(Semi-)Automatically Parsing Private Protocols for In-Vehicle ECU Communications

In-vehicle electronic control unit (ECU) communications generally count on private protocols (defined by the manufacturers) under controller area network (CAN) specifications. Parsing the private protocols for a particular vehicle model would be of great significance in testing the vehicle’s resistance to various attacks, as well as in designing efficient intrusion detection and prevention systems (IDPS) for the vehicle. This paper proposes a suite of methods for parsing ECU private protocols on in-vehicle CAN network. These methods include an algorithm for parsing discrete variables (encoded in a discrete manner, e.g., gear state), an algorithm for parsing continuous variables (encoded in a continuous manner, e.g., vehicle speed), and a parsing method based on upper-layer protocols (e.g., OBD and UDS). Extensive verifications have been performed on five different brands of automobiles (including an electric vehicle) to demonstrate the universality and the correctness of these parsing algorithms. Some parsing tips and experiences are also presented. Our continuous-variables parsing algorithm could run in a semi-automatic manner and the parsing algorithm from upper-layer protocols could execute in a completely automatic manner. One might view the results obtained by our parsing algorithms as an important indicator of penetration testing on in-vehicle CAN network.

Improving The Quality of Learning through Lesson Study Model Based on Innovation Class in SMPN 2, Menganti Gresik District

This study aims to determine the improvement of the quality of learning through the innovation-based class lesson study model school program. Research was conducted in three stages, namely: plan, do, see, for students in grades 7, 8, and 9. Techniques for collecting data through observation, and reporting. Data analysis was done in a qualitative, discrete manner. The results of the study showed the involvement of students, model teachers, teacher observers, Dispendik supervisors, committees and principals, parents / guardians of students and invitations from other schools were very active. Thus, improving the quality of learning through the innovation class based lesson study model school program has been very successful in improving the quality of expected learning.

Adaptive Probabilistic Protocol for WSN in Different Environments

Distinguishing the nature of events in Wireless Sensor Networks (WSNs), whether static or dynamic, determines the type of network action. The classification process is accomplished by adjusting the probability for electing the network head. In this paper, the Low Energy Adaptive Clustering Hierarchy (LEACH) protocol based on the adaptive clustering technique is adopted with two scenarios. In the first scenario, a homogenous environment with a dynamic event is deployed to continuously send the sensing events during the entire period in order to maintain the communication between the base station and the network. Meanwhile, the second scenario deals with heterogeneous environments for static and dynamic events. The static-heterogeneous event is established through sending the data in a discrete manner, while the continuous-heterogeneous event sends the data in a dynamic event. Simulation results using Matlab 2019b indicate that the throughput and lifetime are probability dependent, where increasing the probability value to 0.2 in homogenous networks leads to increased throughput, as it reaches approximately (14402) packets compared to (12029) packets in the fixed probability scenario. In contrast to the heterogeneous network, the lifetime is increased to reach (2806) rounds compared to fixed probability, which achieves (2160) rounds.

Deterministic Sampling from Uniform Distributions with Sierpinski Space-Filling Curves

In this paper the problem of sampling from uniform probability distributions is approached by means of space-filling curves (SFCs), a topological concept that has found a number of important applications in recent years. Departing from the theoretical fact that they are surjective but not necessarilly injective, the investigation focused upon the structure of the distributions obtained when their domain is swept in a uniform and discrete manner, and the corresponding values used to build histograms, that are approximations of their true PDFs. This work concentrates on the real interval [0,1], and the Sierpinski space-filling curve was chosen because of its favorable computational properties. In order to validate the results, the Kullback-Leibler distance is used when comparing the obtained distributions in several levels of granularity with other already established sampling methods. In truth, the generation of uniform random numbers is a deterministic simulation of randomness using numerical operations. In this fashion, sequences resulting from this sort of process are not truly random.

Single-cell RNA sequencing reveals profibrotic roles of distinct epithelial and mesenchymal lineages in pulmonary fibrosis

Pulmonary fibrosis (PF) is a form of chronic lung disease characterized by pathologic epithelial remodeling and accumulation of extracellular matrix (ECM). To comprehensively define the cell types, mechanisms, and mediators driving fibrotic remodeling in lungs with PF, we performed single-cell RNA sequencing of single-cell suspensions from 10 nonfibrotic control and 20 PF lungs. Analysis of 114,396 cells identified 31 distinct cell subsets/states. We report that a remarkable shift in epithelial cell phenotypes occurs in the peripheral lung in PF and identify several previously unrecognized epithelial cell phenotypes, including a KRT5−/KRT17+ pathologic, ECM-producing epithelial cell population that was highly enriched in PF lungs. Multiple fibroblast subtypes were observed to contribute to ECM expansion in a spatially discrete manner. Together, these data provide high-resolution insights into the complexity and plasticity of the distal lung epithelium in human disease and indicate a diversity of epithelial and mesenchymal cells contribute to pathologic lung fibrosis.

Knowledge Management & It's Origin, Success Factors, Planning, Tools, Applications, Barriers and Enablers

Over of the past several years, there have been rigorous discussions about the significance of knowledge management (KM) within the organization and the society. The management of knowledge is endorsed as a significant and essential factor for organizational existence and maintenance of ambitious strength. This article provides an in-depth knowledge of factors affecting KM. Literatures from 1992 to 2018 are covered in this article, 169 research papers have been explored which are related to classification of knowledge, factors affecting KM, KM tools and its planning & application. Various frameworks related to the successful implementation of KM and KM implementation tools proposed by previous authors are presented in this research article. KM is defined, classification of KM is presented, factors affecting KM are shown and its implementation strategies & tools are elucidated in available literatures in discrete manner.

Single-cell RNA-sequencing reveals profibrotic roles of distinct epithelial and mesenchymal lineages in pulmonary fibrosis

Pulmonary fibrosis is a form of chronic lung disease characterized by pathologic epithelial remodeling and accumulation of extracellular matrix. In order to comprehensively define the cell types, mechanisms and mediators driving fibrotic remodeling in lungs with pulmonary fibrosis, we performed single-cell RNA-sequencing of single-cell suspensions from 10 non-fibrotic control and 20 PF lungs. Analysis of 114,396 cells identified 31 distinct cell types. We report a remarkable shift in epithelial cell phenotypes occurs in the peripheral lung in PF, and identify several previously unrecognized epithelial cell phenotypes including a KRT5−/KRT17+, pathologic ECM-producing epithelial cell population that was highly enriched in PF lungs. Multiple fibroblast subtypes were observed to contribute to ECM expansion in a spatially-discrete manner. Together these data provide high-resolution insights into the complexity and plasticity of the distal lung epithelium in human disease, and indicate a diversity of epithelial and mesenchymal cells contribute to pathologic lung fibrosis.One Sentence SummarySingle-cell RNA-sequencing provides new insights into pathologic epithelial and mesenchymal remodeling in the human lung.

Displacement Measurement Method Based on the Rotating Paraboloid Array

Using an optical freeform surface to realize the precision measurement of displacement has become a research focus in the present day. However, the measurement range of this method is limited by the size of the freeform surface processed. In order to overcome this difficulty, this paper presents a two-dimensional displacement measurement system with a large range, which is composed of a slope sensor and a rotating paraboloid array. The slope sensor utilizes the optical structure of an autocollimator with minor optimization, and the rotating paraboloid array expands the measurement range of the system in a discrete manner. The experimental results showed that the optimized optical system enhanced the measurement accuracy to ±0.4 μm within the range of 1500 μm and the overall measurement error was approximately ±2 μm when measured within the range of 450 mm. The developed measurement system has potential applicability for detection of errors, such as the position error and straightness error of multi-axis systems.

Hardware Friendly Robust Synthetic Basis Feature Descriptor

Finding corresponding image features between two images is often the first step for many computer vision algorithms. This paper introduces an improved synthetic basis feature descriptor algorithm that describes and compares image features in an efficient and discrete manner with rotation and scale invariance. It works by performing a number of similarity tests between the feature region surrounding the feature point and a predetermined number of synthetic basis images to generate a feature descriptor that uniquely describes the feature region. Features in two images are matched by comparing their descriptors. By only storing the similarity of the feature region to each synthetic basis image, the overall storage size is greatly reduced. In short, this new binary feature descriptor is designed to provide high feature matching accuracy with computational simplicity, relatively low resource usage, and a hardware friendly design for real-time vision applications. Experimental results show that our algorithm produces higher precision rates and larger number of correct matches than the original version and other mainstream algorithms and is a good alternative for common computer vision applications. Two applications that often have to cope with scaling and rotation variations are included in this work to demonstrate its performance.

Modelling and analysis of barriers affecting the implementation of lean green agile manufacturing system (LGAMS)

Purpose Many types of research have already investigated the lean, green or agile manufacturing systems in a discrete manner or as combinations of two of them. In today’s competitive scenario, if industry wants to perpetuate its name in the market, then it has to supervene proper thinking and smart approach. Therefore, the combination of lean, green and agile manufacturing systems can provide better and beneficial results. The purpose of this paper is to discern the barriers to the combined lean green agile manufacturing system (LGAMS), understand their interdependence and develop a framework to enhance LGAMS by using total interpretive structural modeling (TISM) and MICMAC (Matriced’ Impacts Croise’s Multiplication Appliquée a UN Classement) Analysis. Design/methodology/approach This paper uses TISM methodology and MICMAC analysis to deduce the interrelationships between the barriers and rank them accordingly. A total of 13 barriers have been identified through extensive literature review and discussion with experts. Findings An integrated LGAMS has been presented that balances the lean, green and agile paradigms and can help supply chains become more efficient, streamlined and sustainable. Barriers are identified while referring to all three strategies to showcase the clear relevance. TISM models the barriers in different levels showcasing direct and important transitive relations. Further, MICMAC analysis distributes the barriers in four clusters in accordance with their driving and dependence power. Research limitations/implications The inferences have been drawn from a model developed on the basis of inputs from a small fraction of the industry and academia and may show variations when considering the whole industry. Practical implications The outcome of this research can contribute to bringing the change to the manufacturing systems used in most developing nations. Also, top managers considering adoption of LGAMS can be cautious of the most influential barriers. Originality/value A TISM-based model of the barriers to an integrated LGAMS has been proposed with evaluation of the influence of the barriers.