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Topic Review
Knowledge Management Model for Smart Campus
The application of smart campuses (SC), especially at higher education institutions (HEI) in Indonesia, is very diverse, and does not yet have standards. As a result, SC practice is spread across various areas in an unstructured and uneven manner. KM is one of the critical components of SC. However, the use of KM to support SC is less clearly discussed. Most implementations and assumptions still consider the latest IT application as the SC component. As such, this study aims to identify the components of the KM model for SC. This study used a systematic literature review (SLR) technique with PRISMA procedures, an analytical hierarchy process, and expert interviews. SLR is used to identify the components of the conceptual model, and AHP is used for model priority component analysis. Interviews were used for validation and model development. The results show that KM, IoT, and big data have the highest trends. Governance, people, and smart education have the highest trends. IT is the highest priority component. The KM model for SC has five main layers grouped in phases of the system cycle. This cycle describes the organization’s intellectual ability to adapt in achieving SC indicators. The knowledge cycle at HEIs focuses on education, research, and community service.
  • 594
  • 24 Jan 2022
Topic Review
Enhancing the Decision-Making Process through Industry 4.0 Technologies
In order to meet the increasingly complex expectations of customers, many companies must increase efficiency and agility. In this sense, Industry 4.0 technologies offer significant opportunities for improving both operational and decision-making processes. These developments make it possible to consider an increase in the level of operational systems and teams’ autonomy. However, the potential for strengthening the decision-making process by means of these new technologies remains unclear in the current literature. To fill this gap, a Delphi study using the Régnier Abacus technique was conducted with a representative panel of 24 experts. The novelty of this study was to identify and characterize the potential for enhancing the overall decision-making process with the main Industry 4.0 groups of technologies. Our results show that cloud computing appears as a backbone to enhance the entire decision-making process. However, certain technologies, such as IoT and simulation, have a strong potential for only specific steps within the decision-making process. This research also provides a first vision of the manager’s perspectives, expectations, and risks associated with implementing new modes of decision-making and cyber-autonomy supported by Industry 4.0 technologies.
  • 781
  • 20 Jan 2022
Topic Review
Fuel Consumption and CO2 of Light-Duty Vehicles
Due to the alarming rate of climate change, fuel consumption and emission estimates are critical in determining the effects of materials and stringent emission control strategies. In this research, an analytical and predictive study has been conducted using the Government of Canada dataset, containing 4973 light-duty vehicles observed from 2017 to 2021, delivering a comparative view of different brands and vehicle models by their fuel consumption and carbon dioxide emissions. Based on the findings of the statistical data analysis, this study makes evidence-based recommendations to both vehicle users and producers to reduce their environmental impacts. Additionally, Convolutional Neural Networks (CNN) and various regression models have been built to estimate fuel consumption and carbon dioxide emissions for future vehicle designs. This study reveals that the Univariate Polynomial Regression model is the best model for predictions from one vehicle feature input, with up to 98.6% accuracy. Multiple Linear Regression and Multivariate Polynomial Regression are good models for predictions from multiple vehicle feature inputs, with approximately 75% accuracy. Convolutional Neural Network is also a promising method for prediction because of its stable and high accuracy of around 70%. The results contribute to the quantifying process of energy cost and air pollution caused by transportation, followed by proposing relevant recommendations for both vehicle users and producers. Future research should aim towards developing higher performance models and larger datasets for building APIs and applications.
  • 813
  • 20 Jan 2022
Topic Review
Voxelisation Algorithms
Voxel-based data structures, algorithms, frameworks, and interfaces have been used in computer graphics and many other applications for decades. There is a general necessity to seek adequate digital representations, such as voxels, that would secure unified data structures, multi-resolution options, robust validation procedures and flexible algorithms for different 3D tasks.
  • 1.7K
  • 19 Jan 2022
Topic Review
Prediction of Customer Churn in Retail E-Commerce Business
Customer Relationship Management (CRM) is defined as a process in which the business manages its interactions with customers using data integration from various sources and data analysis.
  • 1.8K
  • 18 Jan 2022
Topic Review
Orientation Detection Mechanism Based on Artificial Visual System
As an important part of the nervous system, the human visual system can provide visual perception for humans. The research on it is of great significance to improve our understanding of biological vision and the human brain. Orientation detection, in which visual cortex neurons respond only to linear stimuli in specific orientations, is an important driving force in computer vision and biological vision. However, the principle of orientation detection is still unknown. 
  • 346
  • 18 Jan 2022
Topic Review
Location-Based Social Networks
There are several definitions for “geosocial network” or “location-based social network”: the first formal definition was given by Quercia et al. in 2010, who defined it as “a type of social networking in which geographic services and capabilities such as geocoding and geotagging are used to enable additional social dynamics”. One year later, Zheng refined this definition by stating that “a location-based social network (LBSN) does not only mean adding a location to an existing social network so that people in the social structure can share location embedded information but also consists of the new social structure made up of individuals connected by the interdependency derived from their locations in the physical world as well as their location-tagged media content, such as photos, video, and texts”. In 2013, Roick and Heuser defined LBSNs simply as “social network sites that include location information into shared contents”. Finally, one most recent definition is given by Armenatzoglou and Papadias and is the following: “geosocial network (GeoSN) is an online social network augmented by geographical information”.
  • 3.0K
  • 17 Jan 2022
Topic Review
Blockchain for Smart Mobility
The concept of a smart city aims to help cities to address these challenges by adapting modern information and communication technology. Smart mobility and transportation form one important aspect of smart cities. Inefficient mobility in cities can lead to problems such as traffic congestion, which results in frustration for residents and a decrease in the quality of life. In the context of smart mobility, blockchain can be used for transactions relating to ridesharing and electric charging, handling of interactions of platoon members, or serving as a foundation for communication between vehicles.
  • 1.1K
  • 17 Jan 2022
Topic Review
Mathematical Background of 5D model of the aorta
Visualization is crucial for the display and understanding of medical image data. For diagnostic and surgical planning, radiologists and surgeons must be able to evaluate the data appropriately. Many imaging systems’ data can incorporate both functional and structural information, resulting in 4D datasets. When the image contains spectral information, it can be extended to 5D in some circumstances. Overall, 5D imaging reveals more information than 4D imaging.
  • 383
  • 17 Jan 2022
Topic Review
Environmental Intelligence
We propose that coupled human and environmental information processing can be applied to concomitantly increase the scope and penetration of surveillance, leading to new opportunities to detect, track, quantify, predict and influence events and interactions across a wide range of operations. Academia and non-governmental organizations, state actors, and commercial interests are expected to utilize and benefit from environmental intelligence in differentiated manners.
  • 2.2K
  • 14 Jan 2022
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