Tag Values Research Articles

An efficient key tag missing identification protocol for multiple regions in the Industrial Internet of Things

Radio Frequency Identification (RFID) is a special wireless network technology that uses radio frequency communication to achieve non-contact automatic identification through tags affixed to items. As one of the core technologies for physical layer communication in the Industrial Internet of Things(IIoT), RFID technology has been widely used in inventory management, supply chain management, access control identification, and many other areas. In practical application scenarios, the value and importance of some special tags far exceeds that of other tags. Therefore, in many cases, managers only need to pay attention to the status of these special tags, i.e., key tags, and not the status of all tags. However, the response of ordinary tags to reader commands will seriously interfere with identifying key missing tags. Therefore, we propose a novel protocol, Random Grouped Missing Key Tag Identification (RGKMTI), designed for multi-region key tag identification. RGKMTI employs a region-based sequential tag identification method to identify each group of tags individually, which effectively reduces collision slots and utilizes the duality property of slots containing only two key tags during the missing key tag verification phase, where the reader can verify two tags by transmitting at most a single tag ID, which significantly reduces the transmission load and shortens the total execution time. The experimental results show that the RGKMTI is significantly better than the existing schemes in terms of execution time and time efficiency, even though it reduces the identification time by 19.83% and improves the time efficiency by 6.82% compared with the best existing schemes.

Evaluations of Crypto-System AES Using Multiple Bloc Ciphering Mode

Cryptography, a scientific field that has existed even before the beginning of computer science. This article looks at the development symmetric crypto-system, which falls within the framework of image security, by Advanced Encryption Standard (AES- Advanced Encryption Standard) algorithms. AES algorithm is not integrity protected. Cryptanalysis could use modified encrypted image of each ciphered bloc for generating oracle and getting the key. A new crypto-system uses hash function named AES-GCM (Advanced Encryption Standard-) for solving this problem. Using Galois Counter Mode (GCM) combined with Secure Hash Algorithm 256 bits (SHA-256) or BLAKE2s hash function, the old mode of ciphering like: Cipher FeedBack (CFB), Output FeedBack (OFB), Cipher Block Chaining (CBC), Electronic Codebook Block (ECB) and CounTeR (CTR) mode encryption, will increase the security level at confidentiality and integrity. In this article, robustness of the crypto-system will be evaluated by multiple criteria, indeed the statistical analysis, sensitivity measurement and performance measurement. For the statistical analysis, the histogram is flat and the correlation between adjacent pixel is not linear for the encrypted image. The relation between clear image and encrypted image doesn’t exist. For the sensitivity analysis, Number of Pixel Changing Rate (NPCR) and Unified Averaged Changed Intensity (UACI) permit to avoid differential attack of the crypto-system. The two values are respectively near 99% and 30%. For performance measurement, the similarity of the decrypted image and original image will be tested. The Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE) are equals of infinity and zero. The decrypted image and original image are the same. The integrity of the image on the crypto-system will be evaluated by modifying one bit of the encrypted image. The decryption process doesn’t give decrypted image and show that the tag value is incorrect.

The use of predator tags to explain reversal movement patterns in Atlantic salmon smolts (Salmo salar L.).

Acoustic telemetry has seen a rapid increase in utility and sophistication in recent years and is now used extensively to assess the behavior and survival rates of many aquatic animals, including the Atlantic salmon. As part of the salmon's complex life cycle, salmon smolts are thought to make a unidirectional migration from fresh water to the sea, which is initiated by changes in their physiology. However, some tag movement patterns do not conform with this and can be difficult to explain, particularly if the tagged fish has been eaten by a predator. This study combines the use of predator tags with machine learning techniques to understand the fate of migrating salmon smolts and thereby improve estimates for migration success. Over 3 years between 2020 and 2022, 217 salmon smolts (including wild and hatchery-reared ranched fish) were acoustically tagged and released into an embayment on the west coast of Ireland. Some tagged smolts were observed to return from the estuary back into a saline lagoon through which they had already migrated. To distinguish between the movement of a salmon smolt and that of a predator, predator tags were deployed in migrating smolts in 2021 and 2022. The addition of a temperature sensor in 2022 enabled the determination of predator type causing the returning movement. A significant number of predator tags were triggered, and the patterns of movement associated with these triggered tags were then used with two types of machine learning algorithms (hierarchical cluster analysis and random forest) to identify and validate the behavior of smolts tagged without extra sensors. Both models produced the same outputs, grouping smolts tagged with predator tags with smolts tagged without the additional sensors but showing similar movements. A mammalian predator was identified as the cause of most reversal movement, and hatchery-reared ranched smolts were found to be more likely predated upon by this predator than wild smolts within the lake and the estuary. However, overall migration success estimates were similar for both wild and hatchery-reared ranched fish. This study highlights the value of predator tags as an essential tool in the overall validation of detection data.

Investigation of the capabilities of algorithms for automated quality assurance of DICOM metadata of chest X-ray examinations

Purpose. To evaluate the quality of filling DICOM tags responsible for the orientation, scanning area and photometric interpretation of the image, as well as to develop and test algorithms for automatically determining the true values of these tags for chest x-rays and fluorograms.Materials and methods. To assess the quality of filling DICOM tags, were used 1885 studies obtained from the Unified Radiological Information Service of the Unified Medical Information and Analysis System (ERIS EMIAS). For training and validation of algorithms for automatic determination of the true values of tags, were used datasets of radiographs in standard frontal and lateral projections, from open databases and from ERIS EMIAS (12,920 studies in total). The deep neural network architecture VGG 19 was chosen as the basis for creating algorithms.Results. We found that the frequency of missing values in DICOM tags can range from 6 to 75%, depending on the tag. At the same time, up to 70% of filled tag values have errors. We obtained next models: a model for determining the anatomical area of x-ray examination, a model for determining the projection on the chest x-ray, a model for determining the photometric interpretation of the image. All of the obtained algorithms have high classification quality indicators. The AUC for each of the obtained models was more than 0.99.Conclusions. Our study shows that a large number of studies in diagnostic practice contain incorrect values of DICOM tags, which can critically affect the implementation of software based on artificial intelligence technology in clinical practice. Our obtained algorithms can be integrated into the development process of such software and used in the preprocessing of images before their analysis.

A CrowdSensing-based approach for proximity detection in indoor museums with Bluetooth tags

In this work, we investigate the performance of a proximity detection system for visitors in an indoor museum exploiting data collected from the crowd. More specifically, we propose a CrowdSensing-based technique for proximity detection. Users’ smartphones can collect and upload RSS (Received Signal Strength) values of nearby Bluetooth tags to a backend server, together with some context-information. In turn, the collected data are elaborated with the goal of calibrating two proximity detection algorithms: a range-based and a learning-based algorithm. We embed the algorithms with R-app, a visiting museum application tested in the Monumental Cemetery’s museum located in Piazza dei Miracoli, Pisa (IT). We detail in this work an experimental campaign to measure the performance improvements of the CrowdSensing approach with respect to state-of-the-art algorithms widely adopted in the field of proximity detection. Experimental results show a clear improvement of the performance when data from the crowd are exploited with the proposed architecture.

Current 137Cs accumulation by mushrooms in different site types of scots pine forests of Ukrainian Polissia

The study of 137Cs radioactive contamination of fruiting bodies of mushrooms was carried out in September - October 2022 in 18 sampling sites laid out in the Korosten district of Zhytomyr region in 3 of the most widespread forest site types (FST): fresh infertile pine site type (А2), fresh fairly infertile pine site type (В2) and moist fairly infertile pine site type (В3). It was found that the highest levels of 137Cs content in investigated FST were characteristic of symbiotrophic mushroom species - Сortinarius mucosus, Сortinarius caperatus, Sarcodon imbricatus, Imleria badia, Tricholoma equestre, Paxillus involutus, Hygrophorus hypothejus, and the lowest - for xylotrophes-saprotrophes such as Armillaria mellea and Tapinella atrotomentosa. When analyzed, it was shown that interspecific differences of average values of 137Cs aggregated transfer coefficient (Tag) among mushrooms in each FST varied in a wide range: they reached 1.1⋅103 times in FST-A2 - from 435 in Cortinarius mucosus to 0.4 m2⋅kg-1⋅10-3 in Armillaria mellea; 71.4 times - in FST-B2 - from 162 in Sarcodon imbricatus to 2.3 m2⋅kg-1⋅10-3 in Armillaria mellea; and 12 times - in FST-B3 - from 111 in Imleria badia to 9.2 m2⋅kg-1⋅10-3 in Leccinum scabrum. Also, it was shown that in genus Russula even in the same FST-B2 among five studied species a 24-fold change in average values of 137Cs Tag are observed - from 67 in Russula vinosa to 2.8 m2⋅kg-1⋅10-3 in Russula aeruginea. The results of ANOVA were discussed as well as the essentiality of the difference of the average values of Tag in mushroom species in different FST.

The Correlation Between Lipid Profile and Proteinuria In Adult Nephrotic Syndrome Patients in Bangladeshi Population

The nephrotic syndrome is a constellation of abnormalities that includes massive proteinuria, hypoalbuminemia and edema. Dyslipidemia is an important secondary biochemical abnormalities in nephrotic syndrome due to proteinuria and hypoalbuminemia. Dyslipidemia in nephrotic syndrome involved in the cardiovascular risk and also accelerates the progression of glomerular dysfunction. This study was conducted to evaluate the relationship between dyslipidemia and proteinuria in adult nephrotic syndrome patients. A total of 50 (fifty) diagnosed adult nephrotic syndrome patients from the Dept of Nephrology, Dhaka Medical College, Dhaka with age range from 20-50 years of both sexes were enrolled as study subjects. To evaluate the correlation between serum TC, TAG, HDL-C and LDL-C with 24 hour urinary total protein. This case control study was carried out in the Department of Biochemistry, Dhaka Medical College, Dhaka, during the period of July 2013 to June 2014. With baseline information, lipid profile and 24 hour urinary total protein of study subjects were estimated. Mean values of the variables were determined. Correlation between variables were determined by Pearson's correlation test by using SPSS for windows version 20.0. For all the statistical analysis p<0.05 was considered as significant. Mean(±SD) values of serum total cholesterol (Tchol), TAG, HDL-C and LDL-C in adult nephrotic syndrome patients were 288.23±35.67 mg/dl, 174.53±18.86 mg/dl, 23.71±4.58 mg/dl and 231.16±34.28 mg/dl respectively. Mean value of 24 hour urinary total protein in study subjects was 5.65±0.54 gm/d. Positive correlation was found between 24 hour urinary total protein and Tchol (r=0.476, p<0.05), TAG (r=0.354, p<0.05), LDL-C (r=0.444, p<0.05) and positive correlation was found between 24 hour urinary total protein and HDL-C (r=0.028 p>0.05). Dyslipidemia in adult nephrotic syndrome possesses a significant relationship with proteinuria which could predispose them to develop coronary artery disease.
 Bangladesh J Med Biochem 2018; 11(2): 24-33

Effects of reverse geocoding on OpenStreetMap tag quality assessment

AbstractOpenStreetMap (OSM), a widely‐used open‐source geographic information system platform, provides a vast geographic dataset in which users contribute both geometric information (nodes, ways, and relations) and semantic information (tags). This method of voluntary contributions is governed by the collective effort of the users. It is widely acknowledged that the quantity of tag information is substantial, but its quality is often poor. Researchers are therefore trying to assess the quality of the tags and enhance the data through various integration experiments. This article investigates the validity of the tags for geographical objects in metropolitan areas using municipal data and a reverse geocoding technique. The proposed method evaluates the data quality and the matching process carried out by reverse geocoding, using municipal points of interest as a reference. The accuracy of the tag and address information and road network centrality metrics were assessed for the OSM objects that were matched to the locations of interest. The tags were found to match the points of interest with an accuracy of 88%. Furthermore, the tag values were categorized and analyzed based on their similarity. It is concluded that in metropolitan settings where centers of interest are closely located, the accuracy of tags and addresses tends to decrease.

Variability of activity concentrations and radial distributions of 137Cs and 90Sr in trunk wood of Scots pine and Silver birch

This study analyzes the variability of 137Cs and 90Sr concentrations in wood and their radial distributions in the trunks of Scots pine and Silver birch trees in the small uniformly contaminated forest stands in the Chornobyl Exclusion Zone. Concentrations of both radionuclides follow a lognormal distribution with a large scatter of values measured in the trees within the stands (GSD ranges from 1.6 to 2.0). No correlation was found between the concentrations of the two radionuclides measured in individual trees, or between their concentrations and tree diameter. The average 137Cs and 90Sr Tag were 8.4 × 10−4 m2 kg−1 and 8.8 × 10−3 m2 kg−1 for pine, respectively, and 9.3 × 10−4 m2 kg−1 and 1.1 × 10−2 m2 kg−1 for birch, indicating a much higher availability of 90Sr for uptake by the studied species. For 137Cs, the Tag values are within the range recommended by the IAEA Handbook (IAEA, 2010), while the values for 90Sr exceed the recommended range for birch and are close to its upper value for pine.The highest concentrations of 137Cs in pine at the height of 1.3 m were measured in the youngest sapwood rings; they were lower in the rest of the sapwood and decreased further in the heartwood, but remained relatively high even in annual rings that were the heartwood at the time of deposition, suggesting sapwood-to-heartwood translocation of the radionuclide by diffusion and/or ray transport. In contrast, 90Sr concentrations increased through the sapwood from the trunk periphery in pine trees up to 80 years old and remained stable through the sapwood in older trees (except for higher concentrations in the young annual rings), but dropped to zero in physiologically inactive heartwood tissues. In most birch trees, regardless of age, 137Cs concentrations demonstrated an increasing trend from the trunk periphery towards the pith, while concentrations of 90Sr were relatively stable in the whole trunk except in the oldest annual rings, where they increased sharply, likely indicating active transport of the radionuclide to senescing tissues.

Real-Time Scheduling on Hierarchical Heterogeneous Fog Networks

Cloud computing is widely used to support offloaded data processing for applications. However, latency constrained data processing has requirements that may not always be suitable for cloud-based processing. Fog computing brings processing closer to data generation sources, by reducing propagation and data transfer delays. It is a viable alternative for processing tasks with real-time requirements. We propose a scheduling algorithm RTH2S (Real Time Heterogeneous Hierarchical Scheduling) for a set of real-time tasks on a heterogeneous integrated fog-cloud architecture. We consider a hierarchical model for fog nodes, with nodes at higher tiers having greater computational capacity than nodes at lower tiers, though with greater latency from data generation sources. Tasks with various profiles have been considered. For regular profile jobs, we use least laxity first (LLF) to find the preferred fog node for scheduling. For tagged profiles, based on tag values, the jobs are split in order to finish execution before the deadline, or the LLF heuristic is used. Using HPC2N workload traces across 3.5 years of activity, the real-time performance of RTH2S versus comparable algorithms is demonstrated. Our proposed approach is validated using both simulation (to demonstrate scale up) as well as a lab-based testbed.

Dynamics of <sup>137</sup>Cs Transfer Factors to Agricultural Products after the Chernobyl Accident: Grain, Potatoes, and Vegetables

The results of the analysis of the 137Cs aggregated transfer factors (Tag) to crops (cereals, potatoes, and vegetables) produced in the districts of the Bryansk region affected after the Chernobyl accident are presented. The aggregated transfer factors in the year of the deposition as well as the dynamics of Tag in the subsequent years depended considerably on the fertility of soils subjected to contamination. The transfer factors of 137Cs to crops in the areas with higher fertility were 3–8 times lower (depending on the plant species) than in the areas with low fertility, and the most significant differences were observed for cereals. Decrease in Tag values was of irregular nature. The half-lives of 137Cs aggregated transfer factors for the period from 1986 to 2021 were calculated. It is shown that the first half-life values calculated for the period of intensive application of countermeasures (1987–1991) were from 0.7 to 1.4 years. The second half-lives varied from 7.3 to 17.3 years. In some areas, after a strong reduction in 137Cs concentrations in crops after 1994, there was a slow increase in 137Cs aggregated transfer factors, which can be explained by insufficient compensation for this decrease of geochemical binding of 137Cs in the soil. Later the dynamics of crop contamination was determined by multidirectional processes: i.e., increase in 137Cs transfer to plants and natural decrease of radionuclides bioavai-lability in soils under the influence of geochemical processes. In areas with intensive application of countermeasures, the reduction of Tag to crops was determined to a greater extent by the influence of agrochemical countermeasures. In the areas with limited application of countermeasures, the natural biogeochemical processes determining radionuclide binding by the soil-absorbing complex made the predominant contribution to the Tag reduction. Limitations of the approach based on the estimation of half-lives and the necessity of using the history of countermeasures implemented, as well as the soil fertility for prediction of the 137Cs intake by plants is noted.

SISTEM PERPAJAKAN, NORMA DAN KEADILAN PADA PENGGELAPAN PAJAK

Abstract
 Taxe play an important role in increasing state tax revenues, several factors that influence the occurrence of tax evasion, namely the uneven taxation system, low taxpayer norms and lock of tax justice. MSMEs in Tlogomas Malang Village partially This study uses quantitative methods. Determination of the sampel is abtained as many as 34 MSME taxpayers in Tlogomas Malang Village, the data collection technique used by the researcher is a questionnaire, the data analysis method used isregression multiple using SPSS 26 program. The result of the study prove that the taxation system has a significant effect on tax evasion with a tag value of 4.191, norms system has a significant effect on tax evasion with a tag value of thg 4.070 and fairness is significant effect on tax evasion with a value of 6.027 As for what needs to be considered by taxpayers, namely paying in time.

Machine Learning Strategy for Wall Heat Flux Prediction in Aerodynamic Heating

The efficient and accurate prediction of the aeroheating performance of hypersonic vehicles is a challenging task in the thermal protection system structure design process, which is greatly affected by grid distribution, numerical schemes, and iterative steps. From the inspiration of the theoretical analysis and machine learning strategy, a new wall heat flux prediction framework is proposed first by establishing the relationship between the wall heat flux and the flow variables at an extreme temperature point (ETP) in the normal direction of the corresponding wall grid cell, which is named the machine learning (ML)-ETP method. In the training phase, the flow properties and their gradients at the ETP and the distance from the ETP normal to the wall are employed as feature values, and the accurate wall heat flux predicted by the converged fine grid is regarded as the tag value. With the assistance of the trained regression model, the heat flux of the same configuration with a coarse grid in the wall-normal direction could be predicted accurately and efficiently. Moreover, test cases of different configurations and inflow conditions with a coarse grid are also carried out to assess the model’s generalization performance. All comparison results demonstrate that the ML-ETP strategy could predict wall heat flux more rapidly and accurately than the traditional numerical method due to its nonstrict grid distribution requirements. The improvement of the predictive capability of the coarse-graining model could make the ML-ETP method an effective tool in hypersonic engineering applications, especially for unsteady ablation simulations or aerothermal optimizations.

A text mining and topic modeling based bibliometric exploration of information science research

This study investigates the evolution of information science research based on bibliometric analysis and semantic mining. The study discusses the value and application of metadata tagging and topic modeling. Forty-two thousand seven hundred thirty-eight articles were extracted from Clarivate Analytic's Web of Science Core Collection 2010-2020. This study was divided into two phases. Firstly, bibliometric analyzes were performed with VOSviewer. Secondly, the topic identification and evolution trends of information science research were conducted through the topic modeling approach latent dirichlet allocation (LDA) is often used to extract themes from a corpus, and the topic model was a representation of a collection of documents that is simplified using topic-modeling-toolkit (TMT). The top 10 core topics (tags) were information research design, information health-based, model data public, study information studies, analysis effect implications, knowledge support web, data research, social research study, study media information, and research impact time for the studied period. Not only does topic modeling assist in identifying popular topics or related areas within a researcher's area, but it may be used to discover emerging topics or areas of study throughout time.

Safety tag generation and training material recommendation for construction workers: a persona-based approach

PurposeEffective construction safety training has been considered to play a significant role in reducing the incidence of accidents. However, the current safety training methods pay less attention to the relationship between workers' personalized characteristics and their learning needs, which results in workers' low learning participation and poor training effect. The purpose of this paper is to improve the participation and effect of safety training for construction workers with a persona-based approach.Design/methodology/approachThis paper presents a persona-based approach to safety tag generation and training material recommendation. By extracting the demographic characteristics and behavior patterns tags of construction workers, a neural network algorithm is introduced to calculate the learning needs tags of workers, and the collaborative filtering recommendation method is integrated to enrich the innovation of recommendation results. Offline experiments and online experiments are designed to verify the rationality of the proposed method.FindingsThe results show that the learning needs of workers are closely related to their background. The proposed method can effectively improve workers' interest in materials and the training effect compared with conventional safety training methods. The research provides a theoretical and practical reference for promoting active safety management and achieving worker-centered safety management.Originality/valueFirst, a persona-based approach is introduced to establish a novel framework for solving the problem of personalized construction safety management. Second, an artificial intelligence algorithm is used to automatically extract the learning needs tag values and design a hybrid recommendation method for construction workers' personalized safety training. The collaborative filtering method is integrated to enrich the innovation of recommendation results.

RFID Indoor Positioning Based on AP Clustering and Improved Particle Swarm Algorithm

This paper proposes a method based on AP clustering and an improved particle swarm algorithm for radio frequency identification (RFID) indoor positioning, called the AP-PSO method. Firstly, an AP clustering algorithm is used to cluster the RSSI values of the experimental region tags with similarity, in order to achieve the division of tagged regions, reduce the search area of the later improved particle swarm algorithm, and reduce the search time. Secondly, the learning factor of the particle swarm algorithm is dynamically adjusted, in order to improve the search ability and convergence speed of the global optimal solution of particles. The experimental results show that the algorithm can effectively achieve RFID indoor positioning of the tags to be measured, with high positioning accuracy and with the algorithm spending less time.

A Novel Sustainable Processing Mode for Burr Classified Prediction of Weak Rigid Drilling Process Using a Fusion Modeling Method

Weakly rigid drilling systems, such as the industrial robot, are widely used in aerospace, military, and other fields due to its good flexibility and large scope of operation. However, the weak rigidity can easily cause burrs, seriously affecting the precision of parts and product performance. To reduce the heavy deburring process and to improve continuous production and sustainable processing capacity, accurate prediction of burr quality is a prerequisite. Traditional burr forming theory cannot accurately predict the drilling defects. Data-driven approaches can be independent of prior knowledge and discover relationships between process parameters and machining precision directly from the data structure itself. Therefore, to take advantage of both approaches, a fusion model was established for burr classified prediction. On the one hand, the drilling and burr forming process was firstly modeled, and preliminary classification results for burrs were calculated. On the other hand, according to the measured data, the errors between initial calculation results and actual classification results were obtained and selected as the tag values of dataset, which served as inputs for the error compensation model of burrs. Finally, by training the network of TCN–DNN using the drilling data, the burr classified prediction in a weak rigid hole-making system was realized. Experimental results showed that compared with traditional drilling theory, the prediction accuracy of the proposed model improved by 25%, reaching 91.67%. The results can provide a basis for judging the process of burr post-treatment, which has practical guiding significance. This method is beneficial to reduce the heavy deburring process and to improve sustainable processing capacity.

Aggregated transfer factor of 137Cs in edible wild plants and its time dependence after the Fukushima Dai-ichi nuclear accident

We obtained the aggregated transfer factor (Tag) for 10 common edible wild plant species (four perennial spermatophytes, bamboo shoot, two tree species, and three perennial pteridophytes) in northeastern Japan. Measurement of Tag was carried out in 2012–2019 and we also used publicly available data for 2012–2019: food monitoring data and total deposition data from an airborne survey. The Tag obtained from actual measurements agreed well with Tag values calculated from the publicly available data. The sampling locations were only identified at the municipal level and uncertainty of the deposition for the publicly available data, and thus Tag values showed substantial variation. The Tag of the perennial spermatophytes, including bamboo shoot, and perennial pteridophytes showed single exponential decline with effective half-lives of approximately 2 years, whereas those of tree species did not show distinct temporal change. These results imply that data since 2014 are applicable for Tag estimation for long-term potential ingestion dose in the future to the public because of the slow decline. The calculated Tag values of all species for 2014–2019 ranged from 6.1 × 10−5 to 5.2 × 10−3 m2/kg-fresh mass. The maximum Tag value was observed for the tree koshiabura (Chengiopanax sciadophylloides) and the minimum value was observed for the perennial spermatophyte giant butterbur (Petasites japonica). Tree species showed higher Tag than spermatophyte and pteridophyte perennials.

CoMeT: Configurable Tagged Memory Extension.

Commodity processor architectures are releasing various instruction set extensions to support security solutions for the efficient mitigation of memory vulnerabilities. Among them, tagged memory extension (TME), such as ARM MTE and SPARC ADI, can prevent unauthorized memory access by utilizing tagged memory. However, our analysis found that TME has performance and security issues in practical use. To alleviate these, in this paper, we propose CoMeT, a new instruction set extension for tagged memory. The key idea behind CoMeT is not only to check whether the tag values in the address tag and memory tag are matched, but also to check the access permissions for each tag value. We implemented the prototype of CoMeT on the RISC-V platform. Our evaluation results confirm that CoMeT can be utilized to efficiently implement well-known security solutions, i.e., shadow stack and in-process isolation, without compromising security.

A novel design layout of three disjoint paths multistage interconnection network & its reliability analysis

Purpose The purpose of this paper is to design a efficient layout of Multistage interconnection network which has cost effective solution with high reliability and fault-tolerence capability. For parallel computation, various multistage interconnection networks (MINs) have been discussed hitherto in the literature, however, these networks always required further improvement in reliability and fault-tolerance capability. The fault-tolerance capability of the network can be achieved by increasing the number of disjoint paths as a result the reliability of the interconnection networks is also improved. Design/methodology/approach This proposed design is a modification of gamma interconnection network (GIN) and three disjoint path gamma interconnection network (3-DGIN). It has a total seven number of paths for all tag values which is uniform out of these seven paths, three paths are disjoint paths which increase the fault tolerance capability by two faults. Due to the presence of more paths than the GIN and 3-DGIN, this proposed design is more reliable. Findings In this study, a new design layout of a MIN has been proposed which provides three disjoint paths and uniformity in terms of an equal number of paths for all source-destination (S-D) pairs. The new layout contains fewer nodes as compared to GIN and 3-DGIN. This design provides a symmetrical structure, low cost, better terminal reliability and provides an equal number of paths for all tag values (|S-D|) when compared with existing MINs of this class. Originality/value A new design layout of MINs has been purposed and its two terminal reliability is calculated with the help of the reliability block diagram technique.