Reviewerly/exHarmony huggingface dataset:
Robots, artificial intelligence, and service automation (RAISA) technologies in the Egyptian hotel sector: A current situation assessment

In the Egyptian marketplace, particularly in the tourism and hotel sector, there needs to be more research on artificial intelligence in the hotel sector.Artificial intelligence (AI) is the newest technological trend in our daily lives.Around the world, the tourist and hospitality industries rely heavily on robots (R), artificial intelligence (AI), and service automation (SA) (RAISA) technology.However, research into the topic in the Egyptian tourism and hospitality industries has been largely ignored.This research aims to examine the use of RAISA technologies in the hotel industry in Egypt.While primary data was gathered through an empirical study conducted using a depth semi-structured interview method, qualitative data was collected from a sample of twenty IT managers in the Egyptian hotel sector and analyzed.Secondary data was gathered from studies on (RAISA) technologies in the Egyptian hotel sector.The findings confirmed that robots have no applications in the Egyptian hotel industry.According to the interviewees, the most significant benefits of RAISA are increased service quality, improved performance, reduced human errors, and resolving employee mental and psychological problems.The disadvantages are the significant investments required and the reduced human interactions between customers and employees.
Assisted quantum simulation of open quantum systems

Universal quantum algorithms (UQA) implemented on fault-tolerant quantum computers are expected to achieve an exponential speedup over classical counterparts. However, the deep quantum circuits make the UQA implausible in the current era. With only the noisy intermediate-scale quantum (NISQ) devices in hand, we introduce the quantum-assisted quantum algorithm, which reduces the circuit depth of UQA via NISQ technology. Based on this framework, we present two quantum-assisted quantum algorithms for simulating open quantum systems, which utilize two parameterized quantum circuits to achieve a short-time evolution. We propose a variational quantum state preparation method, as a subroutine to prepare the ancillary state, for loading a classical vector into a quantum state with a shallow quantum circuit and logarithmic number of qubits. We demonstrate numerically our approaches for a two-level system with an amplitude damping channel and an open version of the dissipative transverse field Ising model on two sites.
Blockchain-smart contracts for sustainable project performance: bibliometric and content analyses

Blockchain-smart contracts have emerged as a new value proposition in improving certain aspects of sustainability in projects. However, there is little knowledge on how smart contracts can be leveraged to stimulate sustainable project performance from the integrated perspective. This study aims to capture the latest research development and applications of smart contracts for sustainable outcomes throughout the project lifecycle. Bibliometric and content analyses were conducted to critically review smart contracts and sustainable project performance. The results show that various new applications of smart contracts for sustainability have become more popular in the architecture, engineering, construction, and operation (AECO) industry. A smart contracts-sustainable project performance framework has been developed to fill up the research gaps for improving each dimension of sustainability and the integrated dimensions of sustainability during the project lifecycle. This study renders important implications for promoting sustainable project performance in the context of the engineering, construction, and operation industry, particularly for the required interdisciplinary research and practice in smart contracts.
Introduction to special issue on Agile UX: challenges, successes and barriers to improvement

The integration of Agile software development and User Experience (UX) has become a growing field of research, as both approaches play critical roles in building digital products and services. In this special issue on Agile UX, the current state of the field is explored through a combination of systematic literature reviews and qualitative and quantitative studies. The special issue provide an overview of the key trends, challenges, and successes in combining Agile and UX, and highlight the importance of involving stakeholders throughout development. The shift from plan-driven approaches to Agile UX approaches has brought a focus on human values and a better understanding of the importance of considering users’ needs. We present recent advances in research and practice, showing that Agile UX is a continuous journey towards changing user behavior by delivering value.
AdapTrack: An adaptive FairMOT tracking method applicable to marine ship targets

Ship tracking at sea is faced with the disadvantages of complex sea conditions and the large influence of ship occlusion on the tracker. Therefore, we propose a method called AdapTrack based on On the Fairness of Detection and Re-Identification in Multiple Object Tracking (FairMOT) which is suitable for marine targets. The search strategy of trivial augmentation is used to randomly select suitable data augmentation methods and strengths. Then, based on the FairMOT tracking framework, we change the sampling selection method of positive and negative samples from a two-dimensional Gaussian distribution with the same variances to a two-dimensional Gaussian distribution with different variances. It is limited by the bounding box (bbox) of ground truth. This method can improve the detection algorithm’s fitness to the ship target. At the same time, we use Multi-Object Tracking by Associating Every Detection Box (ByteTrack)’s double-threshold strategy to divide detection bboxes, which improves the matching and inference speed. In the first stage of data association, the high-scoring bbox calculates the cost matrix of data association through the Re-identification (Re-ID) model. In the second stage, the Intersection over Union(IOU) cost matrix is calculated after merging low-scoring detection bboxes and unmatched detection bboxes of the first stage. The method achieves Multiple Object Tracking Accuracy (MOTA) of 36.1, Identification F-Score (IDF1) of 47.3, and Frames Per Second (FPS) of 28.79 on the Singapore-Marine-dataset. Experiments show that this method can better alleviate Identification Switch (ID-switch) and ensure the real-time tracking of complex and changeable ship target tracking at sea.
Improvement Technique for Group Search Optimization Using Experimental Design Method

This study proposes the use of an experimental design approach in GSO, and a systematic approach to deal with the hyperparameter settings of GSOs and to provide stable algorithmic performance of GSOs through the experimental design approach. To address these two issues, this study explores the combination of hyperparameters that can improve the performance of GSOs using a uniform design. In addition, the Taguchi method and optimal operations were used to derive an excellent combination of parameters that would provide the best value and robustness of the function to provide a stable performance of GSO. The validity of the performance of the proposed method was tested using ten benchmark functions, including three unimodal, three multimodal, and four restricted multimodal functions. The results were compared with the t-distribution test in addition to the mean and standard deviation to analyze their validity. The results of the t-distribution test showed that the p-values obtained for both UD-GSO and R-GSO were less than 0.05, indicating significant differences compared with GSO for both unimodal and multimodal functions. Two restricted multimodal functions are not significantly different, while the other two are below 0.05, indicating significant differences. This shows that the performance obtained using UD-GSO and R-GSO is more effective than the original GSO. UD-GSO and R-GSO provide better and more robust results than GSO. The main contributions of this paper are as follows: (i) This study proposes a uniform design approach to overcome the difficulties of setting hyperparameters in GSO. (ii) This study proposes a Taguchi method and optimal operation to provide a robust calculation for GSO. (iii) The method applied in this study provides systematic parameter design to solve GSO parameter setting and robust result obtaining.
The Effect of Attitude and Acceptability of Using Robots in Restaurants on Behavioral Intention

In recent years, it has been seen that technology-based tools have started to take place frequently in our daily lives.This situation is more prominent in organizations such as food and beverage producing human-oriented services.With the increase in technological awareness, it is observed that the tendency of individuals who are curious about creativity and innovation towards businesses that provide smart robotic services is increasing.The aim of this research is to determine the effect of attitude and acceptability of the use of robots in restaurants on behavioral intention.In line with the purpose of the research, relationships were determined with the help of data obtained from the scales developed on the subject.Based on the literature review, five hypotheses were developed.Relationships were tested with the path analysis created within the scope of structural equation modelling.The acceptability of robot use in restaurants by customers has a significant positive effect on behavioral intention, and this variable has the greatest effect on behavioral intention.In addition, "experience" and "advantage" dimensions of attitude towards robot use have significant positive effects, "disadvantage" dimension has a negative effect on behavioral intention.Lastly, according to R-square, 82.6% of behavioural intention is explained by attitudes and acceptability towards the use of robots in restaurants.
A Novel Image Encryption Technique with Four Stage Bit-Interspersing and A 4D-Hyperchaotic System

This paper introduces a new technique of color image encryption that includes four stages of bit interspersing and a 4D-hyperchaotic system. At first, the pixel values for different RGB channels of a plane color image were represented by an 8-bit binary number. The bit interspersing operation has been implemented on the bit stream generated by considering a particular block size for each color channel and reshaping it to the original size. The cipher image was then constructed by performing a bit XOR operation on the resultant image and the chaotic sequences generated by a 4D hyperchaotic system. The initial state variables of the said chaotic system have been developed from a 32-character secret key. This operation has been repeated three times, considering different block sizes of the newly generated cipher image after each stage. The main strengths of the proposed algorithm are the bit interspersing and image-dependent chaotic key base pixel substitution by bitwise XOR operation. A set of standard security tests are conducted to test the reliability of the suggested encryption method. Comparing the crypto-parameters to other recent works, we find that the proposed algorithm is better than the other methods.
KEYWORD BASED TEXTBOOK RECOMMENDATION SYSTEM USING KNN ALGORITHM

During the last few decades, with the rise of social media objects, web objects and many more, recommender system played a very vital role in this phenomenon.These objects introduced recommender systems and these recommender systems have taken more and more place in current situation.From e-commerce objects to online objects everywhere there exists a recommender model to provide user ease of use and ease of requirement.In a very general way to describe a recommender system they are set of algorithms or algorithms aimed to provide a set of suggestions and relevant information and requirement to the user.
Fostering StudentsDigital Literacy In The Age Of The Internet In The Pandemic Era

Being digitally literate is an ongoing process in which students must consistently keep up by actively learning and trying out new technology tools and resources, building skills with these technologies, and most importantly using this technology to meet their needs and achieve their goals. This paper considers how students can respond to digital media literacy in the internet era. It begins by exploring digital literacy and digital media literacy more specifically. Then, it approaches how digital media should be selected according to students characteristics, authenticity, appropriacy and sufficiency and then emphasizes the importance of the internet and it wide ranging utility. It argues that the advantages of digital technology give valuable contribution for the students. The paper aims to explore extensive use of potential digital media to empower the students, enlarge their knowledge, enhance their communication skills and enjoy better living condition and elevated status in society. The article concludes that digital literacy should be seen as part of global education in era of internet and the use of digital media properly.&#x0D; Keywords: Digital literacy; internet; pandemic era; digital media
Abstractive Text Summarization using Deep Learning

Abstract: The number of text records has increased dramatically in recent years, and social media structures, including websites and mobile apps, will generate a huge amount of statistics about non-text content. structure, including blogs, discussion forum posts, technical guides, and more. Statistics, which constitute human behavior and intuitive thinking, consist of many records that are relatively difficult to manage due to their large number and various factors. However, the demand for statistics summarizing textual content is increasing. Text summarization is a way of analyzing unstructured text and converting it into meaningful statistics for evaluation that will produce the necessary number of useful records. This study describes a deep learning method for effectively summarizing textual content. As a result, the reader receives a condensed and focused model of the unique textual content.
Designing High-Fidelity Zeno Gates for Dissipative Cat Qubits

Bosonic cat qubits stabilized with a driven two-photon dissipation are systems with exponentially biased noise, opening the door to low-overhead, fault-tolerant and universal quantum computing. However, current gate proposals for such qubits induce substantial noise of the unprotected type, whose poor scaling with the relevant experimental parameters limits their practical use. In this work, we provide a new perspective on dissipative cat qubits by reconsidering the reservoir mode used to engineer the tailored two-photon dissipation, and show how it can be leveraged to mitigate gate-induced errors. Doing so, we introduce four new designs of high-fidelity and bias-preserving cat qubit gates, and compare them to the prevalent gate methods. These four designs should give a broad overview of gate engineering for dissipative systems with different and complementary ideas. In particular, we propose both already achievable low-error gate designs and longer-term implementations.
Effect of transformations on the success of adversarial attacks for Clipped BagNet and ResNet image classifiers

Our paper compares the accuracy of the vanilla ResNet-18 model with the accuracy of the Clipped BagNet-33 and BagNet-33 models with adversarial learning under different conditions. We performed experiments on images attacked by the adversarial sticker under conditions of image transformations. The adversarial sticker is a small region of the attacked image, inside which the pixel values can be changed indefinitely, and this can generate errors in the model prediction. The transformations of the attacked images in this paper simulate the distortions that appear in the physical world when a change in perspective, scale or lighting changes the image. Our experiments show that models from the BagNet family perform poorly on images in low quality. We also analyzed the effects of different types of transformations on the models' robustness to adversarial attacks and the tolerance of these attacks.
Implementation of Town and School Watching for Disaster Education to the Communities in Sidomulyo Village, Pronojiwo, Lumajang

The eruption of Mount Semeru on December 4, 2021, caused a fairly high death toll of up to 50 people. The high number of fatalities is caused by the lack of mitigation capacity and the absence of community involvement in mitigation efforts. Increased mitigation capacity can be done by presenting disaster education to the communities. Thus, we applied the concepts of school watching and town watching in Pronojiwo District, Lumajang Regency. School watching was implemented in eight schools located at Sidomulyo Village. We also carried out town watching in Sidomulyo Village and brought out ±33 residents to the Sidomulyo village hall. The implementation of school watching and town watching in Pronojiwo District can increase community involvement in disaster mitigation efforts and public awareness of mitigation efforts.
Pengembangan Sistem Manajemen Bank Sampah berbasis Web untuk mewujudkan keberhasilan Ekonomi Sirkular di Masyarakat

&#x0D; &#x0D; &#x0D; &#x0D; This research will be conducted at the Solusi Hijau Main Garbage Bank in the Gunung Sindur District, Bogor Regency. The Solusi Hijau Waste Bank still uses a manual recording system that is easily lost, inefficient, and not dynamic. Therefore it is necessary to make a Web-based Waste Savings Application that can become the main activity facility for the Green Solutions Main Garbage Bank. This application will be used as an interactive interface for Customers and Unit Waste Banks as well as the general public as Prospective Customers or Prospective Management Unit Waste Banks so that they can maximize the performance of the Waste Bank in its development. The Web-based Waste Savings application is a continuation of basic research that has been done before, namely to create digital applications that are utilized by waste banks and the community so that waste banks can become a forum for public education in terms of waste handling and environmental management as well as generating community economic resources. Systems Development Life Cycle (SDLC) is implemented as an Application development method. SDLC is a system development cycle in making waste bank applications by applying the waterfall method. The results of this research in the future are directed to be developed into a standard for Waste Saving System Applications in the community.&#x0D; &#x0D; &#x0D; &#x0D;
Importance of Reflective Practice in the Teaching Profession during the COVID-19 Pandemic

The research aimed to determine the importance of reflective practice in the teaching profession during the COVID-19 pandemic. To obtain the required information, 85 teachers were selected. Teachers from both public and private educational institutions in the city of Azogues, Cañar province. Most of the participants were female and over 40 years of age. The teachers taught their subjects at the General Basic Education level. A demographic analysis was carried out for data collection. A questionnaire was used in which questions were included to determine the degree of application of reflective practice by the educators. The answers were provided based on a Likert scale with 5 response options. The results obtained showed that not all educators apply reflective practice. Teachers who apply reflective practice found it easier to adapt to the needs of students in the context of the pandemic. Difficulties in implementing improvements in pedagogical planning were also recognized.&#x0D; &#x0D; Received: 8 January 2023 / Accepted: 20 February 2023 / Published: 5 March 2023
Content privacy enforcement models in decentralized online social networks: State of play, solutions, limitations, and future directions

In recent years, Decentralized Online Social Networks (DOSNs) have been attracting the attention of many users because they reduce the risk of censorship, surveillance, and information leakage from the service provider. In contrast to the most popular Online Social Networks, which are based on centralized architectures (e.g., Facebook, Twitter, or Instagram), DOSNs are not based on a single service provider acting as a central authority. Indeed, the contents that are published on DOSNs are stored on the devices made available by their users, which cooperate to execute the tasks needed to provide the service. A specific form of cooperation is to store the content published by a user on other peers’ devices as well, hence dramatically enhancing availability. Consequently, such contents must be properly protected by the DOSN infrastructure, in order to ensure that they can be really accessed only by users who have the permission of the publishers. As a consequence, DOSNs require efficient solutions for protecting the privacy of the contents published by each user with respect to the other users of the social network. This is exactly the focus of this paper. In particular, we investigate and compare the principal content privacy enforcement models adopted by current DOSNs evaluating their suitability to support different types of privacy policies based on user groups. Such evaluation is carried out by implementing several models and comparing their performance for the typical operations performed on groups, i.e., content publish, user join, and user leave. In detail, we show that the join operation incurs a similar cost for all the privacy enforcement models and groups, while for the leave operation performance is greatly affected by the selected solution, which must be evaluated on a case-by-case basis depending on both the type and the activity level of the group—as analytically detailed in our contribution. Further, we also highlight the limitations of current approaches and show future research directions. The provided contributions, other than being interesting on their own, set a blueprint for researchers and practitioners interested in implementing DOSNs, and highlight a few open research directions.
Utilization of Blockchain for Marine Products Tracking

Many marine product companies currently have not implemented blockchain potentials in tracking systems. There could be found many errors in the transactions record. The purpose of this research is to implement blockchain as a fraud prevention system for transactions in marine product companies. This research is qualitative-exploratory research with data collection using documentation techniques from related literature. This study concludes that Blockchain can be used as an alternative to fraud prevention. Blockchain can be used because there is transparency with a distributed system, which makes the whistleblowing system more effective and independent, in fully implementing the principles of GCG (Good Corporate Governance). The results of the advanced system designed at a marine product company are to facilitate data collection of all goods to be sent this providing high-security guarantees because it implements a blockchain security system in this system, and places an integrated tracking system so that data and goods sent during the transaction can be tracked.