The 21st century has witnessed precipitous changes spanning from the way of life to the technologies that emerged. We have entered a nascent paradigm shift (industry 4.0) where science fictions have become science facts, and technology fusion is the main driver. Thus, ensuring that any advancement in technology reach and benefit all is the ideal opportunity for everyone. In this study, disruptive technologies of industry 4.0 were explored and quantified in terms of the number of their appearances in published literature. The study aimed at identifying industry 4.0 key technologies which have been ill-defined by previous researchers and to enumerate the required skills of industry 4.0. Comprehensive literature survey covering the field of engineering, production, and management was done in multidisciplinary databases: Google Scholar, Science Direct, Scopus, Sage, Taylor & Francis, and Emerald Insight. From the electronic survey, 35 disruptive technologies were quantified and 13 key technologies: Internet of Things, Big Data, 3D printing, Cloud computing, Autonomous robots, Virtual and Augmented reality, Cyber-physical system, Artificial intelligence, Smart sensors, Simulation, Nanotechnology, Drones, and Biotechnology were identified. Both technical and personal skills to be imparted into the human workforce for industry 4.0 were reported. The review identified the need to investigate the capability and the readiness of developing countries in adapting industry 4.0 in terms of the changes in the education systems and industrial manufacturing settings. This study proposes the need to address the integration of industry 4.0 concepts into the current education system.

https://downloads.hindawi.com/journals/je/2020/4280156.pdf

Exponential Disruptive Technologies and the Required Skills of Industry 4.0

An innovative design of a hybrid chain coding algorithm for bi-level image compression using an agent-based modeling approach

A highly efficient chain code for compression using an agent-based modeling simulation of territories in biological beavers

The new frontiers open different directions within the higher and deeper knowledge structure using unemployed nano sizes domains. The BaTiO3 and other ceramic materials have fractal configuration nature based on three phenomena. First, ceramic grains have fractal shape looking as a contour in cross section or as a surface. Second, there is the so-called “negative space” made of pores and intergranular space. Third, there is fractal Brownian motion (fBm) within the material, during and after sintering, in the form of microparticle flow: ions, atoms, and electrons. Here, we took upon ourselves the task of extending Coble’s model, with already generalized Euclidean geometries, by fractal nature correction. These triple factors make the very peculiar microelectronic environment electro-static/dynamic combination. The stress is here set on inter-granular micro-capacity in function of higher energy harvesting and storage. Constructive fractal theory allows identifying micro-capacitors with fractal electrodes. The method is based on the iterative process of interpolation which is compatible with the grain model itself. Inter-granular permeability is taken as the fundamental thermodynamic parameter function of temperature and enthalpy (Gibbs free energy), which are very important for a structure-energy relation.

Ceramic materials and energy—Extended Coble’s model and fractal nature

Segmentation of pathological lung regions from the body regions is the most challenging part in any Computer Aided Diagnosis (CAD) system due to the presence of Pathological Bearing Regions (PBR) which lies on the lung’s periphery. Here, a unique pathological lung segmentation method called reference-model based segmentation that uses shape property of human lung is proposed. This method trounces the difficulties in segmentation from traditional approaches by examining the shape knowledge of lung. The proposed segmentation approach constructs a reference lung model from input slices using a novel Sampling Lines Algorithm (SLA) and extracts the shape features. The segmentation work is validated using dataset consisting of Digital Imaging and Communications in Medicines (DICOM) standard chest CT images of seven patients from cancer institute Chennai, nine patients from Gemini Scans, Chennai and fourteen patients from Lung Image Data-base Consortium image collection (LIDC-IDRI). The segmentation method’s performance is analyzed against widely used segmentation methods namely Graph Cuts (GC), Region Growing (RG), Active Contour and Flood Fill in terms of accuracy, specificity, sensitivity, overlap score, Jaccard index, and also Dices similarity coefficients (DSC). The numerical outcomes specify that the proposed work attains an improved result against widely used segmentation techniques.

A model based segmentation approach for lung segmentation from chest computer tomography images

A generalized iterative scanline fill algorithm intended for use in real-time applications and its highly optimized machine code implementation are presented in this paper. The algorithm uses the linear image representation in order to achieve the fast memory access to the pixel intensity values. The usage of the linear image representation is crucial for achieving the highly optimized low-level machine code implementation. A few generalization features are also proposed, and discussion about the possible real-time applications is given. The proposed efficient machine code implementation is tested on several PC machines, and a set of numerical results is provided. The machine routine is compared with standard and optimized implementations of the 4-way flood fill algorithm and scanline fill algorithm. The machine code implementation performs approximately 2 times faster than the optimized scanline fill algorithm implementation and 6 times faster than standard iterative scanline fill algorithm implementation on two-dimensional image data structure. Furthermore, the machine routine proved to perform even more than 15 times faster than the optimized flood fill algorithm implementations. Provided results prove the efficiency of the proposed generalized scanline fill algorithm and its advantage over the state-of-the-art algorithms, and clearly show that optimized machine routine is capable of performing the real-time tasks.

Generalized N-way iterative scanline fill algorithm for real-time applications

In this paper, we present Tesla’s Fountain in ceramics technology reconstruction from basic 3D model, simulation of the engine, light and fluids till the real materialization. As the one of the most important model purposes, we enrich this solution by additional multicolor lights. All of this elements are designed based on Tesla’s original patent no. 1,113,716, US patent office, granted Oct,13. In this model we applied ceramics technology based on ceramic materials casting and sintering. At the time when the patent was granted, the metal materials science and technologies were more advanced than the ceramics technology and applications. We performed all materials characteristics analyses and preparation steps based on the one author’s patent no. 46121, Serbia patent office, granted 21.12.1991. This is one original two patents solution with complete new over-bridging by the state-of-the-art computer modeling and simulation technology.

Tesla’s Fountain – Modeling and simulation in ceramics technology

This paper presents an efficient new image compression and decompression methods for document images, intended for usage in the pre-processing stage of an OCR system designed for needs of the “Nikola Tesla Museum” in Belgrade. Proposed image compression methods exploit the Run-Length Encoding (RLE) algorithm and an algorithm based on document character contour extraction, while an iterative scanline fill algorithm is used for image decompression. Image compression and decompression methods are compared with JBIG2 and JPEG2000 image compression standards. Segmentation accuracy results for ground-truth documents are obtained in order to evaluate the proposed methods. Results show that the proposed methods outperform JBIG2 compression regarding the time complexity, providing up to 25 times lower processing time at the expense of worse compression ratio results, as well as JPEG2000 image compression standard, providing up to 4-fold improvement in compression ratio. Finally, time complexity results show that the presented methods are sufficiently fast for a real time character segmentation system .

/pdf/efficient-image-compression-and-decompression-algorithms-for-4h54gop8tj.pdf

Efficient image compression and decompression algorithms for ocr systems

In this paper, as a pre-processing part of character segmentation system, an automatic document skew correction approach, based on Hough transform, is presented. Document skew is a common pre-processing problem and diverse approaches have been proposed in the past. The importance of solving this problem lies in the fact that further character segmentation process is impossible if document image is skewed. The character segmentation algorithm extended with skew correction algorithm has been proved to be efficient since the experimental results showed that successful character segmentation percentage is higher than 85 after the skew correction. Character segmentation algorithm results for skewed and de-skewed documents are also provided using the original Nikola Tesla’s documents from the “Nikola Tesla Museum”.

/pdf/automatic-optimized-document-skew-pre-processor-for-4o0evaabwz.pdf

Automatic optimized document skew pre-processor for character segmentation algorithm

This paper presents a general, ultra-fast approach for geometrical image transformations, based on the usage of linear lookup hash tables. The new method is developed to fix distortions on document images as part of a real-time optical character recognition (OCR) system. The approach is generalized and uses linear image representation combined with pre-computed lookup tables. Backward mapping is used for generation of lookup tables, while forward mapping is presented as an alternative and more efficient mapping model for specific cases. Also, a theoretical space and time complexity analysis of the proposed method is provided. To achieve maximal computational performance, pointer arithmetic and highly-optimized low-level machine code implementations are provided, including the specialized implementations for horizontal mirror, vertical mirror, and 90° rotation. Also, a modified variant of the approach, based on auto-generated machine code is presented. Very high computational performances are achieved at the expense of memory usage. The performances from the perspective of time complexity are analyzed and compared with classical implementation, FPGA implementation, and other implementations of the image rotation. Numerical results are given for a set of different PC specifications to provide full insight into the implementation performances. The processing time for very large images are below 200 ms for backward mapping and below 100 ms for forward mapping for most machines, which is 30–60 times faster than the classical implementation, 5–20 times faster than the FPGA implementation, and up to 6 times faster than other implementations of image rotation. Original documents belonging to Nikola Tesla are used for visual demonstration of performance.

Boban Arizanovic

Papers

Generalized N-way iterative scanline fill algorithm for real-time applications

Tesla’s Fountain – Modeling and simulation in ceramics technology

Efficient image compression and decompression algorithms for ocr systems

Automatic optimized document skew pre-processor for character segmentation algorithm

Ultra-fast basic geometrical transformations on linear image data structure