Current Trends In Information Technology Research Articles

Unleashing the Potential of Digitalization in the Agri-Food Chain for Integrated Food Systems

Digitalization transforms many industries, especially manufacturing, with new concepts such as Industry 4.0 and the Industrial Internet of Things. However, information technology also has the potential to integrate and connect the various steps in the supply chain. For the food industry, the situation is ambivalent: It has a high level of automatization, but the potential of digitalization is so far not used today. In this review, we discuss current trends in information technology that have the potential to transform the food industry into an integrated food system. We show how this digital transformation can integrate various activities within the agri-food chain and support the idea of integrated food systems. Based on a future-use case, we derive the potential of digitalization to tackle future challenges in the food industry and present a research agenda. Expected final online publication date for the Annual Review of Food Science and Technology, Volume 15 is April 2024. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Current Trends in Information Technology- Which Way for Modern It Experts

The majority of services are currently made possible by IT. Technology development has had both positive and negative effects on society's way of life. The majority of human life today is impacted by new technology. Cloud computing, mobile computing, social media, ubiquitous computing, data analytics, data science, and the Internet of Things (IoT), a network of a large number of computing devices embedded with microchips, sensors, and actuators, have emerged as a result of this development. The various technological trends in information technology, their evolution, the percentage impact of technologies on business and government, and, finally, the creation of a framework for the way forward for IT professionals are the topics covered in this paper.

Applications of ML/DL in the management of smart cities and societies based on new trends in information technologies: A systematic literature review

• Introducing a new taxonomy for the management of smart cities and societies that is based on current trends in information technology. • Presenting an explanation of the critical issues in the ML-based smart cities. • Investigating each subcategory that referred to ML in smart cities and societies with various features. • Proposing innovative ML-DL solutions in the management of smart cities and communities. The goal of managing smart cities and societies is to maximize the efficient use of finite resources while enhancing the quality of life. To establish a sustainable urban existence, smart cities use some new technologies such as the Internet of Things (IoT), Internet of Drones (IoD), and Internet of Vehicles (IoV). The created data by these technologies are submitted to analytics to obtain new information for increasing the smart societies and cities' efficiency and effectiveness. Also, smart traffic management, smart power, and energy management, city surveillance, smart buildings, and patient healthcare monitoring are the most common applications in smart cities. However, the Artificial intelligence (AI), Machine Learning (ML), and Deep Learning (DL) approach all hold a lot of promise for managing automated activities in smart cities. Therefore, we discuss different research issues and possible research paths in which the aforementioned techniques might help materialize the smart city notion. The goal of this research is to offer a better understanding of (1) the fundamentals of smart city and society management, (2) the most recent developments and breakthroughs in this field, (3) the benefits and drawbacks of existing methods, and (4) areas that require further investigation and consideration. IoT, cloud computing, edge computing, fog computing, IoD, IoV, and hybrid models are the seven key emerging developments in information technology that, in this paper, are considered to categorize the state-of-the-art techniques. The results indicate that the Conventional Neural Network (CNN) and Long Short-Term Memory (LSTM) are the most commonly used ML method in the publications. According to research, the majority of papers are about smart cities' power and energy management. Furthermore, most papers have concentrated on improving only one parameter, where the accuracy parameter obtains the most attention. In addition, Python is the most frequently used language, which was used in 69.8% of the papers.

Information in Financial Markets and Its Real Effects

Abstract Financial markets have a central role in allocating resources in modern economies. One of the main functions of financial markets is the discovery of information. This information in turn helps guide decisions in the real side of the economy. The literature on the “feedback effect” of financial markets explores this channel. Empirical work tries to identify the informational feedback from markets to corporate decisions. Theoretical work explores implications that this feedback effect has for the equilibrium in financial markets and for economic efficiency. Current trends in information technology under the FinTech revolution change the nature of information processing in financial markets and so may change the nature of the feedback effect. In this article, I review the main themes of this developing literature and connect them to the current information revolution. I also discuss directions for future research.

Seventh International Scientific and Practical Conference «Transfer of Innovative Technologies 2021»

the 7th International Scientific and Practical Conference "Transfer of Innovative Technologies 2021" was held from May 19 to 20 at the Kyiv National University of Civil Engineering and Architecture. It presented creative ideas, innovative projects and practical developments in the fields of construction, architecture, solving urgent problems of engineering and facility design, environmental protection, current trends in information technology and others. The conference, which was held by videoconference, was attended by domestic scientists, teachers and students of educational institutions, industry representatives, well-known experts from around the world. A total of 128 applications were submitted from one and a half hundred participants, including 15 foreign ones from Australia, Poland, Slovakia, the USA, Kazakhstan, Germany and China.
 The competition commission determined the best works in the nominations: Presentation, Innovative project, Publication, awarded the Diplomas of the winners of 2021. Participants received Certificates, and the most active − Acknowledgments for their work, international scientific relations and organizational support of the forum. A preprint of the article was published in the Proceedings of the conference (online) and in the journal "Transfer of Innovative Technologies", Vol.4, No.1, and the presentations of the participants were published on the conference website. The best works are recommended for publication in the international scientific journals Transfer of Innovative Technologies, Underwater Technologies: Industrial and Civil Engineering. A decision was made to prepare and hold the next forum in 2022, to involve creative participants and new institutions in innovation activities, and to further integrate them into the world scientific space. The Organizing Committee thanks everyone for the presented materials and implementation of innovative technologies!

Input Data Characterization Using Machine Learning and Deep Learning

Seeing the current trends in Information technology, a large volume of heterogeneous data is produced widely across the world by means of social media sites such as Facebook, Instagram, Google plus, etc. and electronic gadgets used by humans for instance sensors. The generated data act as garbage and makes no sense until they are categorized. A strong need of data analytics or data filtering came into existence to filter the data into concrete categories. The generated data contain enormous features with huge dimensions. The high dimension data must be reduced to low dimension data to avoid curse of dimensionality and to build a better machine learning (ML) model.A ML model is built to perform the classification task that result into labeling of the data. In the first phase of work, a framework has proposed to process the data having features belonging to text and images using ML and DL algorithms. In the second phase of work, we have shown data related behavior using ML and DL framework. The proposed work is generic in sense of FS techniques and FE techniques using ML classifiers and DL classifiers. After carefully implementing the algorithms on the datasets we have evaluated the results taking accuracy as our performance metric. After carefully analyzing the accuracy it can be concluded that DL algorithms give better results than ML algorithms on both text and image dataset.

Conceptualisation of Hotel Guest Experience Assessment Process and Electronic Words of Mouth

The success of a hotel depends on the guests’ interpretation and reviews of their visit experience. Guests who perceived their visit experience as worthiness and satisfactory would circulate their experience to their acquaintances. In today’s information based era, their visit experience can be widely circulated through electronic word of mouth (e-wom) such as the social media. This paper aims to construct a research framework to study hotel guests experience responses as the result from their encounters with the hotel’s products and services during their stay. Unforgettable encounters would influence the guests’ future behaviour, starting with their commitment and eventually translated into reaction in the forms of electronic word of mouth responses. Methodically, an exhaustive review of the literature was carried out to establish a theoretical underpinning of hotel guests experience assessment process and their future responses. Perceived value and satisfaction are deemed as important measurements in the initial stage of the hotel guest visit experience outcomes. In line with the current information technology trends, the guests are expected to use electronic word of mouth to disseminate their visit outcomes. Academically, the study framework reduces the gaps related to the formulation of research constructs for hotel visit experience assessment. It is assertive that this paper would be practically beneficial to hotel operators or relevant stakeholders in order to gain a comprehensive understanding about hotel guests' visit experience responses and their future behaviour, including the electronic word-of-mouth response. Keywords: Commitment, electric word-of-mouth, hotel, perceived value, post visit responses, satisfaction.

LOSSLESS AND REVERSIBLE DATA HIDING IN ENCRYPTED IMAGES WITH PUBLIC KEY CRYPTOGRAPHY

In this paper, system uses the cryptography and steganography concept, which proposes a lossless, reversible, and combined data hiding methods for images encrypted by public key cryptosystems with probabilistic and homomorphic properties. In the lossless method, pixels of encrypted images are replaced with new values to embed additional data into LSB-planes of ciphertext pixels by multiple layer wet paper coding. Thus, original data can be directly extracted from encrypted image, and the data embedding does not affect the decryption of plaintext image. In the reversible method, histogram shrink is done before image encryption, so that the modification on cipher text images for data embedding will not cause any loss in plaintext image. With the combined lossless and reversible technique, receivers extract a part of embedded data before decryption, extract another part of embedded data and recover the original plaintext image after decryption. Keywords: Lossless, reversible, encryption, data hiding, decryption Cite this Article Amrtha Anand K, Dheena Kurien . Lossless and Reversible Data Hiding in Encrypted Images with Public Key Cryptography . Current Trends in Information Technology . 2016; 6(2): 27–33p.

Employers’ Feedback on the Competencies of MBA Graduates based on Curriculum and Student Outcomes

This study aims to determine the feedback of the immediate superiors or employers of the Master in Business Administration (MBA) graduates in terms of their competence when considered the curriculum and student outcomes of the MBA program as measuring tool. Descriptive type of research was utilized in the study. Findings revealed that research skill is one of the competencies which obtained the least score on the job performance of the graduates. Employers observed that the MBA graduates utilized appropriate application of technologies in bringing outputs to the customers and other stakeholders as course application of the current trends in Information technology. The graduates were also rated very good in promoting notable behavior in managing the people towards the attainment of vision and mission of the organization with international perspective as application of Human Resource Management and International Business Management.

Transforming Governmental Systems

Governmental as well as other public systems are facing new challenges due to, among other things, current information technology trends and changes in peoples’ lifestyles. Hence, ideas of web services for the citizens and agencies accessible over the net 24-hours per day are born. However, in order to implement this new type of net-based services a set of accessibility, integrity and security problems and hindrances are to be overcome. Further, the methodological challenges are far from unproblematic. Neither the artefact approach nor the approach of social systems design seems to be directly applicable. Instead, an approach called pragmatic systemics is proposed. At last, organizational transformation is not only a technical problem. Seen in a systemic perspective, the technological changes and the introduction of new artefacts have to be carefully balanced with changes in human competence, organizational structures, and system culture.

Romanization of Cyrillic Script: Core Competencies and Basic Research Strategies for Slavic Students, Scholars, and Educators

This article argues that a basic knowledge of the issues associated with the romanization of Cyrillic script, as well as of the research strategies designed to address them, constitutes a core competency for students and scholars of Slavic. The author maintains that, contrary to what might be expected, current trends in information technology and user search behavior render such Slavic‐specific information literacies as romanization more important than ever. Although the article's primary audience is Slavic studies librarians, it also provides model assignments that would be of interest to Slavic‐studies teaching faculty and educators.

Current Trends in Knowledge Production: An Historical–Institutional Analysis

Abstract Building on the author’s recent survey of Western knowledge institutions since antiquity, this article assesses the impact of current trends in information technology, higher education, science, and the environment on knowledge production. Its focus on institutions diverges from conventional histories of ideas, media, and technologies but also from the understandings of knowledge and information prevalent among economists. It instead identifies patterns by which entirely new institutions of knowledge supersede their predecessors, reconceptualizing today’s changes around the fitful process by which the laboratory, broadly understood, outgrows the tutelage of the academic disciplines.

The important role of meta‐analysis in international research in marketing

Considers the current thrust in marketing to create global products, brands and strategies but also to “act local” when appropriate. Deciding which elements have similar effects and which are significantly different conceptually requires meta‐analysis of each of the elements. Reviews some applications of marketing meta‐analysis with a focus on international research. The potential international impact of meta‐analysis in view of current trends in information technology and the globalization of marketing is promising, especially when the focus is on variables such as culture, geography, and economic condition rather than country per se.

Technological trends, product design and the environment

The paper begins with an overview of electronics and the environment. It then describes three current trends in information technology and telecommunications: convergence of products, miniaturisation and the use of networks. The potential impacts that these trends will have on the environment are discussed and summarised in an Abridged Life Cycle Assessment matrix. It is argued that all three trends may act to reduce the environmental impact of future products. However, this will require crucial changes to the design principles of electronic products and we should also change the philosophy of their use.

The status of GIS in undergraduate geography in Singapore

The extent to which Geographic Information Systems (GIS) techniques are being adopted in undergraduate geography programmes in Singapore and their type and level of usage is evaluated and discussed. In view of current trends in information technology in Singapore, the transfer of GIS skills to the general population, through schools, as part of the wider culture of Information Technology appears desirable.