Exchange Data Research Articles

Classifying Intensity Domains From Arm Cycle Ergometry Differs Versus Leg Cycling Ergometry.

Astorino, TA, Robson, T, and McMillan, DW. Classifying intensity domains from arm cycle ergometry differs versus leg cycling ergometry. J Strength Cond Res 37(11): 2192-2199, 2023-This study compared the distribution of exercise intensity domains in response to progressive leg cycle ergometry (LCE) and arm cycle ergometry (ACE). Seventeen active men and women (age and body fat = 26 ± 7 years and 18 ± 3%) initially performed graded exercise on each modality to assess maximal oxygen uptake (V̇o2max) and peak power output (PPO). Using a randomized crossover design, they subsequently performed moderate intensity continuous exercise consisting of three 15-minute bouts at 20, 40, and 60% PPO on each modality. Gas exchange data (V̇o2, V̇co2, and VE), respiratory exchange ratio, heart rate (HR), blood lactate concentration (BLa), and perceptual responses were acquired. Only 2 subjects were classified in the same intensity domains across modalities, with LCE eliciting more subjects exercising at "vigorous" and "near-maximal" intensities than ACE. Time spent above 70 (22 ± 7 vs. 15 ± 8 minutes, d = 1.03) and 80 %HRmax (15 ± 6 vs. 9 ± 6 minutes, d = 1.04) was significantly greater with LCE vs. ACE. Compared with ACE, LCE revealed significantly higher (p < 0.05) peak (94 ± 6 vs. 88 ± 9 %HRmax, d = 0.81) and mean HR (73 ± 6 vs. 66 ± 6 %HRmax, d = 1.20), V̇o2 (54 ± 5 vs. 50 ± 7 %V̇o2max, d = 0.68), and BLa (5.5 ± 2.0 vs. 4.7 ± 1.5 mM, d = 0.48). The results exhibit that progressive leg cycling at identical intensities elicits a greater cardiometabolic stimulus than ACE.

Towards V2I Age-Aware Fairness Access: A DQN Based Intelligent Vehicular Node Training and Test Method

Vehicles on the road exchange data with base station (BS) frequently through vehicle to infrastructure (V2I) communications to ensure the normal use of vehicular applications, where the IEEE 802.11 distributed coordination function (DCF) is employed to allocate a minimum contention window (MCW) for channel access. Each vehicle may change its MCW to achieve more access opportunities at the expense of others, which results in unfair communication performance. Moreover, the key access parameters MCW is the privacy information and each vehicle are not willing to share it with other vehicles. In this uncertain setting, age of information (AoI) is an important communication metric to measure the freshness of data, we design an intelligent vehicular node to learn the dynamic environment and predict the optimal MCW which can make it achieve age fairness. In order to allocate the optimal MCW for the vehicular node, we employ a learning algorithm to make a desirable decision by learning from replay history data. In particular, the algorithm is proposed by extending the traditional DQN training and testing method. Finally, by comparing with other methods, it is proved that the proposed DQN method can significantly improve the age fairness of the intelligent node.

The slope of assimilation rate against stomatal conductance should not be used as a measure of water use efficiency or stomatal control over assimilation

Quantifying water use efficiency, and the impact of stomata on CO2 uptake are pivotal in physiology and efforts to improve crop yields. Although tempting, relying on regression slopes from assimilation-stomatal conductance plots to estimate water use efficiency or stomatal control over assimilation is erroneous. Through numerical simulations, I substantiate this assertion. I propose the term ‘instantaneous transpiration efficiency’ for the assimilation-to-transpiration ratio to avoid confusion with ‘intrinsic water use efficiency’ which refers to the assimilation-to-stomatal conductance ratio, and recommend to compute both metrics for each gas exchange data point.

Elucidating Events within the Black Box of Enzyme Catalysis in Energy Metabolism: Insights into the Molecular Mechanism of ATP Hydrolysis by F1-ATPase.

Oxygen exchange reactions occurring at β-catalytic sites of the FOF1-ATP synthase/F1-ATPase imprint a unique record of molecular events during the catalytic cycle of ATP synthesis/hydrolysis. This work presents a new theory of oxygen exchange and tests it on oxygen exchange data recorded on ATP hydrolysis by mitochondrial F1-ATPase (MF1). The apparent rate constant of oxygen exchange governing the intermediate Pi-HOH exchange accompanying ATP hydrolysis is determined by kinetic analysis over a ~50,000-fold range of substrate ATP concentration (0.1-5000 μM) and a corresponding ~200-fold range of reaction velocity (3.5-650 [moles of Pi/{moles of F1-ATPase}-1 s-1]). Isotopomer distributions of [18O]Pi species containing 0, 1, 2, and 3 labeled oxygen atoms predicted by the theory have been quantified and shown to be in perfect agreement with the experimental distributions over the entire range of medium ATP concentrations without employing adjustable parameters. A novel molecular mechanism of steady-state multisite ATP hydrolysis by the F1-ATPase has been proposed. Our results show that steady-state ATP hydrolysis by F1-ATPase occurs with all three sites occupied by Mg-nucleotide. The various implications arising from models of energy coupling in ATP synthesis/hydrolysis by the ATP synthase/F1-ATPase have been discussed. Current models of ATP hydrolysis by F1-ATPase, including those postulated from single-molecule data, are shown to be effectively bisite models that contradict the data. The trisite catalysis formulated by Nath's torsional mechanism of energy transduction and ATP synthesis/hydrolysis since its first appearance 25 years ago is shown to be in better accord with the experimental record. The total biochemical information on ATP hydrolysis is integrated into a consistent model by the torsional mechanism of ATP synthesis/hydrolysis and shown to elucidate the elementary chemical and mechanical events within the black box of enzyme catalysis in energy metabolism by F1-ATPase.

The Cr(III) Exchange Mechanism of Macroporous Resins: The Effect of Functionality and Chemical Matrix, and the Statistical Verification of Ion Exchange Data

This study focuses on investigating and comparing the influence of the surface functional groups and chemical matrices of macroporous resin on the Cr(III) exchange mechanism. The results discussed herein indicate that sulfonic resin removed Cr(III) ions with faster kinetics than carboxylic resin. Equilibrium was established within 15 and 7 min for the carboxylic and sulfonic resins, respectively, with a 99.5% removal efficiency at 333 K. The Langmuir exchange capacity was observed to be higher for the sulfonic resin (1.5 mmol∙g−1) than the carboxylic resin (0.80 mmol∙g−1) at 333 K. The adsorption isotherms obtained for the carboxylic and sulfonic resins were H and S types, respectively, representing a higher affinity of the carboxylic resin for Cr(III) removal at a low metal ion concentration. Additionally, it was noted that the carboxylic resin preferentially co-sorbed H+ and Cr(OH)2+ ions below Cr(III) concentrations of 6–8 mmol.L−1. The H+ ions co-sorption was almost negligible, whereas the Cr(III) exchange was 87 and 34.5% for the carboxylic acid resin and sulfonic acid resins, respectively. The data of the concentration studies were evaluated using non-linear forms of Freundlich, Langmuir, and Dubinin–Radushkevich adsorption isotherm models, and the kinetic data were analyzed using pseudo-Ist- and pseudo-IIst-order kinetic models. The activation energy Ea for Amberlite IRC-50 (Na+) was greater (22.4 kJ∙mol−1) than that of Amberlyst-15 (Na+) 17 kJ∙mol−1, indicating a higher energy barrier for the ion exchange reaction on carboxylic resin. As per the findings of a statistical error analysis (RMSE and SSE) and absolute average relative distribution (AARD) statistical model, a close agreement between the experimental and theoretical values suggested that the Langmuir isotherm was well-fitted to the current adsorptive investigations. The interaction of the COO− and SO3− functional sites of the resins for the exchange of Cr(III) ions was validated through an FT-IR analysis. The macroporous resins used in the current study for Cr(III) exchange showed promising performances compared to other resins. The current investigations revealed valuable insights for choosing macroporous resins as adsorbents in water filtration systems.

Photosynthetic and hydraulic changes caused by water deficit and flooding stress increase rice’s intrinsic water-use efficiency

Effects of water deficit and flooding stress on rice’s intrinsic water-use efficiency (iWUE) and how iWUE variations are linked to stress-induced physiological changes are poorly understood. Here, we proposed a model-based approach to analyze iWUE across datasets and its relationship with physiological changes, using only leaf gas exchange data and plant hydraulic vulnerability parameters. We applied this approach to a leaf gas exchange dataset of rice, measured during the post-stress period of water deficit and flooding experiments. Results show that water deficit and flooding stress decreased rice’s photosynthetic capacity (Vcmax25) and water transport capacity (Kmax) during the post-stress period, and that these physiological changes altered the relationship between photosynthetic rate and stomatal conductance, leading to an increase in iWUE. Nevertheless, improved iWUE cannot avoid the yield reduction. Interestingly, the stress-induced decrease in Vcmax25 was significantly correlated with the decline in Kmax. The Vcmax25-Kmax relationship was significantly different between the water deficit and flooding treatments, with the slope of the latter being closer to 1:1. Model predicts that stress-induced disproportionate Vcmax25-Kmax co-reduction improved iWUE while maintaining a relatively high intercellular to atmosphere CO2 concentration ratio; this may represent optimal coordination between photosynthetic and hydraulic traits in response to stress. Our work has important implications for using leaf gas exchange data to diagnose variations in iWUE, and for improving our understanding of crop physiological responses to environmental stresses.

Excess post-exercise oxygen consumption after reduced exertion high-intensity interval training on the cycle ergometer and rowing ergometer.

To examine differences in oxygen consumption ([Formula: see text]O2), ventilation ([Formula: see text]E), excess post-exercise oxygen consumption (EPOC), energy expenditure (EE), and blood lactate concentration (BLa) between reduced exertion high-intensity interval training (REHIT) performed on the cycle- and rowing ergometer. Fourteen active participants (age = 27 ± 7yr) initially completed two assessments of maximal oxygen uptake. On two subsequent days, participants completed REHIT requiring three 20s "all-out" sprints on the cycle-(REHIT-CE) and rowing ergometer (REHIT-RE), followed by 60min rest during which gas exchange data and BLa were measured. During exercise, [Formula: see text]O2 increased significantly in response to REHIT-CE (0.21 ± 0.04 L/min vs. 1.34 ± 0.37 L/min, p < 0.001) and REHIT-RE (0.23 ± 0.05 L/min vs. 1.57 ± 0.47 L/min, p < 0.001) compared to rest, and [Formula: see text]O2 remained elevated at 15, 30, and 45min post-exercise in REHIT-CE (p < 0.001). However, [Formula: see text]O2 was only elevated 15min after REHIT-RE (0.23 ± 0.05 L/min vs. 0.40 ± 0.11 L/min, p < 0.001). [Formula: see text]O2 (1.57 ± 0.47 L/min vs. 1.34 ± 0.37 L/min, p = 0.003) and EE (94.98 ± 29.60kcal vs. 82.05 ± 22.85kcal, p < 0.001) were significantly greater during REHIT-RE versus REHIT-CE. EPOC was significantly greater after REHIT-CE versus REHIT-RE (6.69 ± 2.18 L vs. 5.52 ± 1.67 L, p = 0.009). BLa was ~ twofold higher in response to REHIT-CE vs. REHIT-RE (11.11 ± 2.43 vs. 7.0 ± 2.4, p < 0.001). Rowing-based REHIT elicits greater oxygen consumption and EE during exercise, yet lower EPOC and BLa. Whether rowing-based REHIT augments reductions in fat loss remains to be determined.

Evaluation of the Design and Development of the HeLe Newborn Hearing Screening Tele-Audiology Systems for the Philippines.

There is increasing interest in innovation development and management in the Philippines, especially in the last decade. In the advocacy for universal hearing health, the HeLe, "Hearing for Life'' Research Program was implemented. HeLe developed novel telehealth technologies and field tested a proof-of-concept service delivery model to improve provision of newborn hearing screening and intervention services in the Philippines. As the HeLe research period concludes, this appraisal was organized to document and assess the health information technology systems of the HeLe. The evaluation follows the elements of the Centers for Disease Control and Prevention (CDC) guidelines for evaluation of public health surveillance systems. It centers on the status of the eHealth-based components of the HeLe NHS interventions: HeLe NHS module in the Community Health Information Tracking System (CHITS) electronic medical records system, the Tele-Audiology module in National Telehealth System (NTS), and the HeLe NHS registry. The evaluation is based on interviews of key HeLe research staff and documentation review. The HeLe system has a stable, SQL-Server-based architecture. It is a secure, web-based system with clean separation of back-end database and front-end Web, using Secure Socket Layer (SSL) technology. Standardization of data via mapping ensures reliable, comparable measures. HeLe demonstrates that NHS data collected by the HeLe NHS device can be sent to, stored in, and extracted from the CHITS electronic medical record system and exchanged across platforms. Where actual patient and NHS data were available, this HeLe system is validated to be efficacious to capture and seamlessly exchange data across various eHealth platforms. These eHealth technologies are described to be at Technology Readiness Level 5, "technologies are validated in a relevant environment". The HeLe program, however, needs to address completeness in documentation as a standard practice, if only to ensure better management of risks introduced by novel eHealth systems in patient care. The CDC public health surveillance checklist used for this assessment is useful in identifying gaps in research management for the HeLe inventors. It is recommended to be incorporated to be standard and implemented early in the next iteration of the HeLe research. Overall, the HeLe technologies, in this initial stage of research, have achieved the purpose for which they were developed. As a novel technology-based NHS system, HeLe is a potentially powerful tool to assist in monitoring newborn hearing disease caseloads by community-based primary care clinics, NHS facilities, and hospitals that provide definitive medical services. As other health systems strengthening reforms take root in the Philippines, secure exchange of data electronically across the country would depend on sound technologies, including those used in hearing health. This paper can be instructive to the emerging research community in the eHealth and biomedical development space especially in resource-challenged settings. Likewise, lessons can reinforce institutional support from research agencies, clinicians, and state/ county or subnational health departments for policy and resource mobilization to better manage those identified with congenital hearing loss.

Effect of gas exchange data selection methods on resting metabolic rate estimation in young athletes.

This cross-sectional study analysed the effect of the gas exchange data selection methods on the resting metabolic rate (RMR) estimation and proposed a protocol shortening providing a suitable RMR estimation for young athletes. Sixty-six healthy young Brazilian athletes performed a 30-minute RMR assessment. Different methods of gas exchange data selection were applied: short and long-time intervals, steady-state (SSt), and filtering. A mixed one-way ANOVA was used to analyse the mean differences in gas exchange, RMR, respiratory exchange ratio (RER), and coefficients of variation across all methods. Additionally, paired Student's t-test were used to compare the first and best SSt RMR values for each SSt method (3, 4, and 5-min). The 5-min SSt method provided the lowest RMR estimate (1454 kcal.day-1). There was a statistical difference between methods (F = 2.607, p = 0.04), but they presented a clinically irrelevant absolute difference (~36 kcal.day-1). There were no differences in RER among methods. In addition, using the SSt method, 12 minutes of assessment were enough to obtain a valid estimation of RMR. The 5-min SSt method should be employed for assessing the RMR among young athletes, considering the possibility of obtaining a shortened assessment (~12 min) with an acceptable and low coefficient of variation.

Photosynthetic Response of Blueberries Grown in Containers.

Recently, there has been increased interest in container blueberry production as a viable alternative to open-field blueberry planting. Container production of blueberries offers numerous advantages, among these, a lack of limitation by suboptimal soil conditions in the open field and the ability to control substrate pH, drainage, and organic matter. The photosynthetic response for three container-grown Southern highbush blueberry (interspecific Vaccinium hybrids) cultivars including 'Jewel', 'Meadowlark', and 'Victoria' and a rabbiteye blueberry (Vaccinium virgatum) 'Baldwin', were measured during the spring and summer of 2022. It was hypothesized that the three cultivars evaluated would have different photosynthetic responses. The objective of this study was to determine the photosynthetic activity of different blueberry cultivars during the first year of crop establishment. A series of measurements were conducted every 2 h throughout the day and for different dates using a gas exchange data analyzer on newly matured fully expanded leaves located in the top middle section of the canopy for each cultivar. The response curves showed that net photosynthesis (A) became saturated at moderate light, with saturation occurring at a photosynthetic photon flux density (PPFD) of 1932 µmol m-2 s-1. At this point, the rate of CO2 assimilation was approximately 16.84 µmol CO2 m-2 s-1. No differences in (A) were found among cultivars. Overall, the attained values of photosynthesis provide a strong conceptual basis for understanding the cultivar variation response when grown in containers; therefore, the containerized system may serve as a production system for early fruiting blueberries in Alabama, USA.

Multi-Label Classification with Deep Learning for Retail Recommendation

Selecting the right retail business for a location is crucial for the success of a business because it determines the likelihood of favourable return on investment. One common approach used in retail recommendation is multi-class classification, where retail businesses are categorized into different classes or categories based on various features or attributes. Existing research in the field of retail recommendation has extensively proposed and evaluated different algorithms, techniques, and approaches for multi-class classification in the context of retail recommendation, however, limited work has been focusing on formulating retail recommendation as a multi-label problem. This is because in retail recommendation, one location can fit multiple retail businesses so that it can provide more options to recommend the most suitable business for the location. Therefore, multi-label classification will be attempted in this study. An analytical dataset will be constructed that provides comprehensive insights into the characteristics of the business area, and subsequently employ deep learning technique for multi-label classification. The analytical dataset is constructed based on the list of sites of interest data from YellowPages, population data from Humanitarian Data Exchange (HDX) and property data sourced from brickz.my. This work will be focusing on implement deep learning technique which is 1D convolutional neural network (CNN) model. The findings showed that the proposed model achieved 61.22% in terms of accuracy.

Electricity Market Dynamics and Regional Interdependence in the Face of Pandemic Restrictions and the Russian–Ukrainian Conflict

Electricity constitutes a significant part of the consumption basket of European households and companies. Since energy products are essential components of almost all products and services, any change in energy prices directly impacts the general price level of those products and services. Therefore, this study aims to conduct a comprehensive analysis of power exchange data between 2019 and 2022. For the analysis, we examined the data of 15 countries. In the research, we compared electricity prices in European power exchanges using the Jaccard similarity index and the overlap coefficient, using the DAM hourly prices between 1 January 2019 and 31 December 2022. We transformed the time series into networks using the visibility graph procedure and compared the networks of the studied countries using the two comparison methods with the degree distribution functions. Our aim is to examine how the market anomalies caused by the COVID-19 pandemic and the Russian–Ukrainian conflict affect European electricity markets and how quickly the repercussions spread across the studied countries’ exchanges, and whether they show persistent or anti-persistent characteristics. The results support that similar market effects significantly influence the pattern of price changes among the countries. The methods forming the basis of the research can provide significant assistance in analyzing market trends and contribute to a better understanding of market processes.

Peak Ground Velocity (PGV) estimation of Mw 5.6 Cianjur earthquake November 11, 2022 using Global Positioning System (GPS)

The primary purpose of GPS is to be used for positioning, navigation, and timing (PNT). In the last decade, research on GPS for earthquake hazards has increased rapidly, such as for tectonic deformation, GPS seismology, modeling earthquake source parameters, estimation of magnitude, etc. In this study, following the Mw 5.6 Cianjur earthquake on November 11, 2022, we estimate the peak ground velocity from the CJUR GPS station, which is located about 15 km from the epicenter. We compute GPS velocity from the high-rate GPS receiver independent exchange (RINEX) data and broadcast ephemeris. Using a narrow line combination of L1 and L2 observations, we invert velocity epoch by epoch. The result shows the CJUR GPS station has a peak ground velocity of about 11.5 cm/s and equal to VI MMI scale. The peak ground velocity from the GPS station could be important for deriving the earthquake shakemap. By increasing the number of GPS stations in Indonesia, it is very important to support earthquake hazard monitoring.

A New NOMA-Based Two-Way Relaying Scheme

Two-Way Relaying (TWR) has been widely investigated in the literature as an efficient relaying scheme for dual-hop cooperative transmissions. In TWR, two nodes exchange data through an intermediate relay, where both nodes simultaneously send signals towards the relay in the first time slot. The relay, in turn, combines both received signals into one signal and sends it back to both nodes on the second time slot. In this paper, the spectral efficiency is further enhanced in TWR scheme by adopting Non-Orthogonal Multiple Access (NOMA) technique. Specifically, the transmitted signals from the nodes in the first time slot are composed based on NOMA transmission and intended to multiple intermediate relay-nodes. Consequently, each relay will extract its own symbols, combine them and send them in the second time slot. The improvement of the spectral efficiency in our system, as compared to the Conventional TWR, is linearly proportional to the number of relay-nodes that can be installed. The performance of the proposed scheme is mathematically analyzed in terms of the spectral efficiency and error performance, shown significant gain when compared to the conventional TWR scheme.

Popularity And Prevalence Of Gas Exchange Data Processing Methods In Peer-reviewed Literature: A Scoping Review

Popularity And Prevalence Of Gas Exchange Data Processing Methods In Peer-reviewed Literature: A Scoping Review

Rates of convergence for Gibbs sampling in the analysis of almost exchangeable data

Motivated by de Finetti’s representation theorem for almost exchangeable arrays, we want to sample p∈[0,1]d from a distribution with density proportional to exp(−A2∑i<jcij(pi−pj)2), where A is large and cij’s are non-negative weights. We analyze the rate of convergence of a coordinate Gibbs sampler used to simulate from these measures. We show that for every non-zero fixed matrix C=(cij), and large enough A, mixing happens in Θ(A2) steps in a suitable Wasserstein distance. The upper and lower bounds are explicit and depend on the matrix C through few relevant spectral parameters.

Digital twin-driven SDN for smart grid: A deep learning integrated blockchain for cybersecurity

Internet of Things (IoT)-enabled Smart Grid (SG) network is envisioned as the next-generation network for intelligent and efficient electric power transmission. In SG environment, the Smart Meters (SMs) mostly exchange services and data from Service Providers (SPs) via insecure public channel. This makes the entire SG ecosystem vulnerable to various security threats. Motivated from the aforementioned challenges, we incorporate Digital Twin (DT) technology, Software-Defined Networking (SDN), Deep Learning (DL) and blockchain into the design of a novel SG network. Specifically, a secure communication channel is first designed using an authentication method based on blockchain technology that has the ability to withstand a number of well-known assaults. Second, a new DL architecture that includes a self-attention mechanism, a Bidirectional-Gated Recurrent Unit (Bi-GRU) model, fully connected layers, and a softmax classifier is designed to enhance the attack detection process in SG environments. To deliver low latency and real-time services, the SDN is next employed as the network’s backbone to send requests from SMs to a global SDN controller. DT technology is finally integrated into the SDN control plane, which stores the operating states and behavior models of SMs and communicates with SMs. The efficiency of the proposed framework is demonstrated by the blockchain implementation used in the SG network to assess computing time for the various numbers of transactions per block. Finally, the numerical results based on the N-BaIoT dataset shows better intrusion detection.

Towards an Effective Service Allocation in Fog Computing.

The Internet of Things (IoT) generates a large volume of data whenever devices are interconnected and exchange data across a network. Consequently, a variety of services with diverse needs arises, including capacity requirements, data quality, and latency demands. These services operate on fog computing devices, which are limited in power and bandwidth compared to the cloud. The primary challenge lies in determining the optimal location for service implementation: in the fog, in the cloud, or in a hybrid setup. This paper introduces an efficient allocation technique that moves processing closer to the network's fog side. It explores the optimal allocation of devices and services while maintaining resource utilization within an IoT architecture. The paper also examines the significance of allocating services to devices and optimizing resource utilization in fog computing. In IoT scenarios, where a wide range of services and devices coexist, it becomes crucial to effectively assign services to devices. We propose priority-based service allocation (PSA) and sort-based service allocation (SSA) techniques, which are employed to determine the optimal order for the utilizing devices to perform different services. Experimental results demonstrate that our proposed technique reduces data communication over the network by 88%, which is achieved by allocating most services locally in the fog. We increased the distribution of services to fog devices by 96%, while simultaneously minimizing the wastage of fog resources.

Evaluation of Influence of Nano Kaolin on Temperature Sensitivity of Asphalt Pavement Based on Analytic Hierarchy Process

In order to further explore the five different dosage of nano kaolin sensitivity to the temperature of the modified asphalt concrete, combined with constant temperature heating heating experiment and stir yogurt machine constant temperature cooling experiment of these two kinds of innovative experiment of heat exchange data, based on the analytic hierarchy process (ahp) innovative obtains the temperature win min optimum dosage of nano kaolin, The influence of different nano-kaolin content on the temperature sensitivity of modified asphalt was evaluated as a whole. The experimental results show that when the content of nano-kaolin is 7%, the temperature sensitivity of asphalt mixture is the best at 10 different temperatures compared with the other four mixtures. With the increase of nano-kaolin content, the temperature sensitivity of asphalt mixture is first superior and then inferior.

SECURE TEXT ENCRYPTION FOR IOT COMMUNICATION USING AFFINE CIPHER AND DIFFIE-HELLMAN KEY DISTRIBUTION ON ARDUINO ATMEGA2560 IOT DEVICES

In an Internet of Things (IoT) system, devices connected to the system exchange data. The data contains sensitive information about the connected devices in the system so it needs to be protected. Without security, the data in the IoT system can be easily retrieved. One way to prevent this is by implementing cryptography. Cryptography is a technique for protecting information by using encryption so that only the sender and receiver can see the contents of the information contained therein. The implementation of cryptography on IoT devices must consider the capabilities of IoT devices because in general IoT devices have limited processing capabilities compared to computer devices. Therefore, the selection of encryption algorithms needs to be adjusted to the computational capabilities of IoT devices. In this research, the affine cipher cryptography algorithm and Diffie-hellman key distribution algorithm are applied to the arduino atmega2560 IoT device. The purpose of this research is to increase the security of the IoT system by implementing cryptography. The method used in this research involves setting up a sequence of encryption and decryption steps using an affine cipher and diffie-hellman algorithms. Furthermore, these algorithms were implemented on an Arduino IoT device. Finally, the decryption time based on the number of characters and the avalanche test were tested. The results showed that on average, Arduino can perform decryption using affine cipher and diffie-hellman algorithms in 0.07 milliseconds per character. The avalanche test produced an average percentage of 45.51% from five trials.