Block Algorithm Research Articles

AIR SUPPLY REGULATOR FOR THE WORKING SPACE HEAT INSTALLATION BASED ON FUZZY LOGIC

The combustion process in the working space of a heat installation is simulated. The static characteristic of the dependence of fuel consumption on air consumption in the conditions of stabilization of heat generated as a result of the combustion process is shown, therefore, the possibility of optimizing this process is proved. A block diagram, mathematical model and algorithm for calculating energy-saving fuzzy control of the combustion process in the working space of a thermal installation are developed. Combustion Membership functions of fuzzy sets for input linguistic variables are compiled. The rule bases are formulated taking into account the static characteristics of the control object. Examples of technological and linguistic justification of fuzzy controller rules are given. The dynamics of changing the controlled parameter is determined by solving two differential equations. The search for levels of "cut-offs" for the prerequisites of each of the rules using the "minimum" operation in accordance with the compiled database of rules is performed. The defuzzification procedure was performed (bringing it to clarity). The advantages of this system over traditional stabilizing control systems under the action of a set of random factors and a significantly nonlinear relationship between input and output values are shown. Optimal values of scaling factors for the developed automatic control system are determined. Let's consider an example of the formation of a control effect when implementing fuzzy energy-saving control of the combustion process in the working space of the boiler unit No. 3 of the GKP-1A UGPU of Gazprom dobycha Urengoy LLC. The calculations of the amount of inleakage of atmospheric air, excess air flow, the sectional area of the pipe supplying air, the total air flow in the working space of the thermal installation, the volume of natural gas participating in the combustion process, heat resulting from the combustion, the amount of air that did not participate in the combustion process, the amount of heat required to increase the temperature of excess air until the average temperature of the flue gas remaining heat of the combustion reaction, changes in the oxygen concentration in the exhaust flue gases depending on the air flow to the burner. The functional dependence of the flue gas temperature on the natural gas consumption is constructed by approximating the initial data of the regime map of the steam boiler. The dynamic properties of an inertia-delayed controlled process are taken into account when using the Euler method. The combustion control mode influence on the specific fuel consumption is estimated. The effects of using a system with fuzzy control in terms of saving natural gas and electricity over the entire range of performance of a thermal installation are estimated.

A novel image encryption scheme of dynamic S-boxes and random blocks based on spatiotemporal chaotic system

In this paper, a novel image encryption scheme based on spatiotemporal chaotic system is proposed. In the scheme, we adopt the dynamic S-boxes and random blocks algorithms. Firstly, the image is brought into SHA-512 to generate system key. And the key is introduced into Logistic-Dynamic Coupled Logistic Map Lattices (LDCML) spatiotemporal chaos system to initialize the values of dynamic S-boxes and set the parameter values in image encryption. Then, the image is grouped horizontally and vertically in order. Each group consists of non-adjacent rows or non-adjacent columns and is encrypted by the different S-boxes. Lastly, every scrambled pixel is processed by random blocks algorithm. With this encryption scheme, the image is scrambled and diffused simultaneously, which can be scrambled sufficiency and diffused uniformity. Simulation results show that the scheme provides a satisfying level of security and has the advantages of large key space, anti-differential attack, high efficiency and good statistical performance in comparison with other image encryption schemes.

Unsupervised Entity Resolution With Blocking and Graph Algorithms

Entity resolution identifies all records in a database that refer to the same entity. In this paper, we propose an unsupervised framework for entity resolution using blocking and graph algorithms. The records are partitioned into blocks with no redundancy for efficiency improvement. For intra-block data processing, we propose a graph-theoretic fusion framework with two components, namely ITER and CliqueRank. Specifically, ITER constructs a weighted bipartite graph between terms and record-record pairs and iteratively propagates the node salience until convergence. Subsequently, CliqueRank constructs a record graph to estimate the likelihood of two records resident in the same clique. The derived likelihood from CliqueRank is fed back to ITER to rectify the edge weight until a joint optimum can be reached. Experimental evaluation was conducted with 4 real datasets. Results show that our unsupervised framework is comparable or even superior to state-of-the-art deep learning approaches.

Параллельное решение систем линейных уравнений на гибридной архитектуре CPU+GPU

The article discusses the parallel implementation of solving systems of linear algebraic equations on computational nodes containing a central processing unit (CPU) and graphic accelerators (GPU). The performance of parallel algorithms for the classical conjugate gradient method schemes when using the CPU and GPU together is significantly limited by the synchronization points. The article investigates the pipeline version of the conjugate gradient method with one synchronization point, the possibility of asynchronous calculations, load balancing between the CPU and GPU when solving the large linear systems. Numerical experiments were carried out on test matrices and computational nodes of different performance of a heterogeneous cluster, which allowed us to estimate the contribution of communication costs. The algorithms are implemented with the joint use of technologies: MPI, OpenMP and CUDA. The proposed algorithms, in addition to reducing the execution time, allow solving large linear systems, for which there are not enough memory resources of one GPU or a computing node. At the same time, block algorithm with the pipelining decreases the total execution time by reducing synchronization points and aggregating some messages in one.

Analysis of the Ebola Outbreak in 2014 and 2018 in West Africa and Congo by Using Artificial Adaptive Systems

ABSTRACTIn this manuscript the Ebola outbreaks in 2014 and 2018 have been studied. On March 23, 2014, the World Health Organization announced the beginning of the Ebola outbreak in West Africa. The initial location was in a forested area in the south eastern portion of Guinea. We used three different methods to determine the origin of the outbreak. The first was a suite of artificial adaptive systems called Topological Weighted Centroid which located the outbreak origin at Longitude: −10.5337, Latitude: 8.1517. This area is 64 km from Guekedou, Guinea. We also used a Dynamic Naive Bayesian/Dynamic Networks Block Algorithm. The Bayesian algorithm shows the main source of the Ebola outbreak at Kissidougou. Both of these methods revealed the outbreak started in the forested area southeast of Guinea. The distance between Guekedou and Kissidougou is about 69 km. Furthermore, we used an artificial neural network (ANN) called Selfie to predict the outbreak diffusion. The Ebola outbreak in May 2018 in Democratic Republic of Congo was not as widespread as the outbreak in 2014. The outbreak was effecting the health zones of Bikoro and Iboko, and Wangata in Congo. We have used an ANN algorithm and predicted the origin of the outbreak at (Longitude: 18.3046, Latitude: −0.6865) in the Equator about 20 km at North-West of Bikoro.

Automation of Concrete Heat Treatment in Thermoactive Formwork in Monolithic Housing Construction

The block diagram and algorithm for concrete treating in thermoactive formwork is presented. Article presents parameters of the concrete mix, to enter in a command block before automated heating of the concrete mix in thermoactive formwork in accordance with the schedule of changes in concrete temperature in the process of obtaining desired strength. Article formulates mathematical model of the control object for thermal treatment of concrete with consideration of the specifics and general patterns, processes and technological requirements. Article determined control actions, transfer functions of the object and phase graph of the control system.

Continuation of the X-ray monitoring of Sgr A*: the increase in bright flaring rate confirmed

Context.The supermassive black hole Sagittarius A* (Sgr A*) is located at the dynamical center of the Milky Way. In a recent study of the X-ray flaring activity from Sgr A* usingChandra,XMM-Newton, andSwiftobservations from 1999 to 2015, it has been argued that the bright flaring rate has increased from 2014 August 31 while the faint flaring rate decreased from around 2013 August.Aims.We tested the persistence of these changes in the flaring rates with new X-ray observations of Sgr A* performed from 2016 to 2018 (total exposure of 1.4 Ms).Methods.We reprocessed theChandra,XMM-Newton,andSwiftobservations from 2016 to 2018. We detected 9 flares in theChandradata and 5 flares in theSwiftdata that we added to the set of 107 previously detected flares. We computed the intrinsic distribution of flare fluxes and durations corrected for the sensitivity bias using a new method that allowed us to take the error on the flare fluxes and durations into account. From this intrinsic distribution, we determined the average flare detection efficiency for eachChandra,XMM-Newton,andSwiftobservation. After correcting each observational exposure for this efficiency, we applied the Bayesian blocks algorithm on the concatenated flare arrival times. As in the above-mentioned study, we also searched for a flux and fluence threshold that might lead to a change in flaring rate. We improved the previous method by computing the average flare detection efficiencies for each flux and fluence range.Results.The Bayesian block algorithm did not detect any significant change in flaring rate of the 121 flares. However, we detected an increase by a factor of about three in the flaring rate of the most luminous and most energetic flares that have occurred since 2014 August 30.Conclusions.The X-ray activity of Sgr A* has increased for more than four years. Additional studies about the overall near-infrared and radio behavior of Sgr A* are required to draw strong results on the multiwavelength activity of the black hole.

Effective Video Saliency Mapping for Object Detection using Deep Learning Neural Networks

In this paper, we propose a new novel DNN-based video saliency prediction method.The main aim of this project is to separating foreground and background images and also finding the motion of the objects.The methodogy used in this project is to seperating the foreground images using background modelling techniques(Pixel searching algorithm).The another technique is Homography based search algorithm for block based motion estimation is used to finding the movement of the objects.Saliency object detection is also used to highlighting the particular region in the images.In our base paper[1],context subtraction algorithm is introduced.But in this paper,Convolutional neural networks is used to classifying the foreground objects from background images.We propose an deep convolutional neural network (CNN) Classifier is used to predict intra-frame salience by exploring object and object movement details .The CNN classifier is also used to separating the new objects from background. We also find from our database that a temporary correlation of human attention exists, with a smooth transition of saliency across video frames.Therefore, in our DNN-based approach we create a two-layer convolutionary long-term memory (2C-LSTM) network, using the extracted CNN features as the data.The fuzzy clustering is used to store the information as the processed images in this project.This project can be implemented in real time applications such as defence,forest and miltrary area.Saliency Mapping is also used to reduce the Zipper effect,it mainly occurs in edges.It gives High resolution too. Finally, the proposed system is developed using matlab simulation.The PSNR value is attained above 95%.

PoBT: A Lightweight Consensus Algorithm for Scalable IoT Business Blockchain

Efficient and smart business processes are heavily dependent on the Internet of Things (IoT) networks, where end-to-end optimization is critical to the success of the whole ecosystem. These systems, including industrial, healthcare, and others, are large scale complex networks of heterogeneous devices. This introduces many security and access control challenges. Blockchain has emerged as an effective solution for addressing several such challenges. However, the basic algorithms used in the business blockchain are not feasible for large scale IoT systems. To make them scalable for IoT, the complex consensus-based security has to be downgraded. In this article, we propose a novel lightweight proof of block and trade (PoBT) consensus algorithm for IoT blockchain and its integration framework. This solution allows the validation of trades as well as blocks with reduced computation time. Also, we present a ledger distribution mechanism to decrease the memory requirements of IoT nodes. The analysis and evaluation of security aspects, computation time, memory, and bandwidth requirements show significant improvement in the performance of the overall system.

Gefapixant, a P2X3 receptor antagonist, for the treatment of refractory or unexplained chronic cough: a randomised, double-blind, controlled, parallel-group, phase 2b trial

Gefapixant is a P2X3 receptor antagonist that has shown promise for the treatment of refractory and unexplained chronic cough. The aim of this study was to evaluate the efficacy of gefapixant compared with placebo after 12 weeks of treatment for refractory chronic cough or unexplained chronic cough. We did a 12-week, phase 2b, randomised, double-blind, placebo-controlled study in patients with refractory chronic cough or unexplained chronic cough aged 18-80 years who were recruited from 44 primarily outpatient pulmonologist or allergist sites in the UK and the USA. Eligible patients had refractory or unexplained chronic cough lasting 1 year or longer, no radiographic chest abnormality, and 40 mm or more on a 100-mm cough severity visual analogue scale at enrolment. Patients were randomly assigned to receive placebo or one of three doses (7·5 mg, 20 mg, or 50 mg) of oral gefapixant twice daily, every day, for 84 days; visits to investigative sites were on days 1, 28, 42, 56, 70, 84, and 85. The randomisation schedule was computer generated using a permuted block algorithm by Advance Research Associates (Santa Clara, CA, USA). Patients and all personnel involved in the conduct and interpretation of the study were masked to treatment assignment. The primary endpoint was placebo-adjusted change from baseline in awake cough frequency after 12 weeks, assessed in the full analysis set, which is a subset of the intention-to-treat population. Adverse events were monitored and safety was evaluated in all patients receiving one or more doses of study drug. This trial is registered with ClinicalTrials.gov, NCT02612610. Between Dec 21, 2015, and July 26, 2016, 253 patients were randomly assigned to placebo (n=63), gefapixant 7·5 mg (n=64), gefapixant 20 mg (n=63), or gefapixant 50 mg (n=63) twice daily. The mean age of patients was 60·2 (SD 9·9) years and 193 (76%) were women. At 12 weeks, patients' geometric mean awake cough frequency was 18·2 coughs per h (geometric SD 3·1) with placebo, and 14·5 coughs per h (3·7) with 7·5 mg, 12·0 coughs per h (4·2) with 20 mg, and 11·3 coughs per h (2·8) with 50 mg gefapixant. Estimated percentage change relative to placebo was -22·0% (-41·8 to 4·6; p=0·097) with 7·5 mg, -22·2% (-42·0 to 4·3; p=0·093) with 20 mg, and -37·0% (95% CI -53·3 to -14·9; p=0·0027) with 50 mg gefapixant. Dysgeusia was the most common adverse event, occurring in three (5%) patients given placebo, six (10%) given 7·5 mg gefapixant, 21 (33%) given 20 mg gefapixant, and 30 (48%) given 50 mg gefapixant. Targeting purinergic receptor P2X3 with gefapixant at a dose of 50 mg twice daily significantly reduced cough frequency in patients with refractory chronic cough or unexplained chronic cough after 12 weeks of treatment compared with placebo. Further development of gefapixant is warranted for the treatment of chronic cough. Afferent Pharmaceuticals (acquired by Merck & Co., Inc., Kenilworth, NJ, USA).

Energy Efficient Power Domain Non-Orthogonal Multiple Access Based Cellular Device-to-Device Communication for 5G Networks

This paper examines the resource block and power allocation in the power domain non-orthogonal multiple access (PD-NOMA) based cellular device-to-device (D2D) systems. To improve the energy efficiency of the D2D systems and to manage the mutual interference level as well as the quality of service (QoS) requirement of cellular users, different power level is applied to the D2D users sharing the same resource blocks (RBs) to the legacy users. It is essential to design an efficient resource block and power allocation method for PD-NOMA based cellular D2D systems which guarantee the successive interference cancellation (SIC) order in the power allocation solution. In this paper, we propose an iterative algorithm of resource block and power allocation for cellular D2D system which incorporates the SIC aware geometric water filling (GWF) method in the power allocation solution. It is shown that the proposed SIC aware geometric water filling achieves higher energy efficiency compared to iterative water-filling (IWF) power allocation and the GWF based orthogonal multiple access (OMA) method.

Bayesian structured antedependence model proposals for longitudinal data

An important problem in Statistics is the study of longitudinal data taking into account the effect of other explanatory variables, such as treatments and time and, simultaneously, the incorporation into the model of the time dependence between observations on the same individual. The latter is specially relevant in the case of nonstationary correlations, and nonconstant variances for the different time point at which measurements are taken. Antedependence models constitute a well known commonly used set of models that can accommodate this behaviour. These covariance models can include too many parameters and estimation can be a complicated optimization problem requiring the use of complex algorithms and programming. In this paper, a new Bayesian approach to analyse longitudinal data within the context of antedependence models is proposed. This innovative approach takes into account the possibility of having nonstationary correlations and variances, and proposes a robust and computationally efficient estimation method for this type of data. We consider the joint modelling of the mean and covariance structures for the general antedependence model, estimating their parameters in a longitudinal data context. Our Bayesian approach is based on a generalization of the Gibbs sampling and Metropolis-Hastings by blocks algorithm, properly adapted to the antedependence models longitudinal data settings. Finally, we illustrate the proposed methodology by analysing several examples where antedependence models have been shown to be useful: the small mice, the speech recognition and the race data sets.

Modelling and implementation of an intelligent stowage simulator for container ships

To solve the problems that conventional loading master for container ship merely provides the stability, strength, floating condition, etc. a comprehensive intelligent simulator was worked out, which can also obtain the amount of restowage containers, verify segregation scheme for dangerous containers, etc. BLOCK algorithm is proposed for the first time for restowage problems with respect to the containers on deck jam that in hold and all in hold or on deck. In the case of all in hold or on deck, independent stowage and mix stowage are studied in some detail. A fast and effective algorithm is also put forward to perform the segregation verifying. At last, the above proposed algorithms are verified by the loading condition from the loading manual.

Modelling and implementation of an intelligent stowage simulator for container ships

To solve the problems that conventional loading master for container ship merely provides the stability, strength, floating condition, etc. a comprehensive intelligent simulator was worked out, which can also obtain the amount of restowage containers, verify segregation scheme for dangerous containers, etc. BLOCK algorithm is proposed for the first time for restowage problems with respect to the containers on deck jam that in hold and all in hold or on deck. In the case of all in hold or on deck, independent stowage and mix stowage are studied in some detail. A fast and effective algorithm is also put forward to perform the segregation verifying. At last, the above proposed algorithms are verified by the loading condition from the loading manual.

Reverse Intervention for Dealing with Malicious Information in Online Social Networks

Malicious information is often hidden in the massive data flow of online social networks. In “We Media'' era, if the system is closed without intervention, malicious information may spread to the entire network quickly, which would cause severe economic and political losses. This paper adopts a reverse intervention strategy from the perspective of topology control, so that the spread of malicious information could be suppressed at a minimum cost. Noting that as the information spreads, social networks often present a community structure and multiple malicious information promoters may appear. Therefore, this paper adopts a divide and conquer strategy and proposes an intervention algorithm based on subgraph partitioning, in which we search for some influential nodes to block or release clarification. The main algorithm consists of two main phases. Firstly, a subgraph partitioning method based on community structure is given to quickly extract the community structure of the information dissemination network. Secondly, a node blocking and clarification publishing algorithm based on the Jordan Center is proposed in the obtained subgraphs. Experiments show that the proposed algorithm can effectively suppress the spread of malicious information with a low time complexity compared with the benchmark algorithms.

A novel algorithm for TOP-K optimal path on complex multiple attribute graph

In the rapidly-changing information world, the various users and personalised requirements lead to an urgent need for complex multiple attribute decision-making. In addition, the TOP-K path of single attribute decision cannot meet the actual needs. The TOP-K mainly has non-repeatable vertex, repeatable vertex, index and other algorithms. But these techniques are mainly based on the single attribute. There are few documents introducing the complex multiple attribute decision-making problem so for. Therefore, a Tdp algorithm is presented in this paper. Firstly, it uses the technology of interval number and extreme value to solve the uncertain attribute value. Then, TOPSIS technique solves the complex multiple attribute decision-making problems. By this way, the comprehensive score is achieved. Secondly, the paper proposes blocking and bidirectional shortest path algorithm for TOP-K optimal path. Finally, comparison and analysis between Tdp and the Yen were made. Result confirms that Tdp algorithm improves the TOP-K optimal technology.

A novel algorithm for TOP-K optimal path on complex multiple attribute graph

In the rapidly-changing information world, the various users and personalised requirements lead to an urgent need for complex multiple attribute decision-making. In addition, the TOP-K path of single attribute decision cannot meet the actual needs. The TOP-K mainly has non-repeatable vertex, repeatable vertex, index and other algorithms. But these techniques are mainly based on the single attribute. There are few documents introducing the complex multiple attribute decision-making problem so for. Therefore, a Tdp algorithm is presented in this paper. Firstly, it uses the technology of interval number and extreme value to solve the uncertain attribute value. Then, TOPSIS technique solves the complex multiple attribute decision-making problems. By this way, the comprehensive score is achieved. Secondly, the paper proposes blocking and bidirectional shortest path algorithm for TOP-K optimal path. Finally, comparison and analysis between Tdp and the Yen were made. Result confirms that Tdp algorithm improves the TOP-K optimal technology.

Low-fat dietary pattern and global cognitive function: Exploratory analyses of the Women's Health Initiative (WHI) randomized Dietary Modification trial

BackgroundMeta-analyses of observational studies associate adherence to several dietary patterns with cognitive health. However, limited evidence from full scale, randomized controlled trials precludes causal inference regarding dietary effects on cognitive function. MethodsThe Women's Health Initiative (WHI) Dietary Modification (DM) randomized trial, in 48,835 postmenopausal women, included a subset of 1,606 WHI Memory Study (WHIMS) participants >= 65 years old, to assess low-fat dietary pattern influence on global cognitive function, evaluated with annual screening (Modified Mini–Mental State Examinations [3MSE]). Participants were randomized by a computerized, permuted block algorithm, stratified by age group and center, to a dietary intervention (40%) to reduce fat intake to 20% of energy and increase fruit, vegetable and grain intake or usual diet comparison groups (60%). The study outcome was possible cognition impairment (failed cognitive function screening) through the 8.5 year (median) dietary intervention. Those failing screening received a comprehensive, multi-phase cognitive function assessment to classify as: no cognitive impairment, mild cognitive impairment, or probable dementia. Exploratory analyses examined the composite endpoint of death after possible cognitive impairment through 18.7 years (median) follow-up. The WHI trials are registered at ClinicalTrials.gov:NCT00000611. FindingsAmong the 1,606 WHIMS participants, the dietary intervention statistically significantly reduced the incidence of possible cognitive impairment (n = 126; hazard ratio [HR] 0.59 95% confidence interval [CI] 0.38–0. 91, P = 0.01) with HR for dietary influence on subsequent mild cognitive impairment of 0.65 (95% CI 0.35–1.19) and HR of 0.63 (95% CI 0.19–2.10) for probable dementia (PD). Through 18.7 years, deaths from all-causes after possible cognitive impairment were non-significantly lower in the dietary intervention group (0.56% vs 0.77%, HR 0.83 95% CI 0.35 to 2.00, P = 0.16). InterpretationAdoption of a low-fat eating pattern, representing dietary moderation, significantly reduced risk of possible cognitive impairment in postmenopausal women. FundingSeveral Institutes of the US National Institutes of Health.

Modification of RC5 cryptoalgorythm for electronic data encryption systems

Encryption of electronic data requires the use of cryptanalysis functions. Information, like any value, is attacked by various scammers. The level of information security depends primarily on the security of the channels through which information from the company's information base can get into the network. To date, there are specially designed software tools that can block these channels and reduce the risk of leakage, theft or unauthorized access to information. The problem is that with an increase in the number of violations, their detection is reduced. The relevance of threats to the integrity and confidentiality of information requires careful attention to the task of protecting it. 20 years ago, the task of ensuring information security was solved with the help of cryptographic protection, the establishment of firewalls, and access control. Now these technologies are not enough, any information that has financial, competitive, military or political value is at risk. An additional risk is the possibility of intercepting the management of critical information infrastructure facilities. Particularly relevant is the increased stability of block algorithms, in particular, RC5, which is part of various open cryptographic libraries - OpenSSL, OpenVPN, etc. Improve the cryptographic stability of block diagrams and cryptographic algorithms by various methods. The article discusses the choice of shift functions for modifying the classic RC5 algorithm to increase the cryptographic stability of RC5 algorithm. For confirmation of efficiency modeling of the cryptographic system realized on the basis of modification of cryptographic algorithm RC5 was carried out and the time and qualitative characteristics of the work of the modified algorithm were obtained.

Acceleration of calculations using block algorithms for the difference solution of the heat equation

In this paper, we propose taking into account the architectural features of the processor at the stage of constructing the numerical method itself. This idea is illustrated by the example of the synthesis of a new difference scheme for the heat conduction equation, which has traditionally been the object of testing innovations in the theory of difference schemes. The architectural feature hierarchical structure of the computer memory chosen led to considerable communication costs even when a single hardware computational flow was used for organising the calculations. This feature is accounted for in computational linear algebra by using block algorithms, and in the theory of difference schemes, by using the technique of programming ‘tiling’. However, for the two-layer difference schemes of block algorithms for solving grid equations, prior to the proposed work, it was not known because of the impossibility of organising block calculations by using the existing schemes. Here, we propose a new method of constructing two-layer difference schemes and a mixed scheme with a shift as an example of the application of this method. In the course of the experiments, a five-fold acceleration of calculations according to this scheme was demonstrated relative to the traditional explicit model, with the same computational complexity.