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Hotels streamline operations, provide more personalized service, streamline communication, automate procedures, and gather feedback for ongoing development using modern digital technologies like customer care chatbots, mobile guest applications, and property management systems. Batch, sequential, and incremental learning all make heavy use of the Extreme Learning Machine (ELM) because of its efficient and rapid learning rate, rapid convergence, strong generalizability, and simplicity of implementation. By automating repetitive tasks, Artificial Intelligence (AI) improves the hospitality sector’s efficiency and quality on service it provides to customers and employees. Using AI-driven automated systems, hotels may improve inventory management, track and manage energy use, and simplify cleaning schedules. The challenging characteristics of smart flood detection and alert systems are that they lack expertise, streamline operations and provide personalized guest services. Hence, in the proposed method, the Artificial Intelligence Environment enabled Wireless Sensor Network (AIE-WSN), which integrates a hotel digitization effect in an ELM. In addition, case studies and expert interviews provide practical insights into how hotels have used and benefited from financial management systems driven by AI. The research shows that hotels may greatly benefit from AI tools, including personalized pricing strategies, spending monitoring systems, fraud detection algorithms, and predictive analytics when making financial decisions through WSN. The hotel industry is undergoing digitalization, adopting AI-WSN solutions to track products’ provenance and monitor their history, among the many benefits of the proposed approach. It can help with supply chain management and adopting more efficient practices.

This study calculates China’s provincial total factor productivity (TFP) and decomposition indexes. Then, a system of indicators is constructed to measure digitization, and an empirical analysis is conducted. The results show that (1) digitization can significantly improve TFP, especially technical efficiency, largely due to the increase in factor allocation efficiency and the quality of technological innovation resulting from digitization, a finding that remains valid even after a series of robustness tests. (2) The effect of digitization on the improvement of TFP is more pronounced in the central and western regions of China than in the east and more pronounced when economic development is in the service stage. The existence of a digital divide can diminish the positive effects of digitization. The regression results by industry show that digitization has a more significant positive impact on TFP in the secondary and tertiary industries than in the primary industries. (3) Further analysis shows that the process of digitization in raising TFP is nonlinear and that the positive effect of digitization on TFP is stronger when the level of industrial structure crosses the threshold. The findings of this paper bear some beneficial policy implications.

We review some pattern matching algorithms and techniques motivated by the discrete theory of image processing.

The problem inspiring this research is that of searching an aerial photograph for all appearances of some object.

The issues we discuss are digitization, local errors, rotation and scaling.

We review deterministic serial techniques that were used for multidimensional pattern matching and discuss their strengths and weaknesses. We introduce the new geometric model that has been recently found to be extremely suitable for the theory of discrete image processing. We introduce some of the new algorithms developed in the geometric model and show their capability of efficiently solving hitherto open problems.

When chaotic systems are realized with finite precisions in digital computers, their dynamical properties are often found to be entirely different from the original versions in the continuous setting. In the literature, there does not seem to be much work on quantitative analysis of such degradation of digitized chaos and how to reduce its negative influence on chaos-based digital systems. Focusing on 1D piecewise linear chaotic maps (PWLCM), this paper reports some findings on a new series of dynamical indicators, which can quantitatively reflect the degradation effects on a digital PWLCM realized with a fixed-point finite precision. On top of that, the paper introduces a new method for studying digital chaos from an algorithmic point of view. In addition, the theoretical results obtained in this paper should be very helpful for the consideration of reducing negative influence of dynamical degradation in real design of various digital chaotic systems. As typical examples, the proposed dynamical indicators are applied to the performance comparison of different remedies for improving dynamical degradation, cryptanalysis of digital chaotic ciphers based on 1D PWLCM, and design of chaotic pseudo-random number generators with desired characteristics.

In today’s information age, intelligent manufacturing has become a significant trend of future industrial development. The neural network plays a vital role as the basis of smart manufacturing. This is a kind of intelligent algorithm that can simulate human brain organization, with strong learning ability and computing power, and has achieved remarkable results in the application field; the most typical representative is deep neural network, especially in recent years, an artificial intelligence developed based on deep neural network has entered the application stage, providing a new idea and model for industrial production. Based on this, taking the clothing production process as an example, this paper combined transfer learning and network fine-tuning technology to build a Faster RCNN model based on the ResNet-101 network to realize the positioning and recognition of clothing style map features and create an intelligent generation platform for clothing process flow on this basis.

The documentary patrimony deposited in the libraries and archives represents an essential part in the collective memory; it reflects the diversity of languages, peoples and cultures. But such memory is fragile and a part of such patrimony regularly disappears by accident, war or ageing.

There exist about three million manuscripts of an Arab or Islamic origin, scattered throughout the world. They are not well preserved, that is why researchers encounter difficulty in consulting them. The digitization of such documents has become an absolute necessity for saving and preserving them for future generations.

This paper presents a contribution in the domain of digitization and processing of images of historical documents stored in the Arabic libraries. After being scanned, the raw images obtained undergo a primary pre-processing treatment in order to clean them and restore them; then they go through a second phase of image analysis which consists in segmenting the documents so as to separate out texts and graphics, and in compressing the images so as to reduce their stocking cost and their communication time. All such operations are necessary for the retro conversion of the images of historical documents for the purpose of indexing and hosting them on the internet.

A topographic sheet hosts various morphological features that effectively describe the terrain. This multi-faced information content not only elevates human perception but also provides ample direction for research initiatives. Out of all possible attributes based on utility, contours have wide set of application. A contour is characterized by its coordinate system and most importantly, its elevation detail. Upon, successful attainment of these two attributes, creating a fully automatic 3D projection system may be achieved with relative ease. In contrast to the traditional manual approach, this research initiative puts forward a novel mechanism for automatically localizing contour and its attributes including coordinate pattern and elevation value in a referenced map. To accomplish the aforementioned objectives, the proposed mechanism relies on various image processing techniques based on morphological operations. Further, the extracted details can be used to project the contours in a 3D space. This projection is also called Digital Elevation Model (DEM). DEM is crucial for various applications such as Terrain Modeling, Hydrological Modeling, Path Optimization, to name a few. Automatically and accurately created DEM from topographic sheet could contribute a lot in many Geographical Information System (GIS) applications. This paper focuses mainly on elevation value localization associated with specific contour.

Surface Reconstruction is the most potent aspect of 3D computer vision. It allows recapturing or imitating of the shape of real objects. It also provides sufficient knowledge regarding the mathematical foundation for rendering applications which are widely used for analyzing medical volume data, modeling, 3D interior designing, architectural designing. In our paper, we have mentioned various algorithms and approaches for surface reconstruction and their applications. Moreover, we have tried to emphasize the necessity of surface reconstruction for solving image analysis related problem.

India is rich in its heritage and culture. It has many historical monuments and temples where the walls are made of inscribed stones and rocks. The stone inscriptions play a vital role in portraying about the ancient incidents. Hence, the digitization of these stone inscriptions is necessary and contributes much for the epigraphers. Recently, the digitizing of these inscriptions began with the binarization process of stone inscriptions. This process mainly depends on the thresholding technique. In this paper, the binarization of terrestrial and underwater stone inscription images is preceded by a contrast enhancement and succeeded by edge-based filtering that minimizes noise and fine points the edges. A new method called modified bi-level thresholding (MBET) algorithm is proposed and compared with various existing thresholding algorithms namely Otsu method, Niblack method, Sauvola method, Bernsen method and Fuzzy C means method. The obtained results are evaluated with the performance metrics such as peak signal-to-noise ratio (PSNR) and standard deviation (SD). It is observed that the proposed method has an improvement of 49% and 39%, respectively, on an average by the metrics considered.

In order to better improve the quality of English teaching, this paper studies the sharing method of English digital teaching resources combined with modern digital technology. Through the collection and management of English digital teaching resources, it constructs the evaluation index system of teaching resources, so as to comprehensively and objectively evaluate the digital teaching resources and promote the construction and development of digital teaching resource and to effectively promote and improve the teaching effect, and realise the research requirements of effective sharing of massive teaching resources in complex environment.

The gastronomy sector was one of the industries most fundamentally affected by the COVID-19 pandemic restrictions and the subsequent disruption of demand. Entrepreneurs were challenged to secure their survival. This study aims to analyze how COVID-19 has accelerated digital technologies in the hospitality industry. The study assumes that due to lockdowns successful restaurants in Baden–Wuerttemberg have developed new digital business models. Data for the quantitative study were collected through a survey among randomly selected restaurants carried out between December 2020 and February 2021. A cluster analysis is used to identify different types of restaurants concerning their propensity to innovate and their success. Results of the study show that the level of digitization is one important factor regarding the range of entrepreneurial success.

Despite the prevalence of a rich literature on bank profitability, yet, none of it analyzes the simultaneous effects of GFC and COVID-19 on bank profitability. We attempt to fulfil this gap by using a model which factors in digitization, ageing population, endogenous and predetermined variables, let alone control for G-SIBs. Findings show that the impacts of COVID-19 were twice as much deleterious as those hailing from the GFC in the case of NIM and four times as harmful in the case of ROE, with ageing population exerting bearish forces on bank profitability. Mobile usage interacted with COVID-19 crisis dummy and is found to leverage on ROE, underscoring the significance of technology-driven sources of activities during the pandemic. Overall, our paper justifies the significantly larger bailout package launched by the authorities during the pandemic compared to that triggered during the GFC with the critical role of technology being underscored in securing banks’ profits during the pandemic.

Buyers of global drugs must pay big licensing fees. As the race is different, at least before the drug launch in China buyers should ensure the effectiveness and safety of drugs, and what needs to be done is at least four phases of the clinical trial. If there is insufficient overseas clinical trial data, NMPA in China also needs RCT results or validation of drug safety issues of clinical studies. If a large amount of authorization fees is spent in the early stage and the sales volume is not good after it is listed in China, it may be a failed license. Therefore, it is necessary to consult before buying and help buyers make decisions based on data, policies, and expert opinions. We analyze the domain of the disease, learn from epidemic diagnosis to treatment and prognosis of process and data, production for the domestic top clinical experts, statistics, registration experts, policy adviser to the questionnaire, interview, and then summarize the research results. According to the expert opinion, we can give advice on whether it can be licensed in China successfully. It is recommended that the original factory prepare the materials needed for registration in China as soon as possible, and explain the controversial aspects of the original factory’s registration trial design. The overall recommendation is: if the original manufacturer can provide all the overseas materials required for the drug to be registered in China, the explanation of the controversial aspects of the registration trial can be accepted by Chinese experts, and the domestic manufacturer has the money to do both the RWS and the small RCT, the drug is still worth licensing in. We use NLP and knowledge graphs to calculate the commercial decision. Before developing a program we use data and knowledge to evaluate every KOL to select suitable ones. Data was collected from Pubmed and the introduction from portals of hospitals.

This chapter proposes four key foundational technologies in the era of the Fourth Industrial Revolution, collectively termed ABCD technologies: artificial intelligence, big data analytics, cloud computing, and digital technology. While the four technologies emerged independently across different time frames, they have become increasingly interwoven over time, driving the advent of new technologies. This chapter delves into the dynamics of their interplay and articulates their critical role in catalyzing a variety of emerging technologies. This study also highlights how their relevance differs across the emerging technologies, as illustrated by three examples: ChatGPT, the Internet of Things (IoT), and blockchains. Moreover, the study provides implications for both firms and policymakers on how to effectively leverage the four foundational technologies and respond to the fast-changing technology environment in the era of the Fourth Industrial Revolution and beyond.

India is a land of diversity, where diverse cultures, religions, languages and ethnicities have increasingly driven innovation and creativity, giving a boost to the development of small- and medium-sized enterprises (SMEs) in the country. Given that 70% of India’s rural population still primarily depends on agriculture for their livelihood and most of the population lives in villages and Tier 1 and Tier 2 cities, SMEs in these areas have been playing a pivotal role in the inclusive growth of the Indian economy since independence. From cottage industries to the Internet of Things (IoT) and smart technologies or large manufacturing industries, SMEs account for the majority of enterprises worldwide, contributing two-thirds of employment opportunities. Studies conducted in the past show that SMEs have constantly been confronted with various challenges, such as lack of timely access to credit facilities, shortage of manpower and skills, and adoption of new technologies. The outbreak of the COVID-19 crisis in the past few years has crippled their regular activities. However, the crisis has fundamentally changed not only the mindsets, perceptions, and the way businesses, SMEs, organizations, institutions, and individuals operate but also given an opportunity amid the crisis to be more resilient and embrace the digital platforms to survive and eventually achieve success. The aim of this chapter is to identify the future prospects of SMEs through thriving digitization while proposing a framework with a new managerial mindset as a strong force of SME specificities. It also focuses on policy intervention to optimize businesses in order to achieve sustainable economic growth.

This chapter is divided into three main parts. The first part focuses on defining and explaining the purpose of SMEs in India, wherein the significant benefits of digitization as a strategy for driving improved performance and productivity of SMEs are explained. The second part deals with describing the challenges and struggles of Indian SMEs from a managerial perspective while focusing on the new mindset of SME managers and owners toward the organic development of their businesses. The third and most crucial part examines policy interventions and support for SMEs and a new entrepreneurial mindset, and it suggests a model for inclusive growth in an economy.

The present paper discusses the work of digitization of cultural heritage of India. Non-contact digitizing system is the only practical choice for high resolution scanning of sculptures and artifacts. They collect from 20 to more than 25,000 points per second and provide resolution of better than O.OOl-inch to 0.020-inch, depending on technology. Tlhis work is carried out at Indian Institute of Technology, Kanpur and in Allahabad University and focuses mainly on Buddhist deities Hariti and Gajlaxmi. We will discuss about the digitization of these artifacts, concept of Rapid Prototyping, Reverse Engineering. In the paper we will also discuss the detail of the development of the Rapid Prototype of Buddha statue in FDM (Fused Deposition Modeling). Certain research issues pertaining to reconstruction and databases are also discussed.

The development of digital libraries, the mass digitization of cultural heritage resources and the increasing use of electronic information resources both by library staff and users have changed the library environment and played a critical role in managing and disseminating knowledge. This new working environment has transformed the way in which employees share their knowledge. This research project aims to investigate the intrinsic and extrinsic factors that motivate librarians to share knowledge in their workplace. A data gathering tool applied in four European countries (Greece, Czech Republic, Portugal and Slovenia) in order to find out what factors motivate library staff to share their knowledge and manage its flow assists in its dissemination. The Results indicate that library staff acknowledges that the new digital working environment affects the way in which they share knowledge and recognize the importance of the role of intrinsic motivation in knowledge sharing and that team-based culture can benefit the success of knowledge sharing initiatives within libraries. Cross reference of data show similarities and differences from different countries. Finally, a set of Spearman's correlations were used in order to check any connection between the values under research.

This paper discusses the software for digitization and measurement of astronomical plate. Only by using the advanced commercial scanner, the plate can't be digitized in FITS format but in TIFF format. This software can convert TIFF file to FITS file and add some important keywords in the FITS header. This software can also gives the user a way to automatic measure the digitized image of astronomical plate in batch mode. The measurement of an image is done in three steps: identification of stars, elimination of spurious detections, centering of stars.