Reviewerly/exHarmony huggingface dataset:
The Impact of Business Development, Strategic Planning, Business Outsourcing, and Organizational Change towards the Use of Technology among SME’S in Saudi Arabia

This study is aimed to investigate the high rate of SMEs failure in Saudi Arabia after operating for a year.In contrast, the study evaluated the impact of restructuring technologies in SMEs.Besides, finding suitable technology tools that match the organization's needs and boost business sustainability.The research study adopted a descriptive research design.The study applied primary data, where a structured questionnaire was used to collect data.The population of the study was 404 employees of SME's in Saudi Arabia.The data was analyzed using the Statistics Package for Social Sciences (SPSS 27.0) and was interpreted using Cronbach's Alpha reliability test, Pearson Correlation, and Multiple Linear Regression.The findings were presented in figures and tables with percentage scores, mean, and standard deviation.The study found that business development had the strongest relationship with technology, where using the right tools, materials, and equipment helps firms with ultimate possibility results.The study recommends that entrepreneurs and shareholders put in more effort to understand their business type on what best technology can help with a better surplus and give them satisfaction while working to deliver results, thus enhancing productivity.This study will be useful to the government of Saudi Arabia to determine policies affecting business development and make it stabilize.Besides, it will help SME's to choose the factors that affect a firm in reducing cost, maximizing effective operation and revenue, and stabilizing the firm for a longer period.
The Representation and Performance of Responsive Web Page Based on HTML5 and CSS3

Abstract: Responsive web design solves the compatibility problems of web pages displayed at different resolutions, different platforms, and different screen sizes and also brings a high-quality experience to users. Based on the research on responsive web design and related technologies like HTML5 and CSS3, this paper expounds on the design ideas and key technologies of responsive design with a responsive enterprise website. Response web design based on HTML5 and CSS3 has proved to be possible and valuable.
An Interlinked Relationship between Cybercrime &amp; Digital Media

Today, the internet has become so interwoven in our lives that it is difficult to fathom life without it. Technology advancements have led to the emergence of digital media as a significant aspect of our lives, the growing use of mobile information, and social media, which provide platforms for easy global interaction. Technology has many advantages, but it also puts people at risk. As the amount of crimes committed online has multiplied, digital media has become a haven for crooks. The advantages of the internet are no longer a mystery to anyone, and the most recent social media platform is open to anyone. The anonymity it offers and the creation of a genuine atmosphere where users may connect, swap photos, meet others, play games, fall in love, argue, etc. without ever having met in person are the main draws of social media. The exploitation of a victim's name, residence, location, and other personal information by criminals is now, however, all too typical, particularly in situations involving women. Due to the confidentiality and fakeness that are present in social media, as well as jurisdictional concerns, cybercrime has become more prevalent among people of all ages and is now a global problem. The study describes and discusses the effects of digital media on young people as well as the reasons behind the increase in cybercrime on social media. The study addresses the common types of cybercrime that happen there as well as the role of the law in dealing with and preventing it on social media. The research makes numerous recommendations for completely and sufficiently teaching the nation's children about the dangers of cybercriminals.
A Step Towards Automated Functional Assessment of Activities of Daily Living

Current activity recognition approaches have achieved a great success due to the advancement in deep learning and the availability of huge public benchmark datasets. These datasets focus on highly distinctive actions involving discriminative body movements, body-object and/or human-human interactions. However, in real-world scenarios, e.g., functional assessment of a rehabilitation task, which requires the capability of differentiating the execution of same activities performed by individuals with different impairments, their recognition accuracy is far from being satisfactory. To address this, we develop Functional-ADL, a challenging novel dataset to take action recognition to a new level. Compared to the existing datasets, Functional-ADL is distinguished in multi-label and impaired-specific executions of different Activities of Daily Living (ADL) to contribute towards vision-based automated assessment and rehabilitation of physically impaired persons. We also propose a novel pose-based two-stream multi-label activity recognition model consisting of a spatial and a temporal stream. The proposed approach significantly outperforms the state-of-the-art by a considerable margin. This new Functional-ADL dataset presents significant challenges for human activity recognition, and we hope this could advance research towards activity understanding and monitoring.
EXPECT-NLP: An Integrated Pipeline and User Interface for Exploring Patient Preferences Directly from Patient-Generated Text

Understanding patient preferences for drug therapies can help to inform drug development, reimbursement decisions by insurers, and shared decision-making by patients and clinicians. Typically, preferences are assessed using lengthy and costly studies involving qualitative analysis of interviews and focus groups along with complex stated preference surveys. We have developed a more efficient method that allows users (e.g. health services researchers, drug developers, or market researchers) to assess patient preferences semi-automatically from online patient-generated text using a weakly supervised aspect-based sentiment analysis pipeline. To facilitate users’ ability to generate new insights on patient preferences using our system, we have developed a dedicated user interface, which we present here. Our hope is that this will enable users to conduct frequent and adaptable assessments of patient preferences for drug therapies over-time.
The Implementation of the Balanced Scorecard for Improving Quality of Education

The Balanced Score-Card is a principle of managing professional and balanced organizational institutions concerning financial and non-financial aspects. The BSC can be applied to for-profit and non-profit institutions, such as the Putra Satria educational institution. This study uses a qualitative-descriptive approach. It is collecting data by interview, observation, and documentation notes. Data analysis refers to the balanced scorecard theory, which includes financial and non-financial aspects. The result is that the BSC has been implemented well by the Putra Satria Junior High School so that the school has a financial surplus. In addition, internal and external customers aspects of customer satisfaction feel satisfied with school management services. Internal business aspects by carrying out innovations in facilities and infrastructure that have been carried out by school management, as well as innovations in teaching (teaching and learning activities), carried out by teachers. In addition, it was found that the school cares for the development of human resources for teachers and employees through courses, training, seminars, or academic activities that support improving their education.
Decentralization using Blockchain as a Service

Abstract: Due to its immutability, traceability, anonymity, and transparency as a decentralised distributed ledger, blockchain has seen significant development in cryptocurrencies and production as a new trend. The emergence of Blockchain-as-a-Service (BaaS) in the interim aids in the mitigation of the Blockchain system complexity and management challenges make it simpler for developers to concentrate on implementing business logic. However, the majority of current BaaS solutions are hosted by cloud providers, increasing the risk of vendor lock-in and undermining blockchain's intrinsic trustlessness. Although current BaaS systems use edge computing or the cloud as their infrastructure, their availability is constrained by the availability of network connections and the data centre itself. Most developers or teams find it challenging and expensive to create, maintain, and watch over a blockchain network that supports their apps due to the intricacy of blockchain technology. The majority of regular developers or teams are unable to guarantee the dependability and security of the blockchain system, which in part lowers the calibre of their programmes. The BaaS platform we create in this study,BaaS, offers blockchain services across cloud computing environments, including network deployment and system monitoring, smart contract analysis, and testing. Based on these services, developers don't have to worry about maintaining and monitoring the system and can instead concentrate on the business code to investigate how to apply blockchain technology to their business scenarios more effectively.
Knowmads as Possible Mutants of Knowledge Workers in the Brave post-COVID World

The purpose of the present study is to capture the specific forces that are intensifying in the COVID-19 context, which stimulate the adaptation of some knowledge workers characteristics into mutated traits – the traits of knowmads. Also, the present study aims at exploring how this transformation is presented in the literature. Defined by John Moravec, the term "knowmad" describes those workers that stand out by being proficient in working with anybody, anywhere, at any time. As an autonomous knowledge worker apt to develop business ecosystems in real, virtual, or hybrid working environments, knowmads are not confined to employees of a single organization. A steady evolution in this respect has been visible for the last decade already. Still, it accelerated during COVID-19 pandemics, due to the global economic crisis. Studies show that the trend will continue to develop in the post-pandemic environment, as the prevalence of flexible, remote work during pandemics has increased from a niche occurrence to a widespread practice over the past nearly two years. Because of the COVID-19 pandemic, an unprecedented number of employees worked from remote locations, on flexible schedules, and were not under the direct control of their supervisors. This study aims to explore and capture the main forces powered by COVID-19 pandemics, which stimulated the change of certain knowledge workers characteristics into a mutation towards knowmads characteristics. The authors implemented a critical literature analysis, and a computer-aided bibliometric analysis performed with the help of VOSviewer version 1.6.17 software. Findings demonstrate that the COVID-19 context boosted the transformation of the knowledge workers into knowmads, and the process is not going to end soon. Also, the search performed with VOSviewer shows a significant absence of knowledge concerning the transformation of corporate knowledge workers into self-managed knowmads.
The Influence of Product Gender on Frequency of Code-switching in Online Advertisements: A Study on the Saudi Digital Marketing Platform Maroof

Code-switching can be a successful marketing strategy in online advertisements even when the targeted audience is monolingual. Yet, little research was conducted on its frequency or attitudes towards it, especially in the Middle Eastern context. Additionally, most current research on code-switching is on bilingual communities. Such gaps in the literature contribute to the significance of the current study. Therefore, this paper is an attempt to investigate whether gender is a factor influencing both the frequency and the preferences of code-switching in online written advertisements listed on Maroof, a Saudi governmental platform for verifying local online shops. Two questions were formulated to determine if code-switching frequency in advertisements for male and female products is statistically different and to check whether the targeted recipients have different code-choice preferences depending on the gender for which the product is made. A textual analysis and an online questionnaire were employed to answer these research questions. Fifty randomly selected online shops containing products for women were compared with fifty other shops advertising men’s products. The advertisements were mostly Arabic monolingual for both groups (82% in men’s products and 76% in women’s products). However, the group of women’s products had a significantly higher frequency of code-switching, with a p-value of 0.46. A questionnaire completed by 936 Saudi respondents revealed that English monolingual advertisements are favored by a considerable number of respondents, despite their complete absence in the sampled advertisements. The questionnaire also revealed that code-switching preferences seem to be influenced by linguistic constraints.
Rule‑combining Morphotactics and Morphological Theories

Situating the rule-combining approach to morphotactics in a wider theoretical context, I summarize its implications for the architecture of Paradigm Function Morphology and for schema unification in Construction Morphology. I further contrast the exponence-driven conception of morphotactics embodied by the rule-combining approach with the very different word-skeletal approach to morphotactics, drawing attention to two advantages of the rule-combining approach. First, it affords a more parsimonious inventory of morphological operations than is assumed in Distributed Morphology. Second, it avoids the cumbersome theoretical commitments of Information-based Morphology (the assumptions of position-based ordering, rule anchoring, and distributional pigeonholing), which entail numerous complications in the analysis of a language’s morphotactics. The distinct assumptions on which the rule-combining approach rests (those of combination-based ordering, unanchored rules, and distributional multidetermination) afford morphotactic analyses that are at once simpler and more explanatory.
INTERFERENSI MORFOLOGI PADA RUBRIK GAGASAN KORAN SOLOPOS SEBAGAI BAHAN AJAR ANALISIS ARTIKEL OPINI DI SMA

The aims of the study is to examine and describe: (1) the morphological interference, (2) the factors causing Javanese morphological interference into Indonesian in the Gagasan rubric of Solopos newspaper, and (3) the use of research results as teaching materials for analyzing language rules of Opinion Articles in SMA. The type of the research is qualitative research with a content analysis approach. The sources of data are using documents and informants. The sampling technique are purposive sampling, while the data collection technique used the reading and note taking technique. The data validity test technique used triangulation of data sources and triangulation of methods. The data analysis technique research is using interactive analysis. The results of the study indicate that the Gagasan rubric of Solopos Newspaper has (1) the morphological interference in the use of the prefix {N}, suffix / -an /, reduplication or rephrasing, affix removal, and exchange the suffix /-e/ BJ into the suffix /-nya/ BI (2) the causal factors Interference includes written language habits of journalistic variety, the author’s habits, the author's understanding of language interference and linguistic rules is lacking, the author's vocabulary is small, and researchers and editors are less careful, (3) the results of the study can be used and utilized in learning linguistic analysis of opinion articles. by students and teachers in high school. Keyword: Morphological Interference, Causative Factors, Teaching Materials
Nonparametric Clustering of Mixed Data Using Modified Chi-Squared Tests

We propose a non-parametric method to cluster mixed data containing both continuous and discrete random variables. The product space of the continuous and discrete sample space is transformed into a new product space based on adaptive quantization on the continuous part. Detection of cluster patterns on the product space is determined locally by using a weighted modified chi-squared test. Our algorithm does not require any user input since the number of clusters is determined automatically by data. Simulation studies and real data analysis results show that our proposed method outperforms the benchmark method, AutoClass, in various settings.
Neural Adversarial Attacks with Random Noises

In this paper, we present an approach which relies on the use of random noises to generate adversarial examples of deep neural network classifiers. We argue that existing deterministic attacks, which perform by sequentially applying maximal perturbations on selected components of the input, fail at reaching accurate adversarial examples on real-world large scale datasets. By exploiting a simple Taylor expansion of the expected output probability under the noise perturbation, we introduce noise-based sparse (or L 0 ) targeted and untargeted attacks. Our proposed method, called Voting Folded Gaussian Attack (VFGA), achieves significantly better L 0 scores than state-of-the-art L 0 attacks (such as SparseFool and Sparse-RS) while being faster on both CIFAR-10 and ImageNet. Moreover, we show that VFGA is also applicable as an L ∞ attack and outperforms the state-of-the-art projected gradient attack (PGD) method.
Implementasi Sistem Monitoring Jaringan Menggunakan Zabbix Berbasis SNMP

Network administrators require network monitoring in managing a network. Technological developments allow network monitoring using the SNMP protocol combined with a monitoring system using Zabbix. This research is designed for viewing and using routers to display information about the web. The problem that often occurs is the lack of administrators and the network monitoring system has not been accommodated. With this research, objectives continue to be developed, so that network administrators are helped and more quickly solve problems by monitoring existing networks. This study uses Zabbix as an open-source monitoring system. This application can display information from network devices such as Traffic Data, Bandwith Usage, and Network Interface. The results of the trials that have been carried out have proven to be able to monitor networks using SNMP-based Zabbix by displaying the expected results. This is indicated by the running of the monitoring system on the Zabbix application. It is hoped that by developing a network monitoring system using Zabbix-server, it will be easier to help speed up problems that occur and become a benchmark for the system being developed.
Are the communications of African flight attendants a form of slurred speech?

Onboard international flights, you may have witnessed the pre-takeoff information/in-flight safety speech by the cabin crew. It is not out of place that they tend to be European in their mode of speaking. However, when on a local flight, the Europeanness of speech still comes out loud. We want to understand why such Europeanised intonation should be and the audience it is meant to serve. Our research leads us to the conclusion that this insensitivity of local airline operators stems from the desire to enjoy some patronage even if their actions inferiorise the community who are the major patronisers of their services. We will also explain why the Europeanisation of speech could lead to safety hazards. This work is inspired by the personal experiences of the researchers and of a few others.
Simplifying Clustering with Graph Neural Networks

The objective functions used in spectral clustering are generally composed of two terms: i) a term that minimizes the local quadratic variation of the cluster assignments on the graph and; ii) a term that balances the clustering partition and helps avoiding degenerate solutions. This paper shows that a graph neural network, equipped with suitable message passing layers, can generate good cluster assignments by optimizing only a balancing term.Results on attributed graph datasets show the effectiveness of the proposed approach in terms of clustering performance and computation time.
The Construction and Application of Regional Education Quality Monitoring Databases: A Case Study of Suzhou’s Education Quality Monitoring

The development of school education depends on the quality of the education provided, and it is a key metric for assessing the effectiveness of schools in developing talent. Building specialized, intelligent education quality monitoring (EQM) databases is crucial for speeding EQM progress in the big data era. This article examines the development of regional EQM databases in the areas of operational procedure and logical structure based on the idea of data lakes by using the development of databases for the EQM data analysis system (DAS) in Suzhou City as a case study. The goal of this study is to assist in addressing the current issues with regional EQM data processing and ensuring EQM’s successful implementation.
A Wizard or a Fool? Initial Assessment of a Wizard of Oz Agent Supporting Collaborative Virtual Environments

A popular technique for evaluating envisioned AI agents without committing significant engineering resources to implement such an agent is the Wizard of Oz (WoZ) methodology. Thus far, many of the WoZ studies concerned with the design of conversational agents have been standalone systems for individual participants to interact with. The aim of this work was to determine whether a WoZ conversational agent could be embedded within an existing team-based collaborative virtual environment. In doing so, we uncovered a number of potential challenges in designing such a system which may be valuable for those implementing such a system in the future.
Identifikasi Pengembangan Digital Supply Chain pada Industri Pengolahan Sampah

Technology developments in the era of the industrial revolution 4.0 provide many opportunities to improve supply chain performance and performance. The existence of the waste processing industry as a business has prospects for development, given the large amount of waste generated by the community and the need for several processed products. PT A reduced the amount of garbage that accumulates in the final disposal site (TPA) by reprocessing the waste produced by the community. The existence of waste banks, government agencies, hotels, zoos, and Islamic boarding schools is one of the sources of waste that is processed for waste products. This paper seeks to develop the concept of a digital supply chain by adopting the supply chain model run by PT A. The initial identification presented in this paper can result in several technology identifications that need to be prioritized in implementing relevant technologies in the industry. The expected impact of this implementation is an increase in supply chain performance
A Novel Obstacle Bitmap Formulation for Homotopic Path Planning Method Applied to Terrestrial Mobile Robot

In this paper a new bitmap representation of configuration space compatible with the Homotopic Path Planning Method (HPPM) is presented. Bitmap methodology has been developed to extend the application field of the HPPM in discrete workspaces. In the proposed bitmap representation each obstacle is modeled in the configuration space as a semi-algebraic expression using the Smooth High Canonical Piecewise Linear (SHC-PWL) formulation. For HPPM a bitmap representation through semi-algebraic expressions implies the capability to solve complex environments with obstacles in continuous and discrete configuration spaces. Three numerical study cases are presented to show the potential applications of the proposed bitmap representation for applications in real autonomous mobile robots. Finally, some points and future work derived from the analysis of study cases are discussed.