The objective of this paper is to give a comprehensive introduction to applied cryptography with an engineer or computer scientist in mind. The emphasis is on the knowledge needed to create practical systems which supports integrity, confidentiality, or authenticity. Topics covered includes an introduction to the concepts in cryptography, attacks against cryptographic systems, key use and handling, random bit generation, encryption modes, and message authentication codes. Recommendations on algorithms and further reading is given in the end of the paper. This paper should make the reader able to build, understand and evaluate system descriptions and designs based on the cryptographic components described in the paper.

[서평]「Applied Cryptography」

Developing efficient sensor materials with superior performance for selective, fast and sensitive detection of gases and volatile organic compounds (VOCs) is essential for human health and environmental protection, through monitoring indoor and outdoor air pollutions, managing industrial processes, controlling food quality and assisting early diagnosis of diseases. Metal–organic frameworks (MOFs) are a unique type of crystalline and porous solid material constructed from metal nodes (metal ions or clusters) and functional organic ligands. They have been investigated extensively for possible use as high performance sensors for the detection of many different gases and VOCs in recent years, due to their large surface area, tunable pore size, functionalizable sites and intriguing properties, such as electrical conductivity, magnetism, ferroelectricity, luminescence and chromism. The high porosity of MOFs allows them to interact strongly with various analytes, including gases and VOCs, thus resulting in easily measurable responses to different physicochemical parameters. Although much of the recent work on MOF-based luminescent sensors have been summarized in several excellent reviews (up to 2018), a comprehensive overview of these materials for sensing gases and VOCs based on chemiresistive, magnetic, ferroelectric, and colorimertic mechanisms is missing. In this review, we highlight the most recent progress in developing MOF sensing and switching materials with an emphasis on sensing mechanisms based on electricity, magnetism, ferroelectricity and chromism. We provide a comprehensive analysis on the MOF–analyte interactions in these processes, which play a key role in the sensing performance of the MOF-based sensors and switches. We discuss in detail possible applications of MOF-based sensing and switching materials in detecting oxygen, water vapor, toxic industrial gases (such as hydrogen sulfide, ammonia, sulfur dioxide, nitrous oxide, carbon oxides and carbon disulfide) and VOCs (such as aromatic and aliphatic hydrocarbons, ketones, alcohols, aldehydes, chlorinated hydrocarbons and N,N′-dimethylformamide). Overall, this review serves as a timely source of information and provides insight for the future development of advanced MOF materials as next-generation gas and VOC sensors.

Functional metal–organic frameworks as effective sensors of gases and volatile compounds

Carbon and graphene quantum dots (CQDs and GQDs), known as zero-dimensional (0D) nanomaterials, have been attracting increasing attention in sensing and bioimaging. Their unique electronic, fluores...

Review of Carbon and Graphene Quantum Dots for Sensing

Small carbon nanoparticles are an emerging member of the carbonaceous nanomaterial family and have been subsequently named as “carbon quantum dots” or “carbon nanodots”. Generally, carbon quantum dots are a type of spherical or sphere-like nanoparticles of less than 10 nm in size. Due to their unique properties, for example, size-dependent fluorescence, non-toxicity, biocompatibility, and easy accessibility, carbon quantum dots possess a great many potential applications in a range of fields from chemical sensing and imaging to catalysis and drug delivery, and thus are appealing to a number of researchers in nanoscience and nanotechnology. In this review, we give a brief introduction of the synthesis and fundamental properties of carbon quantum dots, then present their applications in metal ion sensing in detail along with illustrating the related mechanisms, and finally come up with some challenges currently faced and future outlooks for this fascinating carbon material. We hope this review could be helpful for readers who are preparing to join and/or have joined the research field of carbon quantum dots.

Carbon quantum dot-based nanoprobes for metal ion detection

Recent progress in the synthesis of graphene and derived materials for next generation electrodes of high performance lithium ion batteries

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A Versatile Wearable Based on Reconfigurable Hardware for Biomedical Measurements

Herein, we present the syntheses of a novel coordination polymer (CP) based on the perylene-3,4,9,10-tetracarboxylate (pery) linkers and sodium metal ions. We have chosen sodium metal center with the aim of surmising the effect that the modification of the metal ion may have on the relative humidity (RH) experimental measurements of the material. We confirm the role of the ions in the functionalization of the deposited layer by modifying their selectivity towards moisture content, paving the way to the generation of sensitive and selective chemical sensors.

/pdf/selectivity-of-relative-humidity-using-a-cp-based-on-s-block-34ide5fr.pdf

Selectivity of Relative Humidity Using a CP Based on S-Block Metal Ions

On the Fusion of Soft-Decision-Trees and Concept-Based Models

Demonstration of Bare Laser-Reduced Graphene Oxide Sensors for Ammonia and Ethanol

There is a growing interest in pushing computation to the edge, especially the problem-solving abilities of artificial neural networks (ANNs). This article presents a simplified method to obtain a ternary neural network based on the multilayer perceptron. The method is focused on resource-constrained devices, where memory, computing power, and battery are some of the most relevant constraints. A dynamic threshold is estimated to perform ternarization, and a new pruning technique is proposed to obtain a drastic reduction in the ANN’s size, with the corresponding decrease in resource utilization and power consumption of the resulting hardware. In addition, a support framework has been developed to automate hardware design exploration and generation from the network trained in software. Experimental results show that the proposed method and architecture, when implemented in a field-programmable gate array (FPGA), provide excellent figures in power (0.11–0.13 W) and efficiency (1225–1448 kfps/W) with respect to state of the art, being its efficiency double than the maximum one reported previously.

Diego P. Morales

Papers

A Versatile Wearable Based on Reconfigurable Hardware for Biomedical Measurements

Selectivity of Relative Humidity Using a CP Based on S-Block Metal Ions

On the Fusion of Soft-Decision-Trees and Concept-Based Models

Demonstration of Bare Laser-Reduced Graphene Oxide Sensors for Ammonia and Ethanol

Power-Efficient Implementation of Ternary Neural Networks in Edge Devices