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In recent years, Blockchain technology has been recognized as one of the most important new technologies affecting businesses and society, with a very bright future ahead. This technology is known as one of the most critical technologies of industry 4. Given that Blockchain technology is a new concept, before implementing it, the organization must understand it and be prepared to accept it; otherwise, the organization will incur irreparable damages. The main purpose of this study is to provide a framework within which organizations can evaluate their readiness to implement Blockchain technology. For this purpose, after a library study and systematic literature review, this study provided the initial research framework using the meta-synthesis method. Finally, the Lawshe model was applied to validate the proposed framework for the organization's readiness to implement Blockchain technology. Based on the findings, the final established framework included seven main dimensions, including Blockchain-based business strategy, operations of a distributed system, culture, people in Blockchain decentralized network, decentralized governance, technology, and Blockchain-based product traceability. Besides, 37 main criteria affected these dimensions, which can help companies increase the level of Blockchain technology readiness. Finally, this framework was used to measure the readiness of an airline company. According to the results of the analysis, Blockchain-based business strategy, culture, and Blockchain-based product traceability showed a medium level of readiness. Moreover, none of the main dimensions of Blockchain technology readiness were sufficiently prepared in this case study. This paper suggests practical recommendations to improve the level of Blockchain technology readiness for the managers

As an emerging technology, blockchain can be used in all areas of e-commerce, one of which is advertising. The present study has been designed to identify a dynamic model of trust in blockchain-based advertising and acceptance of this type of advertising. In order to achieve the purpose of the research, the required information was collected by literature, background review and experts opinions. In the next step, the research information was analyzed using systems dynamics methodology (Sterman approach) and a dynamic research model was presented. After model validation and examining the causal relationships, simulations and scenario analysis were performed using Vensim software. The results show the positive effect of the audience, advertiser and advertising characteristics on trust in blockchain-based advertising and, consequently, the improvement of the audience loyalty coefficient. Also, the results of scenarios indicate an ascending growth (Pessimistic: about %60, Optimistic: about %80) in audience loyalty. Finally, practical suggestions were presented in accordance with the research results

The Architecture, Engineering, and Construction (AEC) industry rely heavily on Building Information Modeling (BIM). BIM is the collection of Information and Communication Technologies (ICT), interacting policies, and procedures. BIM is a tool for managing digital project data during the life cycle of a building. Despite the many benefits and features of BIM, the Malaysian construction industry's proliferation is confronted with adoption issues. Therefore, this research study intends to find the effect of BIM adoption factors in Malaysian AEC. Quantitative data collection from construction firms is gathered. The proposed model's theoretical foundations are based on Technology, Organization Environment framework. The model is tested and validated with the Smart PLS tool. The study's findings indicate that Perceived benefits, Organizational Capabilities, and Trialability are drivers of BIM adoption. Perceived cost and Insecurity are the barriers to BIM adoption. Perceived ease of use and compatibility does not affect BIM adoption. Finally, this study performs Importance Performance Map Analysis to provide recommendations to AEC stakeholders to address the BIM adoption issues for enhancing its diffusion in Malaysia.

In recent times amount of data is increasing rapidly and analysis of data is a must to come up with business decisions, predictions etc. It’s not just text are numbers which has to be stored properly. Data Types these days varies from images, video, social media data, surveys to blogs etc. When this is the case its mandatory to deal with Bigdata and to safeguard those Bigdata. Technologies available in Bigdata and Bitcoin helps us in achieving this. Bigdata technologies helps in storing the unstructured data effectively and processing of such voluminous data is taken care of. Hashing algorithms are used in Blockchain to keep the data safe. Hashing algorithms like SHA 256 are used to make it more secure. Its almost not possible to break the data available in Blockchain. Let’s try to secure the data even more using encryption algorithms to make sure that proper data is used for analysis etc.

Scientific sources demonstrate different attitudes of researchers to cryptocurrencies because they treat them as a category of currency, virtual money, commodity, etc. Accordingly, the relation to the valuation and risk of cryptocurrency as an investment object is different. The purpose of the article is to identify cryptocurrency value formation factors and determine the risks of investing in cryptocurrency. Cryptocurrency is simultaneously considered a currency, an asset with uncertain income, and a specific product, the price of which is determined by the energy costs for mining new cryptocurrency blocks. Thus, the paper examines the risks of investing in cryptocurrency from several positions. First, the study identifies the factors of formation of the value and risk of cryptocurrency as ordinary money based on comparing cryptocurrency with traditional money. Unlike traditional money, cryptocurrency is not tied to the economic performance of a particular country; also, central banks do not control or regulate their mining. Instead, the cryptocurrency emissions depend on the computational capacity of the equipment used for their mining. As a financial asset, cryptocurrency can be a “financial bubble” because their value increasing often exceeds the cost of mining. On the other hand, given the emergence of cryptocurrency as a phenomenon of the information economy, the paper analyses the impact of specific technical features (cryptographic hashing algorithm, the complexity of creating new blocks, the technology of verification of mining operations, etc.) on the risk of investing in cryptocurrency assets.

Building Information Modeling (BIM) is the backbone of the Architecture, Engineering, and Construction (AEC) industry. BIM is the collection of Information and Communication Technologies (ICT), interacting policies, and procedures. BIM generates a methodology to manage the project data in digital format throughout the building's life-cycle. Despite the numerous benefits and features of BIM, its proliferation remains limited and facing adoption issues. Although many existing studies discussed BIM adoption from contextual lenses, discipline-focused, there is still a scarcity of a comprehensive overview of technology adoption models and frameworks in BIM research. The purpose of this Systemic Literature Review (SLR) is to evaluate the current status of BIM adoption, technology acceptance theories, models used and find the research challenges. Furthermore, to identify the roles of independent constructs, dependent construct, moderators, and mediators in BIM adoption research. Also, the findings provide an in-depth description of the different stages of BIM adoption. Finally, this SLR will help the researchers for further research in the field of BIM adoption.

The study of path loss propagation is of high importance in telecommunication, for optimizing the efficiency of wireless communication networks. In this paper, four path loss propagation models; free space path loss (FSPL) model, Okumura model, Okumura-Hata model, and COST 231-Hata model were compared. The models were compared using measurement data from Choba, Port Harcourt, Nigeria. The data is gotten from a 4G walk test using two mobile applications. The first mobile application Network, Signal Info (version 5.68.07), was used to acquire the received signal strength in and the distance between the BTS antenna and the mobile antenna. While the second mobile application, G-NetTrack Lite (version 14.8), was used to map out the track path followed during the test. Choba, the study area, is a coastal suburban area with map coordinates 4.8941° N, 6.9263° E. The measured distance range was from 0.09 km to 0.45 km, and a path loss range of 69dB to 81dB. While the BTS and mobile antenna heights were 32 m and 1m respectively, with a carrier frequency of 800MHz. BTS transmission power of 23 dBm was assumed, based on 3GPP eNodeB recommendations. A graph comparison of the studied models showed that Okumura-Hata model and COST 231-Hata model had the closest predictions to the measured path loss. The need for better path loss models for 4G and 5G propagations was observed

Day by day demand for object tracing is increasing because of the huge scope in real-time applications. Object tracing is one of the difficult issues in the computer vision and video processing field. Nowadays, object tracing is a common problem in many applications specifically video footage, traffic management, video indexing, machine learning, artificial intelligence, and many other related fields. In this paper, the Enhanced Method of Object Tracing Using Extended Kalman Filter via Binary Search Algorithm is proposed. Initially, the background subtraction method was used for merge sort and binary search algorithm to identify moving objects from the video. Merge sort is to divide the regions and conquer the algorithm that arranges the region in ascending order. After sorting, the binary search algorithm detects the position of noise in sorted frames and then the next step extended the Kalman Filter algorithm used to predict the moving object. The proposed methodology is linear about the valuation of mean and covariance parameters. Finally, the proposed work considered less time as compared to the state of art methods while tacking the moving objects. Its shows less absolute error and less object tracing error while evaluating the proposed work.

Although Blockchain can significantly change the future of ERP systems as an innovative tech-nology, few researchers have gone into the details of this development. Most have given an overview of the changes ahead. Therefore, in this research, we have tried to use the method of Exploratory Content Analysis (ECA) by reviewing more than three hundred scientific articles in the field of Blockchain to analyze the effects of this technology on ERP system modules such as supply chain management, maintenance, finance, project management, manufacturing, and hu-man capital management. The result of this exploratory research is an architectural model for a blockchain-based ERP system. The researchers describe the functions of this system carefully, and the role of supporting technologies such as Smart Contract, IoT, Digital Wallet, Cloud Com-puting, and Building Information Model is clarified. We genuinely believe that this research could use as a reference model for ERP vendors and researchers in information systems and business process management

The improved model of the Agile Kanban (i-KAM) is developed to enhance the software project monitoring task when employing Agile project management (APM) approach. The i-KAM have been initially verified by 11 knowledge and domain experts. In consequence, it has been reconstructed and enhanced based on the remarks and recommendations provided by the experts. This paper aims to present the final evaluation results of i-KAM achieved from seven software practitioners participated in a focus group. The focus group method was selected because it is an empirical approach used in the evaluation studies conducted in the software engineering (SE) domain. Therefore, this method was employed to obtain the practitioners’ feedback on the proposed model. Results confirm the effectiveness of i-KAM, in which it can assist the project managers and team members in monitoring their projects’ progress effectively. In addition, it is indicated that i-KAM is an applicable model with easy and practical implementation. This study contributes to improve the task of monitoring software development projects within the APM environment. Accordingly, this would systematically facilitate the top managements’ work, and assist in making meaningful decisions regarding to the management of projects’ workflow. Practically, case studies will be carried out in different software development organizations (SDOs) to implement i-KAM in actual projects within real environments

Dimensionality reduction is among the data mining process that is used to reduce the noise and complexity of features in various datasets. Feature selection (FS) is one of the most commonly used dimensionalities that reduces the unwanted features from the datasets. FS can be either wrapper or filter. Wrappers select subsets of the feature with better classification performance but are computationally expensive. On the other hand, filters are computationally fast but lack feature interaction among selected subsets of features which in turn affect the classification performance of the chosen subsets of features. This study proposes two concepts of information theory mutual information (MI). As well as entropy (E). Both were used together with binary cuckoo optimization algorithm BCOA (BCOA-MI and BCOA-EI). The target is to improve classification performance (reduce the error rate and computational complexity) on eight datasets with varying degrees of complexity. A support vector machine classifier was used to measure and computes the error rates of each of the datasets for both BCOA-MI and BCOA-E. The analysis of the results showed that BCOA-E selects a fewer number of features and performed better in terms of error rate. In contrast, BCOA-MI is computationally faster but chooses a larger number of features. Comparison with other methods found in the literature shows that the proposed BCOA-MI and BCOA-E performed better in terms of accuracy, the number of selected features, and execution time in most of the datasets.

Blockchain technology is one of the revolutionary technologies in service-based industries. E-health services are considered as a major economic and social activity in the world in which patients, the medical community and service providers such as insurance organizations play a key role. In Iran, e-health services have been introduced for more than a decade, but it is seriously lagging behind the leading countries. According to the Blockchain Opportunity window, a technological and economic catch-up is possible in e-health services in the country. Decentralization, data transparency, security and privacy are the key features of Blockchain technology. Therefore, in this research, through case study strategy and using documents, scientific articles, evidence, statistics and events and opinions of experts, policy factors were presented to catch-up through the Blockchain technology opportunity window. The dimensions of the proposed policy framework were presented in 4 categories: macro policies, market, financing, and technology learning and development. This study presents technological catch-up policy framework by Blockchain technology to policymakers for using in e-health services.

At this time in history that the world is becoming smaller every day due to globalization; it is important to achieve an acceptable degree of trust and confidence in any field; and blockchain can put the world on this path. Since there is no central authority governing blockchain, its decentralized nature can turn it into an appropriate platform for project management. Implementing blockchain eliminates project management bureaucracies and allows a single, unchangeable, controllable, and encrypted source to be accessible to everybody and extensible throughout the project life cycle. This approach is the key to achieve an integrated information system and is one of the important reasons for blockchain applicability as an ideal platform for project management and construction. This issue that using blockchain technology in project management will bring about capacities and capabilities has not yet been seriously addressed. Changing the management of construction projects by blockchain is just an idea for now. This study aims to identify the capacity and platforms for developing blockchain technology in project management and construction using systematic and scoping literature reviews. Moreover, it provides some suggestions about the development and improvement areas of this technology. The review results showed that in all areas of project management and construction, there are applications relevant to blockchain technology that confirm the gradual understanding of the significance and positive impact of this technology on enhancing project management and construction performance. According to the results, a major part of blockchain studies was focused on “program and project management”, and two fields of human resources and behavioural areas and research in project management and schools of thought with a share of less than 2% of existing studies were neglected.

In the era of internet technologies, to provide wireless communication and transfer the information in seconds from one place to another has arrived because of the need to consume information technologies. All users desire to quickly access the smart world’s life and interact with the entire world socially. This paper proposed an environment for the safe and secure smart patient’s room connected to the WSN, BAN, and RFID. All the data will be transferred to the session key, secure and contains the patient’s information. The network connected through WSN and data will be sent through the session key to make an smart hospital’s patient cabin. The small token is there that will be transferred throughout the network to get authenticated by each network. This proposed scheme is secure enough to overcome the drawbacks of the other protocol in such a way as to make the protocol more secure from the entire adversary’s attack may occur.

Trust establishment (TE) among sensor nodes has become a vital requirement to improve security, reliability, and successful cooperation. Existing trust management approaches for large scale WSN are failed due to their low cooperation (i.e., dependability), higher communication and memory overheads (i.e., resource inefficient). This paper provides a new and comprehensive hybrid trust estimation approach for large scale WSN employing clustering to improve cooperation, trustworthiness, and security by detecting selfish sensor nodes with reduced resource (memory, power) consumption. The proposed scheme consists of unique features like authentication based data trust, scheduler based node trust, and attack resistant by giving the high penalty and minimum reward during node misbehavior. A task scheduling mechanism is employed for scheduling the significant task to reduce computation overhead. The proposed trust model would be capable to provide security against blackhole attack, grey hole attack, and badmouthing attack. Moreover, the proposed trust model feasibility has been tested with MATLAB. Simulation results exhibit the great performance of our proposed approach in terms of trust evaluation cost, prevention, and detection of malicious nodes with the help of analyzing consistency in trust values and communication overhead.