Reviewerly/exHarmony huggingface dataset:
Two-Channel 3D Range Geometry Compression with Virtual Plane Encoding

Modern computing and imaging technologies have allowed for many recent advances to be made in the field of 3D range imaging: range data can now be acquired at speeds much faster than real-time, with sub-millimeter precision. However, these benefits come at the cost of an increased quantity of data being generated by 3D range imaging systems, potentially limiting the number of applications that can take advantage of this technology. One common approach to the compression of 3D range data is to encode it within the three color channels of a traditional 24-bit RGB image. This paper presents a novel method for the modification and compression of 3D range data such that the original depth information can be stored within, and recovered from, only two channels of a traditional 2D RGB image. Storage within a traditional image format allows for further compression to be realized via lossless or lossy image compression techniques. For example, when JPEG 80 was used to store the encoded output image, this method was able to achieve an 18.2% reduction in file size when compared to a similar three-channel, image-base compression method, with only a corresponding 0.17% reduction in global reconstruction accuracy.
Designing a Quantum Key Distribution Network - Methodology and Challenges

Quantum Key Distribution is a promising concept for protecting operators' critical network infrastructure. We investigate how to design meshed networks with the related technology as a first attempt for further optimizations. Starting from practical operator use-cases we present security requirements. Heuristic methods based on classical design algorithms are introduced and a dedicated reference network serves for benchmarking the approaches. We conclude that more advanced methods are needed to address the challenging quantum-secured network design adequately.
Measurement of Complex Formation Process of Nickel (II) with Freshwater Fulvic Acids Using the Solubility Method

The complex formation process between Ni(II) and fulvic acids has been studied through the solubility method at pH = 9.0. The old suspension of Ni(OH)2 is used as a solid phase. Fulvic acids are isolated from Paravani lake by the adsorption-chromatographic method. The activated charcoal is used as a sorbent. The concentration of fulvic acids in model solutions changes from 1.1 × 10-5 mol/L to 4.4 × 10-5 mol/L. The value of molar mass of fulvic acids at pH = 9.0 was taken into consideration for the calculation of molar concentrations of fulvic acids. Before adding the ligand the initial concentration of nickel was 3.8 × 10-6 mol/L. This article has shown that, during complex formation process every 0.25 part of an associate of fulvic acids (Mw = 7610), inculcates into nickel's inner coordination sphere as an integral ligand, so it may be assumed, that the average molecular weight of the associate of fulvic acids which takes part in complex formation process equals to 1903. This part of the associate of fulvic acids was conventionally called the "active associate". The average molecular weight of the "active associate" was used for determining the concentration of free ligand and average stability constant (1:1), which equals to β = 1.07 × 107 (lgβ = 7.03).
Introducing a hash function for the travelling salesman problem for differentiating solutions

Solution comparison is a process used in different classes of evolutionary algorithms. It can be either for choosing a better solution or differentiating a pair of solutions. While there is no doubt that the fitness function allows determining the best solution, its use to distinguish between solutions is questionable, especially for combinatorial optimisation problems. This short paper focuses on the Travelling Salesman Problem (TSP). 39 instances of the TSPLIB are chosen, two solution samples are generated for each instance. A collision analysis of the fitness function one the TSP is presented, then an introduction to an efficient hash function with almost zero collisions.
Revisiting Lightweight Block Ciphers: Review, Taxonomy and Future directions

Block ciphers have been extremely predominant in the area of cryptography and due to the paradigm shift towards devices of resource constrained nature, lightweight block ciphers have totally influenced the field and has been a go-to option ever since. The growth of resource constrained devices have put forth a dire need for the security solutions that are feasible in terms of resources without taking a toll on the security that they offer. As the world is starting to move towards Internet of Things (IoT), data security and privacy in this environment is a major concern. This is due to the reason that a huge number of devices that operate in this environment are resource constrained. Because of their resource-constrained nature, advanced mainstream cryptographic ciphers and techniques do not perform as efficiently on such devices. This has led to the boom in the field of ‘lightweight cryptography’ which aims at developing cryptographic techniques that perform efficiently in a resource constrained environment. Over the period of past two decades or so, a bulk of lightweight block ciphers have been proposed due to the growing need and demand in lightweight cryptography. In this paper, we review the state-of-the-art lightweight block ciphers, present a comprehensive design niche, give a detailed taxonomy with multiple classifications and present future research directions.
Visual DUX: A Low cost wearable device for guiding the Blind

Amongst the world's total population there exist 285 million visually impaired people. There exist several types of equipment which can lead them to a safe way but are restricted to indoor areas and are high priced. In this paper, a wearable device called VISUAL DUX is developed that helps the blind by detecting the objects in their path and directing them through the freeway either indoor or outdoor in a cost-efficient way. As object detection works better with the deep learning algorithms we have used the YOLO V3 dataset as input to the model. The YOLO method uses convolutional neural networks to detect objects by preparing bounding boxes. After getting the bounding boxes, classes of the objects are identified based on the probabilities of the bounding boxes. After finding the class of the object the direction of the obstacle is detected to direct the people with no vision with a safer path. Compared to the existing devices our device gives better accuracy and not only detecting the obstacle it also gives the safer direction to move as an audio output.
Phase analysis on the error scaling of entangled qubits in a 53-qubit system

We have studied carefully the behaviors of entangled qubits on the IBM Rochester with various connectivities and under a "noisy" environment. A phase trajectory analysis based on our measurements of the GHZ-like states is performed. Our results point to an important fact that entangled qubits are "protected" against environmental noise by a scaling property that impacts only the weighting of their amplitudes. The reproducibility of most measurements has been confirmed within a reasonably short gate operation time. But there still are a few combinations of qubits that show significant entanglement evolution in the form of transitions between quantum states. The phase trajectory of an entangled evolution, and the impact of the sudden death of GHZ-like states and the revival of newly excited states are analyzed in details. All observed trajectories of entangled qubits arise under the influences of the newly excited states in a "noisy" intermediate-scale quantum (NISQ) computer.
Distributed Query Evaluation over Encrypted Data

The availability of a multitude of data sources has naturally increased the need for subjects to collaborate for distributed computations, aimed at combining different data collections for their elaboration and analysis. Due to the quick pace at which collected data grow, often the authorities collecting and owning such datasets resort to external third parties (e.g., cloud providers) for their storage and management. Data under the control of different authorities are autonomously encrypted (using a different encryption scheme and key) for their external storage. This makes distributed computations combining these sources hard. In this paper, we propose an approach enabling collaborative computations over data encrypted in storage, selectively involving also subjects that might not be authorized for accessing the data in plaintext when it is considered economically convenient.
Designing Mathematical Tasks for Primary School Students as A Means of Developing Combinatorial Abilities

The article has been devoted to the description of the study of the effectiveness of methodological techniques used in classes on the academic subject – "methods of teaching mathematics" with future primary school teachers. The proposed techniques allow activating the mutual connection of logical thinking and general awareness of students. This mutual relationship has been considered as a means to evaluate and develop combinatorial abilities in future primary school teachers. The assessment of the general cognitive abilities of students was carried out using the intelligence test (Eysenck, Raven). To assess the general awareness of students (the level of general cultural development, general humanitarian training, features of the microenvironment, as well as the level of general psychosocial development, etc.), the following methods were used: assessment of academic success; expert assessment of the level of general cultural development; assessment of the psychosocial development level. Original methodological techniques were used to stimulate students' interest in designing text-based mathematical tasks for primary school students at the formative stage of the study. The proposed methodological solutions have shown their effectiveness as a means of solving diagnostic tasks and developing combinatorial thinking in future teachers. The development of compositions of text mathematical tasks for primary school students is an effective tool for the development of students' combinatorial abilities. The proposed methodological solutions may be in demand in the training of future primary school teachers.
Explainability is not Enough : Requirements for Human-AI-Partnership in Complex Socio-Technical Systems

Explainability has been recognized as an important requirement of artificial intelligence (AI) systems. Transparent decision policies and explanations regarding why an AI system comes about a certain decision is a pre-requisite if AI is supposed to support human decision-making or if human-AI collaborative decision-making is envisioned. Human-AI interaction and joint decision-making is required in many real-world domains, where risky decisions have to be made (e.g. medical diagnosis) or complex situations have to be assessed (e.g. states of machines or production processes). However, in this paper we theorize that explainability is necessary but not sufficient. Coming from the point of view of work psychology we argue that for the human part of the human-AI system much more is required than intelligibility. In joint human-AI decision-making a certain role is assigned to the human, which normally encompasses tasks such as (i) verifying AI based decision suggestions, (ii) improving AI systems, (iii) learning from AI systems, and (iv) taking responsibility for the final decision as well as for compliance with legislation and ethical standards. Empowering the human to take this demanding role requires not only human expertise but e.g. also human motivation, which is triggered by a suitable task design. Furthermore, at work humans normally do not take decisions as lonely wolves but in formal and informal cooperation with other humans. Hence, to design effective explainability and to empower for true human-AI collaborative decision-making, embedding human-AI dyads into a socio-technical context is necessary. Coming from theory, this paper presents system design criteria on different levels substantiated by work psychology. The criteria are described and confronted with a use case scenario of AI-supported medical decision making in the context of digital pathology. On this basis, the need for further research is outlined.
English Extensive Reading Material Needs in Digital Era

Material is the main needs for the teaching and learning process. Advanced technology has influenced the paradigm of material presenting. This study was to identify material needs for English extensive reading course in the digital era. The study used a qualitative approach through the descriptive qualitative method. Data is taken from observation, interview, and questionnaire. Data validity used triangulation and analysis data used data reduction, data display, and taking conclusion. The findings concluded that the need 0f teaching materials for learning extensive reading in English must be under the curriculum so that students can answer global challenges, the industry, technological developments, and changes in human life that continue to develop. The presentation of the material is also directed at implementing digital facilities that are easily accessible to students. The results of the study also have implications for exploring the ability to read digital sources and variations of material according to student needs or globalization competition.
Online Learning in EFL Classroom  during Pandemic COVID19 :  Teaching Activities, Problems and Solutions

This study aims at finding out online teaching activities, online learning difficulties faced by EFL teachers and students, and students’ parents during the Covid-19 pandemic and solutions to solve them. Some EFL lecturers volunteered to participate in this research through invitation. The EFL teachers were requested to make written reflections regarding their practices in carrying out online EFL learning and the challenges they encounter. Five of them were involved in a follow-up interview individually. Semi-structured interview was administered. Data coding was done and appropriate extracts were informed in results section. To validate the data, data coding was done independently by study. As results, the EFL teachers have carried out online learning through a series of activities ranging from checking the students’ attendance to giving score on the students’ works synchronously or asynchronously depending on each school policy. Various applications and platforms ranging from learning management system to additional resource are employed. However, many problems emerge from the students, the teachers, and the students’ parents along with the valid reasons. Therefore, the online learning does not run well since it lacks of preparation and planning. Implications for better online learning are discussed. Future prospective researches are directed and encouraged
Implementation of a Tracker-Assisted Modeling Activity in an Online Advanced Physics Experiment Course

Experiment or laboratory work is an essential part of physics and other science courses. However, due to the COVID-19 pandemic, face-to-face classes have had to be transformed into remote classes. Because laboratory access has become very limited, technology must be utilized to substitute for hands-on activity in laboratory-based courses. Additionally, maintaining students’ motivation during remote classes is also challenging. In this paper, we report on the implementation of modeling activities using Tracker in our online Advanced Physics Experiment course. We examine the effectiveness of Tracker-assisted modeling activity in improving students’ graph interpretation skills on the topic of Fraunhofer-Diffraction. The results show that 20 out of 21 participants demonstrated an increase in graph interpretation skills. The average normalized gain is 0.74, which can be seen as a high degree of improvement. Although the activity did not allow students to practice hands-on skills, this activity can encourage students to practice other science-related skills. Moreover, according to the survey, students feel more motivated to learn physics online after being exposed to the modeling activity.
A Research Paper on Tweet Sentiment Analysis using Python &amp; Django

In this project our goal is to build a tweet sentimental analysis in which user can search and analyse thousands of tweets in one go. For backend we will use python and Django web framework and for front end we are going to use HTML, Css and bootstrap. It will help to analyse any hashtag and companies about their product feedback reviews. This project contains only the one user side. It is like a tweets search analyser. The design of this project is pretty simple so that the user won’t find any difficulties while working on it.
“Put the what, <i>where</i>? Cut <i>here</i>?!” challenges to coordinating attention in robot-assisted surgery: a microanalytic pilot study

Introduction During robot-assisted surgery (RAS), changes to the operating room configuration pose challenges to communication by limiting team members’ ability to see one another or use gesture. Referencing (the act of pointing out an object or area in order to coordinate action around it), may be susceptible to miscommunication due to these constraints. Objectives Explore the use of microanalysis to describe and evaluate communicative efficiency in RAS through examination of referencing in surgical tasks. Methods All communications during ten robot-assisted pelvic surgeries (radical cystectomies and prostatectomies) were fully transcribed. Forty-six referencing events were identified within these and subjected to a process of microanalysis. Microanalysis employs detailed transcription of speech and gesture along with their relative timing/sequencing to describe and analyse interactions. A descriptive taxonomy for referencing strategies was developed with categories including references reliant exclusively on speech (anatomic terms/directional language and context dependent words (CD)); references reliant exclusively on gesture or available aspects of the environment (point/show, camera focus/movement in the visual field and functional movement); and references reliant on the integrated use of speech and gesture/environmental support (integrated communication (IC)). Frequency of utilisation and number/percent ‘miscommunication’, were collated within each category when miscommunication was defined as any reference met with incorrect or no identification of the target. Results IC and CD were the most frequently used strategies (45% and 26%, respectively, p≤0.01). Miscommunication was encountered in 22% of references. The use of IC resulted in the fewest miscommunications, while CD was associated with the most miscommunications (42%). Microanalysis provided insight into the causes and nature of successful referencing and miscommunication. Conclusions In RAS, surgeons complete referencing tasks in a variety of ways. IC may provide an effective means of referencing, while other strategies may not be adequately supported by the environment.
Estimation of Photovoltaic Energy Potential and Reduced Carbon Emission through Geo-Spatial Technology – A Case Study of Karnal City, Haryana (India)

The study utilizes effectiveness of Geospatial technology analysis to estimate potential of solar photovoltaic on the roof tops of Government buildings in the study area situated between 76°59'40.648E and 29°41'38.146N occupying an area of 5978 hectares. Solar potential was quantified for the magnitude of achieved potential based on remotely sensed monthly average Global Horizontal Irradiance (GHI) derived using the Cartosat Digital Elevation Model (DEM) for the year 2017. The roof tops of institutions were digitized (1:1000 scale) using the High Resolution, panchromatic ortho-rectified World View-II satellite image (0.5 m resolution). Electricity generation considering 60% of actual area depends on the solar potential achieved on each building which varies with month. The annual solar potential summed up as varying monthly potentials with panel efficiency as 0.15 and performance ratio to be 0.75 for polycrystalline panels to be installed along with utilized roof top area were parameters used for calculation of generated electricity. An attempt has been made to calculate the reduced carbon emissions to the environment with an approach to utilize eco-friendly source of energy. Using the CO2 factor as 0.99 kg/kWh, a reduction in 264782.66 kg of carbon dioxide can be achieved for production of 267457.23 kWh of electricity as calculated by energy production using poly-crystalline panels covering an area of 14.4 km2 (60% of the total area). The study suggest to move towards a more sustainable approach to achieve energy security as well as protect the environment from polluting gases released as a result of energy production from carbonaceous fuels.
Creative Industries: Challenges and Opportunities in XR Technologies

The paper aims to point out current challenges and opportunities in extended reality (XR) technologies that cover augmented, mixed and virtual reality (AR, MR, VR) within the frame of creative and related industries and current technological progress particularly based on the results of primary research. While the XR technologies struggle with limitations of the proper research on one side, multiple research projects including this one, have shown significant acceptance and potential of the XR technologies, especially in the ongoing digital era accelerated by the COVID-19 situation. The research presented in this paper was held with the small groups of artists in France who had opportunity to test the augmented reality mobile application on artworks from various artists. This and other cited research projects show that the acceptance rate of the XR technologies by the informed audience strongly predominates over its penetration in such population which can be interpreted as significant market opportunity. This milieu has strong impact on the democratization of the XR industry in the recent years with substantial investments by business sector. Meanwhile these technologies have become powerful enough to raise serious concern of their impact on ethical issues, social distancing and other related topics.
Estimasi Laju Pertumbuhan Penduduk Menggunakan Metode Regresi Linier Berganda Pada BPS Simalungun

The Central Statistics Agency (CSA) is a non-departmental government agency that reports directly to the president. The use of data collection is for state data collection for the needs of economic strategies, infrastructure, and so on. So that the CSA institution must be able to predict the estimated rate of population growth. Particularly one of the CSA institutions in North Sumatra, CSA Simalungun, has experienced problems in estimating the population growth rate. Multiple linear regression model is the development of a simple linear regression model. If the simple linear regression model consists of only one independent variable and one dependent variable, then in multiple linear regression the number of independent variables is more than one and one dependent variable. The stages carried out in the data mining process begin with data selection from source data to target data, the preprocessing stage to improve data quality, transformation, data mining and interpretation and evaluation stages which produce output in the form of new knowledge which is expected to make a better contribution.