Verification Of Specifications Research Articles

Analysis of information flow security using software implementing business logic based on stored database program blocks

Objectives. Verification of software security is typically performed using dynamic and static analysis tools. The corresponding types of analysis do not usually consider the business logic of the software and do not rely on data access control policies. A modern approach to resolving this problem is to implement language-based information flow control. Despite a large amount of research, mechanisms for information flow control in software are not widely used in practice. This is because they are complex and impose increased demands on developers. The aim of the work is to transfer information flow control from the language level to the level of formal verification. This will enable the functions of controlling data integrity and confidentiality in software to be isolated into a separate task, which can be resolved by information security analysts.Methods. The research is based on general formal security methods for computer systems and formal verification methods. The algorithm developed by the author for checking security specifications and resolving security violations uses temporal logic of actions.Results. The technology is presented as a step-by-step approach to resolving specific tasks, including the following: designing a database (DB) for storing and processing sensitive information; analyzing dependencies and identifying relevant sets of program blocks in the DB; generating TLA+ specifications for the identified program blocks; labeling specifications according to global security policy rules and additional constraints; applying the specification verification algorithm, and resolving security violations while providing recommendations for software developers. The procedure also involves analyzing labeled data, in order to control the spread of verified program block output values in external software modules.Conclusions. The technology presented herein does not require developers to include redundant annotations describing security policy rules. The function of analyzing information flows with reference to predefined access restrictions is moved to a separate stage of the software development life cycle.

The influence of tube diameter parameters on the flow resistance and heat transfer characteristics of supercritical CO2 in horizontal tubes

The diameter parameters of tubes are crucial for the flow and heat transfer characteristics of supercritical fluids. however, the diameter effect has not been fully understood. The existing literatures only investigate the effect of different tube diameters on the flow and heat transfer characteristics within a narrow parameter range, lacking specific theoretical analyses and verification in a wide range of parameters. Therefore, experimental research was conducted to investigate the influence of tube diameter parameters on the flow resistance and heat transfer of supercritical carbon dioxide(sCO2) in horizontal tubes and an explanation of the tube diameter effect mechanism is provided based on pseudo-boiling theory. Stainless steel smooth circular tubes with diameters of 8 mm, 10 mm, and 12 mm were used as the test section, and various experiments were carried out under the range of mass flux (G): 509.23–1267.34 kg/m2s, heat flux (qw): 97.91–410.43 kW/m2, and operating pressure (P): 5.54–20.32 MPa. From the pseudo-boiling theory analysis, the influence of tube diameter parameters has a greater influence on the heat transfer in the two-phase-like (TPL) regime and is almost negligible when the P exceeded 1.5Pc, indicating the interaction between liquid-like (LL) and vapor-like (VL) phases is found to be the dominant reason for the tube diameter effect on heat transfer and the correlations for predicting the maximum wall temperature difference between the top and bottom generatrix (ΔTmax) are established. The present work can significantly enhance the understanding on sCO2 flow boiling mechanism and provide a new research direction for supercritical fluid.

A Quantum Algorithm for System Specifications Verification

A Quantum Algorithm for System Specifications Verification

Microsatellite markers for genotyping of Kodamaea ohmeri: Demonstrating outbreaks based on a multicenter surveillance study in China

Kodamaea ohmeri, an emerging human pathogen, caused both sporadic and nosocomial infections among immunocompromised people with high mortality. However, there is limited research on the molecular epidemiology of K. ohmeri. A total of fifty microsatellite loci were designed based on K. ohmeri type strain NRRL Y-1932 and three loci were finally selected for microsatellite analysis. Non-duplicated K. ohmeri isolates and strains of other species were collected across China as a part of CHIF-NET program for sensitivity and specificity verification. Antifungal susceptibility was determined using Sensititre YeastOne TM YO10. The three loci (P10, P11 and P26), with a cumulative discriminatory power of 0.98, exhibited a prospective specificity and reproducibility in the PCR of 92 K. ohmeri strains from different hospitals. A total of 54 microsatellite types (MT) were identified and most of them distributed sporadically. However, six strains of MT12 clustered in HZ hospital and were isolated in the same department within two months, indicating a potential outbreak. Of seven isolates exhibited MIC values of >8 mg/L for fluconazole, three isolates from LR hospital shared the same genotype of MT44. Herein, we established a set of microsatellite loci for K. ohmeri, as a rapid and specific tool for genotyping K. ohmeri, and identified several potential clusters. This study will help us better understand the molecular epidemiology of the emerging pathogen K. ohmeri.

Heterogeneous Integration of Chiplets, Lego-like IP for More than Moore

The semiconductor industry is facing an inflection point as higher cost, lower yield, and reticle size limitations drive the need for viable alternatives to traditional monolithic solutions, which are hitting or coming close to the limits of manufacturing and physics. This is driving an emerging trend to disaggregate what typically would be implemented as an SoC into solid, fabricated IP blocks, otherwise known as chiplets. These chiplets typically provide a specific function implemented in an optimal chip process node. Several chiplets and an optional, custom SOC device mounted and interconnected in a single packing using high speed/bandwidth interfaces that will then deliver monolithic or greater performance at a reduced cost, higher yield, and with only a slightly larger area as a heterogeneous integrated advanced package. As fabless semiconductor companies begin to bring these disaggregated chiplets to market, their successful adoption requires the fabless semiconductor industry to standardize on a set of interface protocols that will offer Lego-like plug and play compatibility between different suppliers chiplets creating a truly open ecosystem and supply chain. When it comes to the physical heterogeneous integration of these chiplets it is typically achieved using a high-performance silicon-like interposer substrate. Such substrates typically require silicon-like design rules and design techniques along with their own specific analysis and verification requirements. The supply chain for these substrates does not change significantly, it is still typically the leading semiconductor foundries and OSATs however the level of interaction, requirements, and signoff approvals does change bringing often new demands and challenges. Is this a revolution or an evolution, it depends on your starting point? Does it need an entirely new set of workflows and design tools? Can we evolve in some stepwise linear process from where we are today with monolithic or traditional system-in-package type designs into this next-generation design environment? This paper will explore these new challenges and outline 5 key workflows that address and manage them. These 5 workflows span interlinked domain areas starting with architecture definition before progressing to design that incorporates planning, prototyping, and technology co-optimization of the chosen architecture as well as the detailed physical implementation of substrates before moving to multi-physics analysis, device-level test, and then manufacturing. This paper will then recommend workflow adoption focus areas that we have seen provide immediate heterogeneous integration capability benefits while providing a managed methodology adoption and migration process that minimizes disruption, risk, and of course cost that can bring heterogeneous integration based chiplet design within reach of the mainstream instead of only being accessible to the mega iDMs and fabless semi’s.

Challenges in Developing a Method to Support the Adoption of a Model‐Based Systems Engineering Methodology

ABSTRACTTo improve design performance and achieve sustainability, organisations are looking to change their systems engineering practices. A model‐based systems engineering (MBSE) methodology provides a framework for integrating, associating, orchestrating, and connecting executable and interactive models. It improves early verification and validation of system specifications and architectures, as well as communication and collaboration between project stakeholders. In this sense, MBSE has a truly systemic aspect. The variables to be considered when designing a support strategy are numerous and multidimensional. As a result, this situation can lead to contradictions in the choice of actions to be implemented, or to paradoxes that are likely to slow down the progress of the deployment project with the engineers. Currently, there is no method to support teams in charge of a methodological transformation (for example, in MBSE) to facilitate the adoption of this methodology. This article identifies the main challenges involved in developing such a methodology.

Expression of G protein-coupled receptor GPR19 in normal and neoplastic human tissues

Little is known about the expression of the orphan G protein-coupled receptor GPR19 at the protein level. Therefore, we developed a rabbit antibody, targeting human GPR19. After verification of the antibody specificity using GPR19-expressing cell lines and a GPR19-specific siRNA, the antibody was used for immunohistochemical staining of a variety of formalin-fixed, paraffin-embedded normal and neoplastic human tissue samples. In normal tissues, GPR19 expression was detected in a distinct cell population within the cortex, in single cells of the pancreatic islets, in intestinal ganglia, gastric chief cells, and in endocrine cells of the bronchial tract, the gastrointestinal tract, and the prostate. Among the 30 different tumour entities investigated, strong GPR19 expression was found in adenocarcinomas, typical and atypical carcinoids of the lung, and small cell lung cancer. To a lesser extent, the receptor was also present in large cell neuroendocrine carcinomas of the lung, medullary thyroid carcinomas, parathyroid adenomas, pheochromocytomas, and a subpopulation of pancreatic neuroendocrine neoplasms. In lung tumours, a negative correlation with the expression of the proliferation marker Ki-67 and a positive interrelationship with patient survival was observed. Overall, our results indicate that in adenocarcinomas and neuroendocrine tumours of the lung GPR19 may serve as a suitable diagnostic or therapeutic target.

Effect of foliar nutrition on growth and yield of cotton (Gossypium herbaceum) MCU 5

From the experimental results, it is inferred that cotton crop responds well to the foliar nutrition with zinc and magnesium. Application of these nutrients through foliar spray might be the feasible option to control the yield barrier under rainfed condition. Further the study found that foliar spraying of MgSO4 1.0% along with 0.5% of ZnSO4 three times respectively at squaring, flowering and boll formation stages markedly improved the plant growth and seed cotton yield. Thus, these treatments may be recommended for enhancing the rainfed cotton yield but location specificity verification is required before recommendation.

Prediction of Radiomics-Based Machine Learning for Specific Dosimetric Verification of Pelvic Intensity Modulated Radiotherapy.

To establish the different machine learning classification predict models of gamma pass rates for specific dosimetric verification of pelvic intensity modulated radiotherapy plan which based on the radiomic features and to explore the best prediction model. Retrospective analysis of the 3D dosimetric verification results based on measurements with gamma pass rate criteria of 3%/2 mm and 10% dose threshold of 196 pelvic intensity-modulated radiotherapy plans was carried. Prediction models were established by extracting radiomic features data. Four machine learning algorithms, random forest, support vector machine, adaptive boosting and gradient boosting decision trees, were used to calculate the AUC value, sensitivity and specificity respectively. The classification performance of the four prediction models were evaluated. The sensitivity and specificity of the random forest, support vector machine, adaptive boosting, and gradient boosting decision trees models were 0.93,0.85,0.93,0.96, and 0.38,0.69,0.46, and 0.46, respectively. The AUC values for the random forest model and the adaptive boosting model were 0.81 and 0.82, respectively, and the AUC values for the support vector machine and gradient boosting decision tree models were 0.87. Machine learning methods based on radiomics can be used to establish a prediction model of gamma pass rate for specific dosimetric verification of pelvic intensity modulated radiotherapy. The classification performance of support vector machine model and gradient boosting decision trees model is better than that of random forest model and adaptive boosting model. The prediction model for a specific site is helpful to improve the performance of the model.

A Pre-Training Framework Based on Multi-Order Acoustic Simulation for Replay Voice Spoofing Detection.

Voice spoofing attempts to break into a specific automatic speaker verification (ASV) system by forging the user's voice and can be used through methods such as text-to-speech (TTS), voice conversion (VC), and replay attacks. Recently, deep learning-based voice spoofing countermeasures have been developed. However, the problem with replay is that it is difficult to construct a large number of datasets because it requires a physical recording process. To overcome these problems, this study proposes a pre-training framework based on multi-order acoustic simulation for replay voice spoofing detection. Multi-order acoustic simulation utilizes existing clean signal and room impulse response (RIR) datasets to generate audios, which simulate the various acoustic configurations of the original and replayed audios. The acoustic configuration refers to factors such as the microphone type, reverberation, time delay, and noise that may occur between a speaker and microphone during the recording process. We assume that a deep learning model trained on an audio that simulates the various acoustic configurations of the original and replayed audios can classify the acoustic configurations of the original and replay audios well. To validate this, we performed pre-training to classify the audio generated by the multi-order acoustic simulation into three classes: clean signal, audio simulating the acoustic configuration of the original audio, and audio simulating the acoustic configuration of the replay audio. We also set the weights of the pre-training model to the initial weights of the replay voice spoofing detection model using the existing replay voice spoofing dataset and then performed fine-tuning. To validate the effectiveness of the proposed method, we evaluated the performance of the conventional method without pre-training and proposed method using an objective metric, i.e., the accuracy and F1-score. As a result, the conventional method achieved an accuracy of 92.94%, F1-score of 86.92% and the proposed method achieved an accuracy of 98.16%, F1-score of 95.08%.

Evaluation of a planar diode matrix for SRS patient-specific QA in comparison with GAFchromic films.

We validate the routine use of a two-dimensional (2D) diode matrix for patient specific pre-treatment verification for Cyberknife (CK) stereotactic radiosurgery and to compare it with film dosimetry. A total of 46 patients were selected according to the most frequent diseases treated at our institution with the CK system, that is, brain metastases, meningiomas, spine metastases, and prostate tumors. All cases were evaluated with GAFChromic EBT-3 films and SRS MapCHECK for Fixed cone, IRIS, and MLC collimators of the CK. The highest mean passing rate was observed for the SRS MapCHECK system compared to films. In order to assess if the two techniques provide statistically different results, a Wilcoxon Signed-Rank non-parametric test was performed (p<0.05) and we found gamma values significantly lower for EBT-3 films with respect to the SRS MapCHECK. We noticed a moderately significant association between the two techniques using Spearman's rank correlation coefficient (rs>0.4). We also performed the Bland-Altman statistical method: less than 5% of the differences resulted outside the range (mean±1.96×SD), so the two methods can be considered interchangeable within the combined inaccuracy. The use of SRS MapCHECK for CK patient specific quality assurance (QA) is feasible for a variety of clinical districts and could be reliably used as a replacement for radiochromic films.

Model checking embedded adaptive cruise controllers

While checking functional correctness for automated driving is often achieved through vast amounts of automated and manual field testing, automating specification verification is essential for developing and releasing fully self-driving vehicles. This paper presents an automatic bounded model checking approach for functional specifications over longitudinal vehicle controller implementations. The proposed method checks the actual embedded program, rather than an extracted abstract model. The specification is converted into a monitor that is interleaved with the execution of the program over a finite time horizon in closed-loop simulation. A decomposition is proposed to tackle the verification complexity. This allows verifying the program for whole parameter sets using a software model checker as opposed to testing only individual samples. The approach is capable of identifying functional flaws in several exemplary longitudinal controllers with variable complexity.

SMACS: A framework for formal verification of complex adaptive systems

Abstract Self-adaptive systems (SASs) have the capability to evaluate and change their behavior according to changes occurring in the environment. Research in this field is being held since mid-60, and over the last decade, the importance of self-adaptivity is being increased. In the proposed research, colored petri nets (CPN) formal language is being used to model self-adaptive multiagent system. CPN is increasingly used to model self-adaptive complex concurrent systems due to its flexible formal specification and formal verification behavior. CPN being visually more expressive than simple, Petri Nets enable diverse modeling approaches and provides a richer framework for such a complex formalism. The main goal of this research is to apply self-adaptive multi-agent concurrent system (SMACS) for complex architectures. In our previous research, the SMACS framework is proposed and verified through traffic monitoring system. All agents of SMACS are also known as intelligent agents due to their self-adaptation behavior. Due to decentralized approach in this framework, each agent will intelligently adapt its behavior in the environment and send updates to other agents. In this research, we are choosing smart computer lab (SCL) as a case study. For internal structure of each agent modal, μ \mu -calculus will be used, and then a model checker TAPAs: a tool for the analysis of process algebras will be applied to verify these properties. CPN-based state space analysis will also be done to verify the behavioral properties of the model. The general objective of the proposed system is to maximize the utility generated over some predetermined time horizon.

Empirical study on security verification and assessment of neural network accelerator

With the significant success of machine learning, there are plenty of innovative neural network designs nowadays. The related applications become more and more pervasive in our daily life, even in life-critical domains such as autopilot and medical diagnosis, etc. In these domains, whether the AI-based system is “secure” or not is a critical issue. In this work, we first present six Hardware Trojan attacks with demonstrations of their impacts on the hardware design of neural networks. When data leakage occurs, we encode the leakage data to the output and make it more difficult to be detected. Most of our attacks can either achieve more than 98% attack success rate or leak out confidential data without causing any functional violation, with less than 1.5% overhead. We also discuss how to effectively and efficiently detect these Hardware Trojans with formal verification methods and further propose a risk assessment process to constitute a priority guidance to suggest security verification tasks of neuron network hardware. Based on our results, we strongly suggest that security specification and total verification are essential to neuron network designs.

Deploying SDG Knowledge to Foster Young People’s Critical Values: A Study on Social Trends about SDGs in an Educational Online Activity

Educational tasks for the development of competencies on the Sustainable Development Goals (SDGs) pose a challenge to educators due to the multidisciplinary and complex nature of these goals. It is necessary to develop innovative educational resources and tools that holistically account for this complexity and highlight the environmental and social components of these goals on an equal footing. A learning tool based on the serious games methodology, called BotBusters, is used to inoculate this type of knowledge and skills among young Europeans through a specific news verification activity. This game has been designed to collect interaction data (logs) and thus perform an analysis of players’ behavior, which allows us to understand their preferences and knowledge of the SDGs (specifically 3, 12, 13 and 15). The data collected yield interesting conclusions about the educational needs of young people in this field, showing their preferences for topics related to the environmental SDGs. This indicates that there is a need to promote awareness of the SDGs on social issues, especially those that require a more collective type of agreement and intervention.

SAFETY INSPECTION OF PRESSURE VESSELS AT AN ENGINE GRINDER IN AGRESTINA-PE

Pressure vessels are critical components in internal combustion engines as they withstand high pressures of oil, air, steam or other fluids. Failure of a pressure vessel can result in loss of containment, personal injury, equipment damage and, in severe cases, even explosions. Therefore, it is crucial to carry out periodic and rigorous inspections of these vessels in an engine overhaul to ensure their integrity and safety. This article discusses the steps of inspection in pressure vessels in an engine grinding plant, including inspection of pressure vessels containing argon gas stored to perform aluminum welding, as well as verification of design specifications, external visual evaluation, dimensional verification, ray inspection, visual inspection on compressors, which is important to extend its useful life and prevent accidents, inspection is performed according to specific standards and codes, such as ASME and API, and can be performed by internal or external inspectors, depending on the complexity of the equipment

The Chronology of the Second Muslim Civil War between Shared and Competing Historical Memories

The events of the second Muslim civil war have been reported in Muslim sources and Christian chronicles. John bar Penkāyē is by far the most important non-Muslim source because he lived throughout the events that he documented in the Book of Main Points (Ktâbâ d-rêšê mellê) which he wrote in 67/687. Although some of the events reported by John are corroborated by Muslim sources and Christian chronicles as shared historical memories, he is also the main source of competing historical memories. As the sequence of events that John describes in his narrative does not often match with what has been reported in the Muslim sources, this article applies the methodology of Specific Date Verification, primarily derived from Muslim sources, to attempt to shed light on the competing historical memories. It concludes that John’s narrative was not influenced by a later editor and that his work, along with that of other Christian chroniclers, raises important questions about the events of the second civil war.

Environmental Consciousness, Purchase Intention, and Actual Purchase Behavior of Eco-Friendly Products: The Moderating Impact of Situational Context

Recently, environmental issues have become major social concerns, and consumers are becoming increasingly aware of environmental matters; however, they remain hesitant to purchase eco-friendly products. This study examined consumers' environmental consciousness as a factor influencing the purchase of eco-friendly products, and investigated situational factors that induce hesitancy in purchasing eco-friendly products. We studied the moderating effects of these factors with regard to ease of purchase and eco label credibility. Our research model is validated using data from 220 consumers with experience in purchasing eco-friendly products in Korea. For the data analysis, we used SPSS 22.0 and AMOS 22.0 to perform confirmatory factor analysis and SEM. The specific verification results are as follows. First, environmental interest did not significantly impact the purchase intention of eco-friendly products. Second, consumers' environmental knowledge and consumer effectiveness perception both had a significant impact on the purchase intention of eco-friendly products. Third, the intention to purchase eco-friendly products significantly impacted the purchase behavior of eco-friendly products. In addition, the results of this study show that ease of purchase and eco label credibility have moderating effects on the relationship between purchase intention and purchase behavior. This study results contribute to the eco-friendly consumption literature by explaining the intention-behavior gap. This study also show that eco-friendly consumption can be stimulated through raising eco label credibility and ease of purchase. The findings have theoretical implications for understanding the factors that affect consumers' intentions of and behavior toward eco product purchases, and practical implications for how to stimulate environmental consumer behavior.

The concept of detection of dynamic lung hyperinflation using cardiopulmonary exercise testing.

Dynamic lung hyperinflation (DLH) caused by air trapping, which increases residual air volume, is a common cause of shortness of breath on exertion in chronic obstructive pulmonary disease (COPD). DLH is commonly evaluated by measuring the decrease in maximal inspiratory volume during exercise, or using the hyperventilation method. However, only few facilities perform these methods, and testing opportunities are limited. Therefore, we investigated the possibility of visually and qualitatively detecting DLH using data from a cardiopulmonary exercise test (CPET). Four men who underwent symptom-limiting CPET were included in this study, including a male patient in his 60s with confirmed COPD, a 50s male long-term smoker, and 2 healthy men in their 20s and 70s, respectively. We calculated the difference between the inspiratory tidal volume (TV I) and expiratory tidal volume (TV E) per breath (TV E-I) from the breath-by-breath data of each CPET and plotted it against the time axis. No decrease in TV E-I was observed in either of the healthy men. However, in the patient with COPD and long-term smoker, TV E-I began to decrease immediately after the initiation of exercise. These results indicate that DLH can be visually detected using CPET data. However, this study was a validation of a limited number of cases, and a comparison with existing evaluation methods and verification of disease specificity are required.

Illegal Domain Name Generation Algorithm Based on Character Similarity of Domain Name Structure

Detecting and controlling illegal websites (gambling and pornography sites) through illegal domain names has been an unsolved problem. Therefore, how to mine and discover potential illegal domain names in advance has become a current research hotspot. This paper studies a method of generating illegal domain names based on the character similarity of domain name structure. Firstly, the K-means algorithm classified illegal domain names with similar structures. Then, put the classified clusters into the adversarial generative network for training. Finally, through a specific result verification method, the experiment shows that the average concentration of the generation algorithm is 23.82%, the effective concentration is 63.54%, and the expansion rate is 7.5. By comparing the results with the enumeration algorithm, the generation algorithm has greatly improved in terms of generation efficiency and accuracy.