A general introduction to lithium-ion batteries: From the first concept to the top six commercials and beyond

The birth of lithium-ion batteries (LIBs) is not a breakthrough scientific discovery overnight but a successor and continuous development of scientists for a long time based on the previous generation of electrochemical batteries. The development of LIBs and succeeding generations of batteries, however, is highly hopeful given the broad commercialization of LIBs during the previous ten years. Intensified research is required to create next-generation LIBs with drastically better performance, including enhanced energy density, charging rate, lifespan, stability, and safety, in order to fulfill the rising demand for energy storage. Research into LIBs and next-generation is currently in an explosive phase with the goal of overcoming the significant challenge posed by conventional LIBs that can keep up with the rapidly evolving needs of the electronics, mechanical, and automation industries, particularly electric vehicles. In this case, this tutorial review might offer a broad overview of LIBs as well as an optimistic look toward the upcoming generation

Building a P2P RDF Store for Edge Devices

The Semantic Web technologies have been used in the Internet of Things (IoT) to facilitate data interoperability and address data heterogeneity issues. The Resource Description Framework (RDF) model is employed in the integration of IoT data, with RDF engines serving as gateways for semantic integration. However, storing and querying RDF data obtained from distributed sources across a dynamic network of edge devices presents a challenging task. The distributed nature of the edge shares similarities with Peer-to-Peer (P2P) systems. These similarities include attributes like node heterogeneity, limited availability, and resources. The nodes primarily undertake tasks related to data storage and processing. Therefore, the P2P models appear to present an attractive approach for constructing distributed RDF stores. Based on P-Grid, a data indexing mechanism for load balancing and range query processing in P2P systems, this paper proposes a design for storing and sharing RDF data on P2P networks of low-cost edge devices. Our design aims to integrate both P-Grid and an edge-based RDF storage solution, RDF4Led for building an P2P RDF engine. This integration can maintain RDF data access and query processing while scaling with increasing data and network size. We demonstrated the scaling behavior of our implementation on a P2P network, involving up to 16 nodes of Raspberry Pi 4 devices.Comment: Accepted to IoT Conference 202

Semantic Programming for Device-Edge-Cloud Continuum

This position paper presents ThothSP, a Semantic Programming framework with the aim of lowering the coding effort in building smart applications on the Device-Edge-Cloud continuum by leveraging semantic knowledge. It introduces a novel neural-symbolic stream fusion mechanism, which enables the specification of data fusion pipelines via declarative rules, with degrees of learnable probabilistic weights. Moreover, it includes an adaptive federator that allows the Thoth>runtime to be distributed across multiple compute nodes in a network, and to coordinate their resources to collaboratively process tasks by delegating partial workloads to their peers. To demonstrate ThothSP's capability, we report a case study on a distributed camera network to show ThothSP's behaviour against a traditional edge-cloud setup.Comment: arXiv admin note: text overlap with arXiv:2202.1395

An Efficient Design of the Piezoresistive Pressure Sensor Applied for Micro Aerial Vehicle

In this research, the developing process of a piezoresistive pressure sensor working in the atmosphere environment applied in micro aerial vehicle using the MEMS fabrication method is introduced. The sensor consists of four Au/Cr piezoresistors in a Wheatstone bridge configuration on a wet oxidized silicon diaphragm. To fabricate the sensor, three lithographic steps were conducted: the first one is to define the resistors and Au/Cr lines/pads, the second and the third ones are to determine the width and the thickness of the square SiO2/Si diaphragm, respectively. The sensor diaphragm shape and thickness were defined by the anisotropic etching of Si in tetramethylammonium hydroxide (TMAH) solution, and the resistors array are formed by sputtering and wet etching method. The sensor size is ~6000 µm by 6000 µm. The sensor output voltage was measured for various applied pressure levels from 0 to 1.2 bar with 5V voltage supply. The fabricated sensor also exhibits a sensitivity of 50.01 mV/bar

An Efficient Design of the Piezoresistive Pressure Sensor Applied for Micro Aerial Vehicle

In this research, the developing process of a piezoresistive pressure sensor working in the atmosphere environment applied in micro aerial vehicle using the MEMS fabrication method is introduced. The sensor consists of four Au/Cr piezoresistors in a Wheatstone bridge configuration on a wet oxidized silicon diaphragm. To fabricate the sensor, three lithographic steps were conducted: the first one is to define the resistors and Au/Cr lines/pads, the second and the third ones are to determine the width and the thickness of the square SiO2/Si diaphragm, respectively. The sensor diaphragm shape and thickness were defined by the anisotropic etching of Si in tetramethylammonium hydroxide (TMAH) solution, and the resistors array are formed by sputtering and wet etching method. The sensor size is ~6000 µm by 6000 µm. The sensor output voltage was measured for various applied pressure levels from 0 to 1.2 bar with 5V voltage supply. The fabricated sensor also exhibits a sensitivity of 50.01 mV/bar

Pushing the Scalability of RDF Engines on IoT Edge Devices

Semantic interoperability for the Internet of Things (IoT) is enabled by standards and technologies from the Semantic Web. As recent research suggests a move towards decentralised IoT architectures, we have investigated the scalability and robustness of RDF (Resource Description Framework)engines that can be embedded throughout the architecture, in particular at edge nodes. RDF processing at the edge facilitates the deployment of semantic integration gateways closer to low-level devices. Our focus is on how to enable scalable and robust RDF engines that can operate on lightweight devices. In this paper, we have first carried out an empirical study of the scalability and behaviour of solutions for RDF data management on standard computing hardware that have been ported to run on lightweight devices at the network edge. The findings of our study shows that these RDF store solutions have several shortcomings on commodity ARM (Advanced RISC Machine) boards that are representative of IoT edge node hardware. Consequently, this has inspired us to introduce a lightweight RDF engine, which comprises an RDF storage and a SPARQL processor for lightweight edge devices, called RDF4Led. RDF4Led follows the RISC-style (Reduce Instruction Set Computer) design philosophy. The design constitutes a flash-aware storage structure, an indexing scheme, an alternative buffer management technique and a low-memory-footprint join algorithm that demonstrates improved scalability and robustness over competing solutions. With a significantly smaller memory footprint, we show that RDF4Led can handle 2 to 5 times more data than popular RDF engines such as Jena TDB (Tuple Database) and RDF4J, while consuming the same amount of memory. In particular, RDF4Led requires 10%–30% memory of its competitors to operate on datasets of up to 50 million triples. On memory-constrained ARM boards, it can perform faster updates and can scale better than Jena TDB and Virtuoso. Furthermore, we demonstrate considerably faster query operations than Jena TDB and RDF4J.BMBF, 01IS18025A, Verbundprojekt BIFOLD-BBDC: Berlin Institute for the Foundations of Learning and DataBMBF, 01IS18037A, Verbundprojekt BIFOLD-BZML: Berlin Institute for the Foundations of Learning and DataEC/H2020/661180/EU/A Scalable and Elastic Platform for Near-Realtime Analytics for The Graph of Everything/SMARTE

VisionKG: Unleashing the Power of Visual Datasets via Knowledge Graph

The availability of vast amounts of visual data with heterogeneous features is a key factor for developing, testing, and benchmarking of new computer vision (CV) algorithms and architectures. Most visual datasets are created and curated for specific tasks or with limited image data distribution for very specific situations, and there is no unified approach to manage and access them across diverse sources, tasks, and taxonomies. This not only creates unnecessary overheads when building robust visual recognition systems, but also introduces biases into learning systems and limits the capabilities of data-centric AI. To address these problems, we propose the Vision Knowledge Graph (VisionKG), a novel resource that interlinks, organizes and manages visual datasets via knowledge graphs and Semantic Web technologies. It can serve as a unified framework facilitating simple access and querying of state-of-the-art visual datasets, regardless of their heterogeneous formats and taxonomies. One of the key differences between our approach and existing methods is that ours is knowledge-based rather than metadatabased. It enhances the enrichment of the semantics at both image and instance levels and offers various data retrieval and exploratory services via SPARQL. VisionKG currently contains 519 million RDF triples that describe approximately 40 million entities, and are accessible at https://vision.semkg.org and through APIs. With the integration of 30 datasets and four popular CV tasks, we demonstrate its usefulness across various scenarios when working with CV pipelines

ANNOUNCEMENT OF THE SUSTAINABLE DEVELOPMENT REPORT OF VIETNAMESE HOTEL ENTERPRISES

The purpose of this study is to examine the factors affecting the publication of sustainability reports from the perspective of managers at 4-5 star hotels in Vietnam. Issues of corporate size, profitability, legal regulation, corporate governance and technology of the company were mentioned as factors that may affect the publication of the report on sustainable development. The author has synthesized the relevant background theory as well as previous outstanding studies on the issue of publishing sustainable development reports. SPSS 20 software was used to test the relationship between the factors affecting the publication of the Sustainable Development Report based on the manager's point of view. The results of the study show that the factors of business size, profitability, and legal regulations all affect the publication of sustainable development reports at 4-5 star hotels in Vietnam. A new finding of this study is that the two factors of corporate governance and the company's technology combine into a public governance factor based on technology and it is the technology that has the strongest influence on the publication of the Sustainable Development Report. The study once again confirms the relationship between the factors affecting the publication of the Sustainable Development Report and is a document to help researchers understand better in the research context in Vietnam, one of the leading countries in the world developing countries and have limited access to and use of secondary data

PILOT SCALE STUDY ON AMMONIUM REMOVAL IN PHAP VAN WATER PLANT, HANOI CITY

Joint Research on Environmental Science and Technology for the Eart