Reviewerly/exHarmony huggingface dataset:
Utilization of Information and Communication Technologies (ICTs) for Managing Students’ Academic Records in Nigerian Schools

This study examined the utilization of Information and Communication Technologies (ICT) for managing students’ academic records in Nigerian schools. A descriptive survey method was used for the study. The population of the study comprises 131 teachers in selected secondary schools in Kogi. The multi-stage sampling procedure was adopted to select 97 teachers, both male and female as samples in six (6) secondary schools in the three districts of Kogi State. Five (5) research questions guided the study. Percentile rank and mean scores were used as statistical tools for data analysis. The findings revealed that ICT facilities available for managing students’ records in the school include computers, printers, handsets, photocopiers, and diskettes, among others. The study found that insufficient knowledge and skills on how to operate ICT equipment, ignorance of the advantages of ICT devices, principals' reluctance to use ICT gadgets, inadequate physical facilities/equipment, sporadic disruption of electricity supply and inadequate funds to provide ICT devices were challenges in using ICT to manage students’ academic records in the secondary schools under study. The study, among others, recommended that school teachers and principals should be trained in the use of the latest information technologies and gadgets to be effective and efficient in their performances. Also, Information and Communication Technologies (ICTs) should be incorporated into the school curriculum, especially at the secondary school level and the government should put in place power plants in every secondary school in order to solve the issue of disruption in power supply.
Hybrid moth-flame optimisation algorithm with differential evolution for visual object tracking

The improvement of the metaheuristic algorithms is one of the exciting topics to investigators in current years to resolve the optimisation and engineering problems. One of the population-based search methods, i.e., moth-flame optimisation algorithm (MFO), is eminent by easy execution, low limits, and high speed. On the other hand, the MFO process has shortcomings; for instance, the verdict of local minimum as a substitute for global minimum and weakness in global pursuit proficiency. In this paper, to resolve these shortages, the MFO algorithm is integrated with differential evolution (DE) and proposed a new hybrid method called MFO-DE. The exploration ability of the MFO algorithm is improved and existence trapped in the local minimum is prohibited by a mixture of the MFO and DE in the MFO-DE algorithm. The proposed algorithm was tested on the set of best-known unimodal and multimodal benchmark functions in various dimensions. Furthermore, MFO-DE is applied to visual object tracking as a real-life application.
Heterogeneity in making: Findings, approaches, and reflections on inclusivity in making and makerspaces

Making, that is, the hobbyist and technologically based creation of things, has been associated with many benefits. It is considered to contribute to the development of skills and to enable participation in innovation, and even democracy. At the same time, institutionalized making (in makerspaces, FabLabs) is known to be exclusive as members of such spaces are very often young well-educated white men. This is in contradiction to the promise and self-understanding of the maker culture, which aims to be open and inclusive. In the past 3 years, we, a group of researchers, makers, fablab employees, hackerspace operators, and artists, have engaged with such disparities in a collaborative research project. We inquired into barriers that women * and other underrepresented groups experience, created visions to change the status quo, and implemented smaller and bigger interventions in different spaces (fablab, hackerspace, and makers' homes) to explore their impacts. This article discusses findings, approaches, and foremost, reflections and experiences. In addition to presenting selected insights from our explorations, we pay particular attention to the tensions and challenges that we encountered during our research endeavors. Many of those are rooted in our own roles, perspectives, and backgrounds, which are multiple, sometimes conflicting, troubling, frustrating, yet enriching, and rewarding. In the form of a written conversation among project members, we present those different viewpoints, connect them where possible, and oppose them where needed. We conclude by articulating tensions that we see as characteristic regarding making and the research around it.
Bridging social marketing and technology in the disability field: an empirical study on the role of cybernetic avatar and social inclusion

Purpose This study aims to determine the perception and attitude of consumers toward the presence of cybernetic avatars (CAs) as part of a social inclusion initiative. Design/methodology/approach A mixed method was used to conduct the study using facial recognition expressions and surveys. Three studies were conducted. Study 1 examines consumers’ attitudes and perceptions of a CA and what it can do to promote social inclusivity among people who have mobility disabilities but wish to work. Study 2 tests a conceptual model to determine the factors that affect consumers’ intention to visit an establishment that uses CAs as their employees. Study 3 extends Study 2 and tests two moderators predicted to influence consumers’ attitudes toward CAs and their intention to visit an establishment that uses CAs. Findings The results show that consumers generally accept and are excited about such technological developments. Study 2 further supports this positive perception with its conceptual model. Study 3 provides insights into how the moderating factors influence a consumer’s attitude toward CAs and their intention to visit the establishment. Between consumers who have a mobility disability and those who do not, those who have mobility disabilities showed a more positive attitude and intention to patronize such an establishment. Originality/value Studies on CAs are still in the infancy stage. This study provides insight into how society can use technology to promote social inclusion, contrary to prior opposing arguments towards integrating robots into society.
Towards an Infrastructure Cost Model for Blockchain-Based Applications

Blockchain has become a core technology for developing decentralized applications allowing the safe interaction of untrusted actors. Given the early stage of blockchain research, the current literature has not addressed several inherent challenges related to system and software engineering, including the infrastructure costs and benefits. These are critical to evaluate the feasibility of any system and guide architectural choices during its design, implementation, and exploitation. This work presents a model for evaluating the infrastructure costs and benefits in blockchain applications. First, we propose a taxonomy to classify the application related transactions. Then, we propose a model to evaluate the infrastructure costs and benefits in applications using either public or private blockchains. The model is based on parameters that describe the systems and can be easily identified at any stage of the application life cycle. To illustrate the model validity, we quantitatively analyze a real use case. The results highlight the inherent complexity of characterizing the costs and benefits of blockchain applications, while the proposed models facilitate several aspects of this process. Moreover, it provides a solid ground to evaluate a blockchain-based system from the early stages of the development, eventually supporting the entire life cycle.
Sharding-Based Proof-of-Stake Blockchain Protocol: Security Analysis

Blockchain technology has been gaining great interest from a variety of sectors including healthcare, supply chain, and cryptocurrencies. However, Blockchain suffers from its limited ability to scale (i.e., low throughput and high latency). Several solutions have been proposed to tackle this issue. In particular, sharding proved that it is one of the most promising solutions to Blockchain scalability. Sharding can be divided into two major categories: (1) Sharding-based Proof-of-Work (PoW) Blockchain protocols, and (2) Sharding-based Proof-of-Stake (PoS) Blockchain protocols. The two categories achieve a good performance (i.e., good throughput with a reasonable latency), but raise security issues. This article focuses on the second category. In this paper, we provide a probabilistic model to analyze the security of these protocols. More specifically, we compute the probability of committing a faulty block and measure the security by computing the number of years to fail. Finally, we evaluate the effectiveness of the proposed model via a numerical analysis.
A Primer on Anomaly and Fraud Detection in Blockchain Networks

Blockchain technology is a distributed ledger system that allows multiple parties to record and verify transactions in a secure and transparent manner. However, blockchain networks are vulnerable to anomalies and frauds that can have serious consequences for the integrity and security of these networks. In this primer, we provide an overview of the definition and properties of blockchain technology, and discuss the types and examples of anomalies and frauds that occur in these networks. We also examine the techniques and technologies that are used to detect and prevent these attacks, including statistical approaches, machine learning approaches, game-theoretic approaches, digital forensics, reputation-based systems, and risk assessment systems. We present case studies of anomaly and fraud detection in real-world blockchain networks, and discuss the lessons learned from these cases and their implications for future research and practice. We also identify emerging trends and challenges in the field, and discuss potential future research directions and technologies. This primer is intended as a resource for practitioners and researchers in the field of anomaly and fraud detection in blockchain networks, and aims to provide a technical and comprehensive overview of this growing and important field.
An Optimal Approach for Multi-class Object Detection

Object detection in an image aims to point out all the desired objects in the target image and considers the positional enlightenment to obtain machine perspective knowledge. In object detection vanishing gradient has been the most significant problem that can occur, it results in a model with many layers being specified to unable to learn on a specific dataset. It could cause models to a low-grade solution. To get grip on the obstacles, this paper has analyzed certain algorithms for precise object detection from a customized dataset. In this approach, multiple objects in an image have been classified and localized with the help of Mask Region Colvolutional Neural Network (R-CNN). This work is pulled off using a regional convolutional neural network, pixellib, OpenCV, and TensorFlow, resulting in a preferable desired output. Implementing this technique and algorithm, based on deep learning, which is also based on machine learning requires framework understanding. The experimental result and analysis are done with multiple classes of an image to verify the efficiency of the mask R-CNN technique. The algorithm has been compared with other existing object detection strategies to establish the accuracy and reliability of the concerned determined algorithm. The systematic execution enabled clarification of the suggested technique to be precise in analyzing multi-class object in an image.
Execution Time Program Verification with Tight Bounds

This paper presents a proof system for reasoning about execution time bounds for a core imperative programming language. Proof systems are defined for three different scenarios: approximations of the worst-case execution time, exact time reasoning, and less pessimistic execution time estimation using amortized analysis. We define a Hoare logic for the three cases and prove its soundness with respect to an annotated cost-aware operational semantics. Finally, we define a verification conditions (VC) generator that generates the goals needed to prove program correctness, cost, and termination. Those goals are then sent to the Easycrypt toolset for validation. The practicality of the proof system is demonstrated with an implementation in OCaml of the different modules needed to apply it to example programs. Our case studies are motivated by real-time and cryptographic software.
Embedding Functional Logic Programming in Haskell via a Compiler Plugin

We present a technique to embed a functional logic language in Haskell using a GHC plugin. Our approach is based on a monadic lifting that models the functional logic semantics explicitly. Using a GHC plugin, we get many language extensions that GHC provides for free in the embedded language. As a result, we obtain a seamless embedding of a functional logic language, without having to implement a full compiler. We briefly show that our approach can be used to embed other domain-specific languages as well. Furthermore, we can use such a plugin to build a full blown compiler for our language.
At the margins of grammar

This paper focuses on the variable placement of the particle of particle verb constructions in Dutch and German. In particular, the option to place the particle in first sentence position is studied in a judgment task. We asked native speakers of Dutch to judge utterances which differ with respect to the semantic transparency of the particle and with respect to the distance between particle and verb. In spite of an overall awkwardness of constructions with a fronted particle, the factors under investigation turned out to influence their well-formedness. Our observations thus raise some questions about the acceptability and the grammaticality status of such dubious structures. When comparing our results to those found by Trotzke et al. (2015), who did a similar study for German, we find that the patterns in the two languages are similar but that there are nonetheless some important differences to note. We suggest that this discrepancy has to do with the more flexible use of the first sentence position in German.
Real-Time Trajectory Generation of a Quadrotor UAV with Load Suspended from a Pulley

Quadrotor UAV carrying a payload with a cable can be a prominent setup for aerial transportation. However, it is challenging for the suspended load system to navigate through tunnel-like obstacles if the vertical gap is narrower than the length of the cable. We aim to resolve this problem by adopting the pulley mechanism which controls the cable length. This paper presents a model predictive control based real-time trajectory generation algorithm for a quadrotor with its load suspended from a pulley, or the quadrotor-pulley system. We design a cost function that can be generally applied for avoiding obstacles with rectangular surfaces. Using the cost function, an optimal control problem is formulated, which is then solved by implementing model predictive control algorithm with sequential quadratic programming solver. We employ the state-of-the-art real-time iteration scheme to promote computational efficiency of the algorithm. The presented algorithm is demonstrated with simulations, where trajectories for the quadrotor-pulley system were successfully generated. Collision-free trajectories through tunnels with various heights and lengths were generated in real-time, thus validating the robustness of the algorithm.
Comparative Analysis of IR-IR Image Matching Using Classical Techniques

In this paper, after finding feature points and description using classical feature detection and description techniques, this paper compares and analyzes the performance of each classical technique by matching descriptors of the IR-IR images with the FLANN technique and matching with the Homography technique. Usually, these classical techniques are often used in EO images, but recently, in technologies that require a high level of detection such as defense technology, not only EO images but also IR images are being used. Therefore, classical feature detection and description techniques specialized for reflected light are applied to IR-IR images, and their performance is compared, and the limitations of classical techniques are examined. Classical techniques to use include SIFT, SURF, and KAZE.
PTZ Camera Control on Robot Telemedicine Service for Infectious Diseases

Attentions for medical assistance services to isolated patients have increased due to recent infectious diseases. In the isolation case, telemedicine service is valuable because of no direct contact between infected patients and medical staff. This work proposes a pan-tilt-zoom (PTZ) camera control system that provides convenience for medical staff during telemedicine. Our automatic camera controller tracks the region while maintaining the best viewpoint when medical staff selects a region of interest, e.g., a patient’s symptoms or wounds. In order to develop the system, several attributes of object trackers suitable for the proposed control system were explored. Based on the evaluations of object trackers, we found that the scale-variance property of object trackers is significant to our PTZ controller. As a result, the proposed approach using a scale-variant object tracker can control the pan, tilt, and zoom to support a convenient telemedicine service without annoying manual viewpoint control.
Generating Even More Chaotic Instances in Hardware

It is well known that multiplication inside a computer does not follow the associative property because of roundoff effects. It is possible to use this fact to generate other different chaotic instances of chaotic maps or oscillators when a multiplication of three terms appears. Chaos is very sensitive to small changes in the initial conditions and amplifies these small rounding effects. We use this condition to build different chaotic instances, which give different results, of the Lü oscillator and the 2D map, and we show one application to create new instances of a pseudo random number generator using the 2D map. Both chaotic systems are simulated in software and in hardware within an FPGA where another 144 different 2D map instances and 81 different Lü oscillators can be created. To best of our knowledge, it is the first paper that analyze the construction of new chaotic entities by using the roundoff effects.
An Alternative Computation of the Entropy of 1D Signals Based on Geometric Properties

The objective of this work is to present a novel methodology based on the computation of a couple of geometric characteristics of the position of the data points in 1D signal to propose an alternative estimation of signal entropy. The conditions to be fulfilled by the signal are minimal; only those necessary to meet the sampling theorem requirement are enough. This work shows some examples in which the proposed methodology can distinguish among signals that cannot be differentiated by other in-use alternatives. Additionally an original example where the usual ordinal pattern algorithm to compute entropy is not applicable, is presented and analyzed. The proposal developed through this work carries some advantages over other alternatives and constitutes a true advancement in the pathway to compute the distribution function of the sequential points of 1D signals later used to compute the entropy of the signal.
Testing the Validity of Laplace Model Against Symmetric Models, Using Transformed Data

In this paper, we first present three characterizations of Laplace distribution and then we introduce a goodness of fit test for Laplace distribution against symmetric distributions, based on one of the transformations. The power of the proposed test under various alternatives is compared with that of the existing tests, by simulation. To show the behavior of the proposed test in real cases, two real examples are presented.
An Analysis of Lightweight Cryptographic Algorithms for IoT-Applications

With the arrival of advanced technologies, IoT has enabled the connection of many devices that can collect huge amounts of data. IoT security requirements are therefore supreme. Cryptography is used to secure the confidentiality, data integrity, authentication and control access to networks. To provide a complete overview of this field, we have compared some existing algorithms based on hardware and software performance and expectations of different attacks. We also discussed the requirement and direction of novel research in lightweight cryptography to improve security and performance. This paper presents the performance comparison of their memory, latency & throughput, Area (GE), Key & Block size and other parameters of hardware and software efficient LWC algorithm. Primarily for lightweight block ciphers and further shows new research directions for developing new algorithms with the performance, security, and cost characteristics.
Image Encryption Algorithm Based on Timeout, Pixel Transposition and Modified Fisher-Yates Shuffling

Social media has become an inseparable part of our lives which has increased the sharing of images across multiple platforms. To enhance the security, various image encryption algorithms are being used but there are still are a few areas that can be improved. First, the data transmission mostly includes the original image which can be secretly read by a middle man. Second, the sender loses control over the image after sharing. Third, generally, encryption keys are of fixed length and long which take up more memory & efforts in sharing them securely. Fourth, the key-space of algorithms is fixed, thus allowing an upper limit estimation to any brute force attack. In our work, we propose a timeout based symmetric key column-row transposition encryption algorithm for images providing the same level of security irrespective of the key size. The timeout feature allows the sender to specify a time until when the image can be decrypted by anyone. With the algorithm, we present an Android Library that implements this algorithm and provides ability to prevent unauthorized sharing of images in apps. To support other platforms as well, we present NPM & Python Package. Various performance measures were used to test the efficacy of the algorithm.
A Career Recommendation Method for College Students Based on Occupational Values

The numerous recruitment information and the information asymmetry between college majors and work posts make it difficult for college students to seize the job opportunities that conform to their occupational values, and the employment success rate is always at a low level. The effect of current college student career recommendation systems is usually unsatisfactory, and the existing systems haven’t fully considered the role of college students’ occupational values in instructing their employment. To fill in this research blank, this paper studied a career recommendation method for college students based on occupational values. At first, the paper proposed a collaborative filtering algorithm based on the features of collect students’ occupational values, introduced a few features that can affect their occupational values, assigned weight values to these features, and gave the method for determining the weight. Then, based on the principle of the Kruskal’s algorithm (the minimum spanning forest), this paper modified the K-Means algorithm and clustered the features of occupational values. At last, the paper elaborated in detail the principle of generating career recommendation results for college students based on occupational values, and used experimental results to verify the correctness of the proposed career recommendation algorithm.
Spatial separation of collinearly emitted broadband frequency-correlated photon pairs

The authors demonstrate the efficient separation of broadband frequency-entangled photon pairs generated in the same spatial and polarization mode. Entangled photons with a broad bandwidth of 90 nm are successfully separated using time-reversed Hong-Ou-Mandel interference.