Reviewerly/exHarmony huggingface dataset:
Modern types of consulting in the management system of an educational organisation

Introduction. In market economy, the internal and external processes of educational organisations are becoming more complex. There is a need to identify managerial practices, which can be delegated to external consultants. The process of defining such practices is not completely studied. The application of expert support from leaders and management teams is often situational. The aim of the present research is to identify the range of managerial problems of educational organisations, which cause the need to resort to external consulting support. Methodology and research methods. The application of the method of cluster analysis of text data of periodicals allowed the authors to investigate a potential market for consulting services, to identify the modern management needs of educational organizations and the experience of their solution by external organisations. The analysis of open data of consulting organisations was carried out to identify real practices. Results. The main management problems of educational organisations and the types of consulting services necessary for their solution are considered and classified. The main approaches to defining the framework of educational consulting are highlighted. The authors have developed the method for monitoring the prospective market for consulting services. It was determined that the growing demand for consulting services and the expansion of the range of these services are associated with the formation of a market environment in the education system and the desire of management of educational organisations to provide a competitive advantage. The cases of Russian and foreign consulting organisations were analysed and grouped in accordance with the proposed typology. Scientific novelty. In academic literature, the study of this issue is mainly limited to defining the boundaries of educational consulting. The authors have made an attempt to identify typical situations, in which managers of educational organisations need to request the services of external experts. Practical significance. The results of the current research can serve as a guideline for the management of educational organisations, when making managerial decisions. It will allow the managers to determine the cases, in which it is possible to turn to external consultants according to the supply conditions on the market, and to identify the issues, regarding which it is desirable to rely solely on internal resources.
Russian Engineering Universities in International Ratings

This article is devoted to the problem of improving the quality of engineering education in Russia in the context of global changes in the world economy associated with the fourth industrial revolution and the task of digitalizing the economy of the Russian government.Increasing competition in all civilian sectors requires highly qualified creative engineering staff to work in innovative companies.The lag of higher (including engineering) education from world standards is becoming more noticeable and is manifested in the low positions of Russian universities in international ratings.The transition to a market form of management and integration into the global economic system require, among other things, improving the quality of higher education in Russia, which should be confirmed by higher positions of Russian universities in international ratings.The purpose of this article is to help in choosing ways to reform Russian engineering education through a critical analysis of the experience of the world's leading technical universities.Taking into account international experience, the author proposes several ways to reform Russian engineering education.First, to diversify leading engineering universities by strengthening programs in basic sciences (physics, chemistry), life sciences (medicine, bioengineering) and humanities.Second, to strengthen the research sector of engineering universities by transferring to them a part of academic and industrial research institutes.Third, the reform of engineering universities should be coordinated with the diversification and partial conversion of state defense corporations.
Examining the Drivers and Barriers of Intention to Use AI Chatbot to Purchase Apparel Online

<p class="MsoNormal"><font face="Times New Roman, serif"><span style="font-size: 16px;">It is reported that the use of AI chatbot in retail sales is expected to grow to $22 billion by 2023 from $2.6 billion in 2019 (Tracy, 2019). AI chatbot can help customers by answering their questions, asking follow-up questions to customers, and providing suggestions for searching products (Huang et al., 2007). Therefore, many apparel brands such as Louis Vuitton, Burberry, Tommy Hilfiger, and H&amp;M have adopted AI chatbot technology to interact with their consumers. Te purpose of this study is to investigate the drivers and barriers of apparel consumers’ intentions to use AI chatbot purchasing apparel online. Findings revealed that optimism and innovativeness of technological readiness positively influenced the perceived ease of use of AI chatbot. Findings showed that while relative advantage and complexity of psychological readiness positively influenced the perceived usefulness of AI chatbot, resistance to change of psychological readiness negatively influenced the perceived usefulness of AI chatbot.</span></font><br>
Proximity-Based COVID-19 Contact Tracing System Devices for Locally Problems Solution

COVID-19 contact tracing is one of preventive solution to slow down the spread of the virus.Some of countries have been implementing manual contact tracing and also digital tracing using smartphone application.The success of the digital tracing implementation requires cooperation from the community and firm leadership from the government as well as medical record reporting from the public health so that the data can be analyzed as soon as possible for the next preventive action required.However, for countries with large population like Indonesia, it is difficult to control the society while the health facilities are quite overwhelmed enough to cope with the number of infected, which has not decreased to date.Proximity-based COVID-19 contact tracing system devices using BLE (Bluetooth Low Energy) technology is focusing on tracing and controlling the spread of virus in local community.For example, the system devices will be implemented in a factory, the devices are put in front pocket of factory employee' shirt or hooked on the shirt.The devices will record the proximity between employees and the data is synchronized using their smartphone or via application to be stored in database.The proximity records will be used once there is an infected employee to obtain information of possibility of other employees are being infected, to avoid massive test and isolation.In addition, the use of this device can be expanded even further.
WIRELESS SENSOR NETWORKS CONGESTION AND ROLE OF ARTIFICIAL INTELLIGENCE

The occurrence of the congestion has an extremely deleterious impact on the performance of Wireless Sensor Network (WSNs).Some novel blockage control method utilizing computerized reasoning for remote sensor systems.Remote Sensor Systems are a class of remote systems estimated for checking objective and ecological wonders.Our paper provides opening to wireless sensor network as well as for artificial intelligence, which aims to act both proactively, in order to avoid the creation of congestion in WSNs, and reactively, so as to mitigate the diffusion of upcoming congestion through alternative path routing.We make use of Artificial Intelligence (AI) which play an important role in our society, give rise to systems that can manage themselves.Many advanced AI techniques can be utilized to improve the performance and reliability.Investigating the AI algorithm applied to WSN may improve network management, security or routing in WSN which may result in a more reliable network.We will look at AI algorithm applied in WSN and discuss the possible use of these AI in WSN to address the WSN challenge and improve its performance and reliability.And due to the constraint on data processing and power consumptions, use of artificial intelligence has been historically discarded in these kind of network.The use of the AI in WSN makes system error free, fast and efficient in almost many aspects.This paper attempts to encourage the use of art ificial intelligence techniques in wireless sensor nodes.
Cyber-physical Threat Detection Platform Designed for Healthcare Systems

Hospitals are responsible for delivering healthcare services to patients in need. These services are large and complex and get affected by multiple interacting actors, such as doctors, nurses, patients, citizens, medical suppliers, health insurance providers. Lately, hospitals around the world are one of the main targets when it comes to terrorist attacks, the cyber realm being the principal source. The healthcare sector is particularly vulnerable due to heavy involvement in patient personal and health information, time constraints, and complex day-to-day operations. In addition to cyber-threats, physical threats are increasingly growing and even healthcare facilities are not immune to them. Malicious intended people created cyber threatening attacks with the purpose to systematically collect evidence against the healthcare system, to advocate for the end of such attacks, and to endanger people's lives or to use the stolen personal data for bad intended actions. Henceforth it is necessary to build a platform that will get alerts and incidents at a fast pace in real-time to prevent any casualties at low cost. SAFECARE project aims to offer protection to hospitals and increase the compliance for the European regulations and security regarding ethics and privacy for health services. This paper presents a solution that will enhance security in hospitals. The primary platform will be built based on a BTMS (Building Threat Monitoring System) where events, incidents, and alerts will be transmitted by sensors from hospital rooms in real-time. Several scenarios were thought to simulate different types of attacks against hospitals and according to the scenarios, various prototypes will be built for assuring the security of the personal and patients from various hospitals.
Implementation challenge and analysis of thermal image degradation on R-CNN face detection

Face detection systems with color cameras were rapidly evolving and have been well researched. In environments with good visibility they can reach excellent accuracy. But changes in illumination conditions can result in performance degradation, which is the one of the major limitations in visible light face detection systems. The solution to this problem could be in using thermal infrared cameras, since their operation doesn't depend on illumination. Recent studies have shown that deep learning methods can achieve an impressive performance on object detection tasks, and face detection in particular. The goal of this paper is to find an effective way to take advantages from thermal infrared spectra and provide an analysis of various image degradation influence on thermal face detection performance in a system based on R-CNN with special accent on implementation on a hardware platform for video signal processing that institute Vlatacom has developed, called vVSP.
Trends towards IOT in Egypt

This research aims to investigate the benefits of implementing the cloud computing system over the currently used IT system, as well the challenges of applying Cloud computing that companies in Egypt could face. This research applies mixed methods of research. Both qualitative and quantitative methods of research are used in the form of semi-structured interviews and questionnaires, respectively. The semi-structured interview was targeting the supply chain and IT managers of three different companies at Coca Cola Egypt, Nestle Egypt and Carrefour Egypt. A SWOT analysis was conducted to serve as a guide to many companies in Egypt that are willing to implement such a system and can then avoid the weakness points and the threats that they could be faced with during the implementation. The importance of this research adds to the literature by focusing on the application of IOT in Egypt in terms of the implementation of a cloud computing system in Egypt and it analyzes whether it could increase the efficiency of the companies in Egypt.
Small and Medium Enterprises and Cloud Technology–Challenges and Opportunities during COVID19

The cloud technology has proven its benefits during the lockdown situation.Small and Medium scale industries are severely impacted during pandemic due to multi fold reasons.This paper depicts the situation of SMEs who were prepared for digital journey using cloud technologies verses underprepared SMEs.It covers the cloud basics and usefulness of cloud technology for Small and Medium scale industries.It also provides views for selecting right option to maximize the benefits for SMEs.Software as a Service (SaaS) offering has proved more beneficial for SMEs over Landscape as a Service (LaaS) and Platform as a Service (PaaS).The key benefits of SaaS such as SMEs do not require hardware and software installations at their premises.The Cloud Service Providers (CSPs) extend support for installation and customization for their products.They takes care of maintenance and various upgrades necessary during product life cycle.These distinct advantages of cloud technology became more relevant during Pandemic situation for SMEs.The SMEs being vital part of our economy, the cloud service providers are coming up with various offerings to encourage them for cloud technology adoption.The Pandemic period is also assisted CSPs to improvise their services.The increased cyber-attacks strengthened the security mechanism while the surge in the network usages emphasized the need of optimization code for better user experience.The Covid-19 pandemic has opened up new opportunities for cloud technology in health care sector.The new normal has brought less social contacts and more usages of technology means for daily interaction.Cloud technology has become a part of business continuity planning and brought new perspective during COVID-19 pandemic.The cloud-based workforce collaboration tools and round the clock remote accessibility mitigate the major risks during natural disasters.It is time to adopt cloud technology by those SMEs who have not considered cloud adoption as an option in the first place.
A strictly stronger relative must

It is widely accepted that when “might” expresses certain kinds of relative modality, the sentence “p and it might not be the case that p” is in some sense inconsistent. It has proven difficult to define a formal semantics that explicates this inconsistency while meeting certain other desiderata, in particular, that p does not imply “Must p.” This paper presents such a semantics. The key idea is that background contexts have to have multiple levels, including an inner set consisting of worlds that represent what might be true and an outer set of worlds such that a sentence must be true only if it is true in all of them.
Environmental Impact Assessment of Soil Pollution in Industrial Zones

The study area is the city of Mosul, which is located in the north-western part of Iraq and study aims to determine the level of heavy metal contamination in the main industrial areas of Mosul City, northern Iraq, where 12 samples collected Only soil samples had been collected with depth (0-15) cm by using a homemade soil sampler in industrial zone.Samples was carried in January 2019.First of all, samples were air-dried in natural condition, and the debris of animals and plants had been cleaning by hands.Samples grind and pass through a sieve (2mm), so they ready to measure.and analyzed from the industrial soil areas (6 samples from the soil of the Okab industry-west of Mosul City) and (6 samples from the soil of the Karama Industry-East of Mosul City), the soil was at depth (0-15) cm and analyzed by the X-ray Fluorescence for 8 metals included (Pb, As, Cd, Ni, Cr,).The GIS10.6.1 ArcMap program was used to draw the environmental maps of each metals and to determine the extent of these metals and their impact on neighboring regions The results obtained for heavy metals and compared to the WHO, 2003 and these areas are already contaminated with (Ni, Cr, As) metals that have Exceeded the specified values.In addition, Pb and Cd elements are within the allowed values.
Software Deception Steering through Version Emulation

Determined cyber adversaries often strategize their attacks by carefully selecting high-value target machines that host insecure (e.g., unpatched) legacy software.In this paper, we propose a moving-target approach to thwart and countersurveil such adversaries, wherein live (non-decoy) enterprise software services are automatically modified to deceptively emulate vulnerable legacy versions that entice attackers.A game-theoretic framework chooses which emulated software stacks, versions, configurations, and vulnerabilities yield the best defensive payoffs and most useful threat data given a specific attack model.The results show that effective movement strategies can be computed to account for pragmatic aspects of deception, such as the utility of various intelligence-gathering actions, impact of vulnerabilities, performance costs of patch deployment, complexity of exploits, and attacker profile.
Unsupervised Learning of Depth and Camera Pose with Feature Map Warping

Estimating the depth of image and egomotion of agent are important for autonomous and robot in understanding the surrounding environment and avoiding collision. Most existing unsupervised methods estimate depth and camera egomotion by minimizing photometric error between adjacent frames. However, the photometric consistency sometimes does not meet the real situation, such as brightness change, moving objects and occlusion. To reduce the influence of brightness change, we propose a feature pyramid matching loss (FPML) which captures the trainable feature error between a current and the adjacent frames and therefore it is more robust than photometric error. In addition, we propose the occlusion-aware mask (OAM) network which can indicate occlusion according to change of masks to improve estimation accuracy of depth and camera pose. The experimental results verify that the proposed unsupervised approach is highly competitive against the state-of-the-art methods, both qualitatively and quantitatively. Specifically, our method reduces absolute relative error (Abs Rel) by 0.017–0.088.
Emotional Response to Extended Realities: The Effects of Augmented and Virtual Technologies in a Shopping Context

Extended reality (XR) technologies such as Augmented Reality (AR) and Virtual Reality (VR) are facing mixed expectations.XR is often touted to offer deeply engrossing experiences but it can also lead to cybersickness, disappointment, and frustration.Moreover, research has not kept pace with how these technologies may affect users' emotions.Therefore, to understand emotions in XR, this study employs a 2 (virtual: yes vs. no) ×2 (augmented: yes vs. no) between-subject experiment (N = 162) in the shopping context.Effects on emotions are assessed by measuring changes in emotional valence and examining them using Median Tests and exploratory data analysis.Results suggest that emotional responses in XR are similar to those in a physical store.However, there is an unexpected effect of the augmented experiences where negative emotions markedly vary.Implications are presented both for retail businesses and simulations, and emotionally engaging experiences such as immersive journalism and psychotherapy.
Blockchain Application to the Cancer Registry Database

Blockchain, since its 2008 conceptual inception, has largely been contextualized in crypto currencies. Today, blockchain technology has matured to a level that allows the exploration of its application to other and diverse domains, including the management of cancer registries. When collecting and handling data relating to cancer diagnosis and treatment as mandated by law in many municipalities, the process is both time-consuming and requires significant coordination among multiple levels of data collecting jurisdictions. This often leads to inconsistent data vis-à-vis the various levels of data storage. This paper calls for using a blockchain-based mechanism to alert the data users on possible inconsistencies prior to applying the collected data in cancer research. A system framework drawing on the design science research methodology is found to result in increased data quality so as to improve cancer research outcome accuracies.
Partitions of correlated N-qubit systems

The production and manipulation of quantum correlation protocols will play a central role where the quantum nature of the correlation can be used as a resource to yield properties unachievable within a classical framework is a very active and important area of research. In this work, we provide a description of a measure of correlation strength between quantum systems, especially for multipartite quantum systems.
Specifics of Project Management of Development and Implementation of DPO Programs in Universities: Role of Educational and Scientific Centers

In the article the features of organization of the system of supplementary education in Russian universities in the conditions of modern reality are considered. Among them are the accelerating shift of professions, the concept of "long life learning", the digitalization of all spheres, including education, as well as a stable segment of the programs of professional education in the educational portfolio of a university is needed for its of sustainable competitiveness. As an example, there are proposed some perspective forms of organization of educational and scientific process which are new for the Russian practice of managing education. One of these forms could be an educational-scientific center in a university as a union of the departments and research units in the relevant subject area, structurally separated from the classical forms of faculty and completely different from it. The last one is classically managed individually, collegially or on the basis of linear-functional approach, especially in Russia. The education &amp; science center of Management in the Plekhanov Russian University of Economics is given as an example. It is a really successful division of the university, which has a confidently leading position in the internal rating system for KPI and a stable portfolio of orders for research and vocational programs for the corporate segment, which ensures the implementation of financial plans and guarantees the sustainability of a university’s budget. The article provides generalized practical recommendations for building the processes of development, promotion and implementation of vocational programs, taking into account the differentiation by basic target groups of consumers (students), diverse technologies for their training and creating basic versions of the educational products.
A kernel based reordering algorithm

We present in this short working paper a reordering algorithm, that we found quite handy while working in the context of Reproducing Kernel Hilbert Space (RKHS) theory. This algorithm, based on the linear assignment value problem, is used in a number of our research or industrial applications. It is integrated into our python library, named CodPy. CodPy stands for “Curse of dimensionality in Python” and is a Support Vector Machine (SVM), application oriented, Python library, providing tools for machine learning, statitistical learning and numerical simulations, consisting in a standard implementation of reproducing kernel Hilbert space (RKHS) methods.