to resolve realistic optimization issues. This work represents a modified differential evolution algorithm by using the idea of exponential scale factor and logistic map in order to address the slow convergence rate, and to keep a very good equilibrium linking exploration and exploitation. Modification is done in two ways: (i) Initialization of population and (ii) Scaling factor.The proposed algorithm is validated with the aid of a 13 different benchmark functions taking from the literature, also the outcomes are compared along with 7 different popular state of art algorithms. Further, performance of the modified algorithm is simulated on 3 realistic engineering problems. Also compared with 8 recent optimizer techniques. Again from number of function evaluations it is clear that the proposed algorithm converses more quickly than the other existing algorithms.
Optimal Trajectory Planning Method for the Navigation of WIP Vehicles in Unknown Environments: Theory and Experiment

Navigation of underactuated wheeled inverted pendulum (WIP) vehicles in unknown environments is still facing great difficulties, especially when the optimal motion is required. This article proposes an optimal trajectory planning method for the navigation of WIP vehicles in unknown environments, where various performance demands, such as security, smoothness, efficiency, etc., are all considered. First, a map-building algorithm based on the improved Rao–Blackwellized particle filter is applied for the WIP vehicle to construct the environmental map. Then, a multiobjective optimization using the genetic algorithm is performed to find an optimized path between the given start and target point with path length, path curvature, and safe distance being taken into consideration simultaneously. Moreover, on the basis of kinematical and dynamical analysis, velocity, and acceleration constraints are parameterized with a path parameter, and the minimum-time trajectory along the optimized path is further planned with a sequence of maximum acceleration and deceleration trajectories. Finally, a WIP vehicle platform based on the robot operating system is designed, and related experiments in a real obstacle environment are conducted to validate the feasibility of the proposed method.
An Empirical Study on the Use of CDIO in Software Engineering Education

Contribution: In this study, we accumulated the knowledge and generated evidence on how and in what context CDIO framework has been used in software engineering (SE) education. The aggregated evidence will enable SE academics in making informed decisions while adopting CDIO for SE education and build upon it. Background: CDIO framework is relevant for SE as it focuses on enabling engineering graduates in conceiving, designing, implementing, and operating complex systems and products. We were not able to find any study that identifies and aggregates the evidence on the use of CDIO for SE education. Research Questions: This study attempts to answer the following research questions: 1) how CDIO has been used in SE education? and 2) what are the experiences of academics in applying the CDIO framework in SE education? Methodology: Using a mixed-method approach (systematic mapping study and interview study with experienced academics in SE), we established the state of the art and practice on the use of CDIO in SE education. Findings: Getting a commitment from the higher management, teachers, and students is a major challenge in the adoption of the CDIO initiative followed by a lack of competence, finance, and resources. Ownership, motivation, persistence, and training of teachers and students are required not only to adopt CDIO for SE but also to sustain it.
Coordinated Path Planning for Multi-aircrafts Based on Improved Differential Evolution Algorithm

In order to solve the problem of path planning and maximize the cooperative combat effectiveness of manned aircrafts and unmanned aircrafts, firstly, considering the battlefield environment model and the performance of each aircraft, the cost function of multi-aircrafts coordinated path planning is established. Then, a path planning strategy is proposed based on the improved differential evolution algorithm using auxiliary population. Finally, the model is built to verify the simulation. The results show that the proposed algorithm and strategy can effectively meet the requirements of coordinated path planning.
Sociocultural Functional Literacy As a Planned Learning Outcome of a Primary Schoolchild

The article emphasizes the expediency of introducing modern technologies and teaching aids into the educational process of elementary school, in particular, the creation and use of an information and educational environment based on multimedia resources. The design of a media library according to the modules of the exemplary work program "Fine Arts", intended for primary school students, is considered. Existing catalogs of multimedia resources or a thematic media library created by the teacher himself as an actual educational component are able to provide active artistic and creative visual activity of younger students, support their successful mastering of spatial and visual arts.
Taman Belajar: Learning Management System (LMS) that Provides Free Massive Open Online Course (MOOC) for School Students

research-article Share on Taman Belajar: Learning Management System (LMS) that Provides Free Massive Open Online Course (MOOC) for School Students Authors: Budi Yulianto Computer Science Department, School of Computer Science, Bina Nusantara University, Indonesia Computer Science Department, School of Computer Science, Bina Nusantara University, IndonesiaView Profile , Andyni Khosasih Chinese Department, Faculties of Humanities, Bina Nusantara University, Indonesia Chinese Department, Faculties of Humanities, Bina Nusantara University, IndonesiaView Profile , Evawaty Tanuar Computer Science Department, School of Computer Science, Bina Nusantara University, Indonesia Computer Science Department, School of Computer Science, Bina Nusantara University, IndonesiaView Profile , Yuventia Prisca Diyanti Todalani Kalumbang Public Relations Department, Faculty of Economics & Communication, Bina Nusantara University, Indonesia Public Relations Department, Faculty of Economics & Communication, Bina Nusantara University, IndonesiaView Profile Authors Info & Claims ICETM'21: 2021 4th International Conference on Education Technology ManagementDecember 2021 Pages 52–58https://doi.org/10.1145/3510309.3510318Online:14 March 2022Publication History 0citation17DownloadsMetricsTotal Citations0Total Downloads17Last 12 Months17Last 6 weeks2 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my Alerts New Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Human Detection and Posture Estimation with IR Thermal Images by a Drone

Recently, multirotor drones have been used in various fields, and drones can effectively search missing people in harsh environments. Infrared (IR) thermal imaging can be used day and night to find people that cannot be detected in visible light images. In this paper, we address the detection and estimation of a person's posture in dangerous environments using a multirotor drone equipped with an IR thermal imaging camera. We detect missing people through k-means clustering and morphological operations and remove false alarms based on the size and squareness of rectangular object windows. Then, the posture of the detected object is estimated through template matching. In the experiments, standing or sitting people were detected using thermal images captured by a drone during day and at night in the mountains, and the posture was successfully estimated.
Remote sensing-based mapping of the Wadi Sa’al-Wadi Zaghara basement rocks, southern Sinai, Egypt

The Wadi Sa'al-Wadi Zaghara area, southern Sinai, Egypt is a key geologic region within the framework of the Arabian-Nubian Shield (ANS). It almost documents the whole tectono-thermal evolution history of the Pan-African orogeny; hence it records the latest stages of Rodinia breakup (Late Mesoproterozoic) till the penultimate regional deformation event (D3) that impacted the northern tip of the ANS in the Late Neoproterozoic, i.e., before the Najd fault system. Since the metamorphosed volcano-sedimentary rock units in both Wadi Sa’al and Wadi Zaghara exhibit considerable differences in their geological evolution, they were dealt with as two distinct metamorphic belts. They cover a wide spectrum of basement rock varieties, which developed over a long period of time, from Late Mesoproterozoic (Wadi Sa’al metamorphosed volcano-sedimentary rocks) till Late Neoproterozoic Ediacaran period (post-collision granites). The different rock units of the study area were discriminated based on various image processing techniques such as Decorrelation Stretch (DS) Band Ratio (BR) and Principal Component (PC) of Sentinel-2, Landsat-8 and ASTER datasets. Remote sensing data analyses with the aid of petrography, previously published data and field verification enabled us to produce a new enhanced geological map of the study area. Advanced Land Observing Satellite (ALOS) digital elevation and enhanced Sentinel-2, Sobel directional filter images were successfully used for automatic lineaments extraction in the study area.