Search results for: parameterized multi agent systems

Authors: M. Grandcolas, N. Rival, H. Bu, S. Jahren, R. Schmid, H. Johnsen

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The concept of an autonomic self-healing material, where initiation of repair is integrated to the material, is now being considered for engineering applications and is a hot topic in the literature. Among several concepts/techniques, two are most interesting: i) Capsules: Integration of microcapsules in or at the surface of coatings or fibre-like structures has recently gained much attention. Upon damage-induced cracking, the microcapsules are broken by the propagating crack fronts resulting in a release of an active chemical (healing agent) by capillary action, subsequently repairing and avoiding further crack growth. ii) Self-healing polymers: Interestingly, the introduction of dynamic covalent bonds into polymer networks has also recently been used as a powerful approach towards the design of various intrinsically self-healing polymer systems. The idea behind this is to reconnect the chemical crosslinks which are broken when a material fractures, restoring the integrity of the material and thereby prolonging its lifetime. We propose here to integrate both self-healing concepts (capsules, self-healing polymers) in electrospun fibres and coatings. Different capsule preparation approaches have been investigated in SINTEF. The most advanced method to produce capsules is based on emulsification to create a water-in-oil emulsion before polymerisation. The healing agent is a polyurethane-based dispersion that was encapsulated in shell materials consisting of urea-benzaldehyde resins. Results showed the successful preparation of microcapsules and release of the agent when capsules break. Since capsules are produced in water-in-oil systems we mainly investigated organic solvent based coatings while a major challenge resides in the incorporation of capsules into water-based coatings. We also focused on developing more robust microcapsules to prevent premature rupture of the capsules. The capsules have been characterized in terms of size, and encapsulation and release might be visualized by incorporating fluorescent dyes and examine the capsules by microscopy techniques. Alternatively, electrospinning is an innovative technique that has attracted enormous attention due to unique properties of the produced nano-to-micro fibers, ease of fabrication and functionalization, and versatility in controlling parameters. Especially roll-to-roll electrospinning is a unique method which has been used in industry to produce nanofibers continuously. Electrospun nanofibers can usually reach a diameter down to 100 nm, depending on the polymer used, which is of interest for the concept with self-healing polymer systems. In this work, we proved the feasibility of fabrication of POSS-based (POSS: polyhedral oligomeric silsesquioxanes, tradename FunzioNano™) nanofibers via electrospinning. Two different formulations based on aqueous or organic solvents have shown nanofibres with a diameter between 200 – 450nm with low defects. The addition of FunzioNano™ in the polymer blend also showed enhanced properties in term of wettability, promising for e.g. membrane technology. The self-healing polymer systems developed are here POSS-based materials synthesized to develop dynamic soft brushes.

Keywords: capsules, coatings, electrospinning, fibers

Procedia PDF Downloads 241

Authors: Adam Beaunoyer, Cory Beaunoyer, Mohammed Elmorsy, Hanan Saleh

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This research aims to create a reinforcement learning agent capable of racing in challenging simulated environments with a low collision count. We present a reinforcement learning agent that can navigate challenging tracks using both a Deep Q-Network (DQN) and a Soft Actor-Critic (SAC) method. A challenging track includes curves, jumps, and varying road widths throughout. Using open-source code on Github, the environment used in this research is based on the 1995 racing game WipeOut. The proposed reinforcement learning agent can navigate challenging tracks rapidly while maintaining low racing completion time and collision count. The results show that the SAC model outperforms the DQN model by a large margin. We also propose an alternative multiple-car model that can navigate the track without colliding with other vehicles on the track. The SAC model is the basis for the multiple-car model, where it can complete the laps quicker than the single-car model but has a higher collision rate with the track wall.

Keywords: reinforcement learning, soft actor-critic, deep q-network, self-driving cars, artificial intelligence, gaming

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Authors: Kyung-Jin You, Kiwon Rhee, Marc H. Schieber, Nitish V. Thakor, Hyun-Chool Shin

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It remains unknown whether M1 neurons encode multi-finger movements independently or as a certain neural network of single finger movements although multi-finger movements are physically a combination of single finger movements. We present an evidence of correlation between single and multi-finger movements and also attempt a challenging task of semi-blind decoding of neural data with minimum training of the neural decoder. Data were collected from 115 task-related neurons in M1 of a trained rhesus monkey performing flexion and extension of each finger and the wrist (12 single and 6 two-finger-movements). By exploiting correlation of temporal firing pattern between movements, we found that correlation coefficient for physically related movements pairs is greater than others; neurons tuned to single finger movements increased their firing rate when multi-finger commands were instructed. According to this knowledge, neural semi-blind decoding is done by choosing the greatest and the second greatest likelihood for canonical candidates. We achieved a decoding accuracy about 60% for multiple finger movement without corresponding training data set. this results suggest that only with the neural activities on single finger movements can be exploited to control dexterous multi-fingered neuroprosthetics.

Keywords: finger movement, neural activity, blind decoding, M1

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Authors: Małgorzata Drzewiecka, Tomasz Śliwiński, Maciej Radek

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The inhibition of histone deacetyles (HDACs) holds promise as a potential anti-cancer therapy because histone and non-histone protein acetylation is frequently disrupted in cancer, leading to cancer initiation and progression. Additionally, histone deacetylase inhibitors (HDACi) such as class I HDAC inhibitor - valproic acid (VPA) have been shown to enhance the effectiveness of DNA-damaging factors, such as cisplatin or radiation. In this study, we found that, using of VPA in combination with talazoparib (BMN-637 – PARP1 inhibitor – PARPi) and/or Dacarabazine (DTIC - alkylating agent) resulted in increased DNA double strand break (DSB) and reduced survival (while not affecting primary melanocytes )and proliferation of melanoma cells. Furthermore, pharmacologic inhibition of class I HDACs sensitizes melanoma cells to apoptosis following exposure to DTIC and BMN-637. In addition, inhibition of HDAC caused sensitization of melanoma cells to dacarbazine and BMN-637 in melanoma xenografts in vivo. At the mRNA and protein level histone deacetylase inhibitor downregulated RAD51 and FANCD2. This study provides that combining HDACi, alkylating agent and PARPi could potentially enhance the treatment of melanoma, which is known for being one of the most aggressive malignant tumors. The findings presented here point to a scenario in which HDAC via enhancing the HR-dependent repair of DSBs created during the processing of DNA lesions, are essential nodes in the resistance of malignant melanoma cells to methylating agent-based therapies.

Keywords: melanoma, hdac, parp inhibitor, valproic acid

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Authors: Farzad Pargar

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We introduce the preventive maintenance and renewal scheduling problem for a multi-unit system over a finite and discretized time horizon. Given the latest possible time for carrying out the next maintenance and renewal projects after the previous ones and considering several common set-up costs, the introduced scheduling model tries to minimize the cost of projects by grouping them and simultaneously finding the optimal balance between doing maintenance and renewal. We present a 0-1 pure integer linear programming that determines which projects should be performed together on which location and in which period (e.g., week or month). We consider railway track as a case for our study and test the performance of the proposed model on a set of test problems. The experimental results show that the proposed approach performs well.

Keywords: maintenance, renewal, scheduling, mathematical programming model

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Authors: Justie Su-Tzu Juan, Ming-Jheng Li, Ching-Fen Lee, Ruei-Yu Wu

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A secret image sharing scheme is a way to protect images. The main idea is dispersing the secret image into numerous shadow images. A secret image sharing scheme can withstand the impersonal attack and achieve the highly practical property of multiuse  is more practical. Therefore, this paper proposes a verifiable and detectable secret image-sharing scheme called VDGMSISS to solve the impersonal attack and to achieve some properties such as encrypting multi-secret images at one time and multi-use. Moreover, our scheme can also be used for any genera access structure.

Keywords: multi-secret image sharing scheme, verifiable, de-tectable, general access structure

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Authors: Albert Bou, Sebastian Dittert, Gianni de Fabritiis

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Advancing reinforcement learning (RL) requires tools that are flexible enough to easily prototype new methods while avoiding impractically slow experimental turnaround times. To match the first requirement, the most popular RL libraries advocate for highly modular agent composability, which facilitates experimentation and development. To solve challenging environments within reasonable time frames, scaling RL to large sampling and computing resources has proved a successful strategy. However, this capability has been so far difficult to combine with modularity. In this work, we explore design choices to allow agent composability both at a local and distributed level of execution. We propose a versatile approach that allows the definition of RL agents at different scales through independent, reusable components. We demonstrate experimentally that our design choices allow us to reproduce classical benchmarks, explore multiple distributed architectures, and solve novel and complex environments while giving full control to the user in the agent definition and training scheme definition. We believe this work can provide useful insights to the next generation of RL libraries.

Keywords: deep reinforcement learning, Python, PyTorch, distributed training, modularity, library

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Authors: Ma. Rosario Concepcion O. Ang, Luis Caezar Ian K. Panganiban, Charmyne B. Mamador, Oliver Dan G. De Luna, Michael D. Bausas, Joselito P. Cruz

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PhilSHORE is a multi-site, multi-device and multi-criteria decision support tool designed to support the development of tidal current energy in the Philippines. Its platform is based on Geographic Information Systems (GIS) which allows for the collection, storage, processing, analyses and display of geospatial data. Combining GIS tools with open source web development applications, PhilSHORE becomes a webGIS-based marine spatial planning tool. To date, PhilSHORE displays output maps and graphs of power and energy density, site suitability and site-device analysis. It enables stakeholders and the public easy access to the results of tidal current energy resource assessments and site suitability analyses. Results of the initial development shows PhilSHORE is a promising decision support tool for ORE project developments.

Keywords: gis, site suitability analysis, tidal current energy resource assessment, webgis

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Authors: Xiang Li, Jian-Qiao Sun

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As the crucial component of city traffic network, intersections have significant impacts on urban traffic performance. Despite of the rapid development in transportation systems, increasing traffic volumes result in severe congestions especially at intersections in urban areas. Effective regulation of vehicle flows at intersections has always been an important issue in the traffic control system. This study presents a multi-objective optimization method at intersections with cellular automata to achieve better traffic performance. Vehicle conflicts and pedestrian interference are considered. Three categories of the traffic performance are studied including transportation efficiency, energy consumption and road safety. The left-turn signal type, signal timing and lane assignment are optimized for different traffic flows. The multi-objective optimization problem is solved with the cell mapping method. The optimization results show the conflicting nature of different traffic performance. The influence of different traffic variables on the intersection performance is investigated. It is observed that the proposed optimization method is effective in regulating the traffic at the intersection to meet multiple objectives. Transportation efficiency can be usually improved by the permissive left-turn signal, which sacrifices safety. Right-turn traffic suffers significantly when the right-turn lanes are shared with the through vehicles. The effect of vehicle flow on the intersection performance is significant. The display pattern of the optimization results can be changed remarkably by the traffic volume variation. Pedestrians have strong interference with the traffic system.

Keywords: cellular automata, intersection, multi-objective optimization, traffic system

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Authors: K. S. Hemant Yadav, H. G. Shivakumar

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The present study investigation was to prepare and evaluate the mucoadhesive multi-particulate system for nasal drug delivery of anti-histaminic drug. Ebastine was chosen as the model drug. Drug loaded nanoparticles of Ebastine were prepared by ionic gelation method using chitosan as polymer using the drug-polymer weight ratios 1:1, 1:2, 1:3. Sodium tripolyphosphate (STPP) was used as the cross-linking agent in the range of 0.5 and 0.7% w/v. FTIR and DSC studies indicated that no chemical interaction occurred between the drug and polymers. Particle size ranged from 169 to 500 nm. The drug loading and entrapment efficiency was found to increase with increase in chitosan concentration and decreased with increase in poloxamer 407 concentration. The results of in vitro mucoadhesion carried out showed that all the prepared formulation had good mucoadhesive property and mucoadhesion increases with increase in the concentration of chitosan. The in vitro release pattern of all the formulations was observed to be in a biphasic manner characterized by slight burst effect followed by a slow release. By the end of 8 hrs, formulation F6 showed a release of only 86.9% which explains its sustained behaviour. The ex-vivo permeation of the pure drug ebastine was rapid than the optimized formulation(F6) indicating the capability of the chitosan polymer to control drug permeation rate through the sheep nasal mucosa. The results indicated that the mucoadhesive nanoparticulate system can be used for the nasal delivery of antihistaminic drugs in an effective manner.

Keywords: nasal, nanoparticles, ebastine, anti-histaminic drug, mucoadhesive multi-particulate system

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Authors: Yasser Sanad, Thu Trang Dao

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Introduction: Implementing the One Health (OH) approach requires an integrated, interdisciplinary, and cross-sectoral methodology. OH is a key tool for developing and implementing programs and projects and includes developing ambitious policies that consider the common needs and benefits of human, animal, plant, and ecosystem health. OH helps humanity readjust its path to environmentally friendly and impartial sustainability. As co-leader of the Global Health Security Agenda’s Zoonotic Disease Action Package, Vietnam pioneered a strong OH approach to effectively address early waves of the COVID-19 outbreak in-country. Context and Aim: The repeated surges in COVID-19 in Vietnam challenged the capabilities of the national system and disclosed the gaps in multi-sectoral coordination and resilience. To address this, FHI 360 advocated for the standardization of the OH platform by government actors to increase the resiliency of the system during and post COVID-19. Methods: FHI 360 coordinated technical resources to develop and implement evidence-based OH policies, promoting high-level policy dialogue between the Ministries of Health, Agriculture, and the Environment, and policy research to inform developed policies and frameworks. Through discussions, an OH-building Partnership (OHP) was formed, linking climate change, the environment, and human and animal health. Findings: The OHP Framework created a favorable policy environment within and between sectors, as well as between governments and international health security partners. It also promoted strategic dialogue, resource mobilization, policy advocacy, and integration of international systems with National Steering Committees to ensure accountability and emphasize national ownership. Innovative contribution to policy, practice and/or research: OHP was an effective evidence-based research-to-policy platform linking to the National One Health Strategic Plan (2021-2025). Collectively they serve as a national framework for the implementation and monitoring of OH activities. Through the adoption of policies and plans, the risk of zoonotic pathogens, environmental agent spillover, and antimicrobial resistance can be minimized through strengthening multi-sectoral OH collaboration for health security.

Keywords: one health, national policies, health security, COVID-19, Vietnam

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Authors: Nasser S. Shebka

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Fuzzy logic is used in complex adaptive systems where classical tools of representing knowledge are unproductive. Nevertheless, the incorporation of fuzzy logic, as it’s the case with all artificial intelligence tools, raised some inconsistencies and limitations in dealing with increased complexity systems and rules that apply to real-life situations and hinders the ability of the inference process of such systems, but it also faces some inconsistencies between inferences generated fuzzy rules of complex or imprecise knowledge-based systems. The use of fuzzy logic enhanced the capability of knowledge representation in such applications that requires fuzzy representation of truth values or similar multi-value constant parameters derived from multi-valued logic, which set the basis for the three t-norms and their based connectives which are actually continuous functions and any other continuous t-norm can be described as an ordinal sum of these three basic ones. However, some of the attempts to solve this dilemma were an alteration to fuzzy logic by means of non-monotonic logic, which is used to deal with the defeasible inference of expert systems reasoning, for example, to allow for inference retraction upon additional data. However, even the introduction of non-monotonic fuzzy reasoning faces a major issue of conflict resolution for which many principles were introduced, such as; the specificity principle and the weakest link principle. The aim of our work is to improve the logical representation and functional modelling of AI systems by presenting a method of resolving existing and potential rule conflicts by representing temporal modalities within defeasible inference rule-based systems. Our paper investigates the possibility of resolving fuzzy rules conflict in a non-monotonic fuzzy reasoning-based system by introducing temporal modalities and Kripke's general weak modal logic operators in order to expand its knowledge representation capabilities by means of flexibility in classifying newly generated rules, and hence, resolving potential conflicts between these fuzzy rules. We were able to address the aforementioned problem of our investigation by restructuring the inference process of the fuzzy rule-based system. This is achieved by using time-branching temporal logic in combination with restricted first-order logic quantifiers, as well as propositional logic to represent classical temporal modality operators. The resulting findings not only enhance the flexibility of complex rule-base systems inference process but contributes to the fundamental methods of building rule bases in such a manner that will allow for a wider range of applicable real-life situations derived from a quantitative and qualitative knowledge representational perspective.

Keywords: fuzzy rule-based systems, fuzzy tense inference, intelligent systems, temporal modalities

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Authors: Kishor Bhagwat, Gayatri Vyas

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Construction industry is earmarked with complex processes depending on the nature and scope of the project. In recent years, developments in this sector are remarkable and have resulted in both positive and negative impacts on the environment and human being. Sustainable construction can be looked upon as one of the solution to overcome the negative impacts since sustainable construction is a vast concept, which includes many parameters, and sometimes the use of multi-criteria decision making [MCDM] tools becomes necessary. The main objective of this study is to determine the weightage of sustainable building parameters with the help of MCDM tools. Questionnaire survey was conducted to examine the perspective of respondents on the importance of weights of the criterion, and the respondents were architects, green building consultants, and civil engineers. This paper presents an overview of research related to Indian and international green building rating systems and MCDM. The results depict that economy, environmental health, and safety, site selection, climatic condition, etc., are important parameters in sustainable construction.

Keywords: green building, sustainability, multi-criteria decision making method [MCDM], analytical hierarchy process [AHP], technique for order preference by similarity to an ideal solution [TOPSIS], entropy

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Authors: Chhaya Gangwal, R. N. Bhaumik, Shishir Kumar

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Handling uncertainty and impreciseness of knowledge appears to be a challenging task in Information Systems. Intuitionistic fuzzy (IF) and rough set theory enhances databases by allowing it for the management of uncertainty and impreciseness. This paper presents a new efficient query optimization technique for the multi-valued or imprecise IF rough database. The usefulness of this technique was illustrated on malaria knowledge from the rural tribal communities of Tripura where most of the information is multi-valued and imprecise. Then, the querying about knowledge on malaria is executed into SQL server to make the implementation of IF rough data querying simpler.

Keywords: intuitionistic fuzzy set, rough set, relational database, IF rough relational database

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Authors: Liqin Zhang, Liang Yan

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This paper addresses the speed synchronization control problem for a network-based multi-motor system from the perspective of cluster consensus theory. Each motor is considered as a single agent connected through fixed and undirected network. This paper presents an improved control protocol from three aspects. First, for the purpose of improving both tracking and synchronization performance, this paper presents a distributed leader-following method. The improved control protocol takes the importance of each motor’s speed into consideration, and all motors are divided into different groups according to speed weights. Specifically, by using control parameters optimization, the synchronization error and tracking error can be regulated and decoupled to some extent. The simulation results demonstrate the effectiveness and superiority of the proposed strategy. In practical engineering, the simplified models are unrealistic, such as single-integrator and double-integrator. And previous algorithms require the acceleration information of the leader available to all followers if the leader has a varying velocity, which is also difficult to realize. Therefore, the method focuses on an observer-based variable structure algorithm for consensus tracking, which gets rid of the leader acceleration. The presented scheme optimizes synchronization performance, as well as provides satisfactory robustness. What’s more, the existing algorithms can obtain a stable synchronous system; however, the obtained stable system may encounter some disturbances that may destroy the synchronization. Focus on this challenging technological problem, a state-dependent-switching approach is introduced. In the presence of unmeasured angular speed and unknown failures, this paper investigates a distributed fault-tolerant consensus tracking algorithm for a group non-identical motors. The failures are modeled by nonlinear functions, and the sliding mode observer is designed to estimate the angular speed and nonlinear failures. The convergence and stability of the given multi-motor system are proved. Simulation results have shown that all followers asymptotically converge to a consistent state when one follower fails to follow the virtual leader during a large enough disturbance, which illustrates the good performance of synchronization control accuracy.

Keywords: consensus control, distributed follow, fault-tolerant control, multi-motor system, speed synchronization

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Authors: Neeraj Malhotra, Ramya Shenoy

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Objective: To assess the effect of clinical parameters (bonding agent, preparation design & storage media) on the strength of reattached anterior tooth fragment. Methodology: This is a systematic review and meta-analysis for articles referred from MEDLINE, PUBMED, and GOOGLE SCHOLAR. The articles on tooth reattachment and clinical factors affecting fracture strength/bond strength/fracture resistance of the reattached tooth fragment in anterior teeth and published in English from 1999 to 2016 were included for final review. Results: Out of 120 shortlisted articles, 28 articles were included for the systematic review and meta-analysis based on 3 clinical parameters i.e. bonding agent, tooth preparation design & storage media. Forest plot & funnel plots were generated based on individual clinical parameter and their effect on strength of reattached anterior tooth fragment. Results based on analysis suggest combination of both conclusive evidence favoring the experimental group as well as in-conclusive evidence for individual parameter. Conclusion: There is limited evidence as there are fewer articles supporting each parameter in human teeth. Bonding agent had showed better outcome in selected studies.

Keywords: bonding agent, bond strength, fracture strength, preparation design, reattachment, storage media

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Authors: Jianyong Xue, Olivier L. Georgeon, Salima Hassas

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During the initial phase of cognitive development, infants exhibit amazing abilities to generate novel behaviors in unfamiliar situations, and explore actively to learn the best while lacking extrinsic rewards from the environment. These abilities set them apart from even the most advanced autonomous robots. This work seeks to contribute to understand and replicate some of these abilities. We propose the Bottom-up hiErarchical sequential Learning algorithm with Constructivist pAradigm (BEL-CA) to design agents capable of learning autonomously and continuously through interactions. The algorithm implements no assumption about the semantics of input and output data. It does not rely upon a model of the world given a priori in the form of a set of states and transitions as well. Besides, we propose a toolkit to analyze the learning process at run time called GAIT (Generating and Analyzing Interaction Traces). We use GAIT to report and explain the detailed learning process and the structured behaviors that the agent has learned on each decision making. We report an experiment in which the agent learned to successfully interact with its environment and to avoid unfavorable interactions using regularities discovered through interaction.

Keywords: cognitive development, constructivist learning, hierarchical sequential learning, self-adaptation

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Authors: Chaudhari S. G., Saxena, S.

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We systematically and quantitatively investigated the effect of glucose as a model of natural molecular crowding agent on the structure and thermodynamics of Watson-Crick base paired three duplexes (named as D1, D2 and D3) of different base compositions and lengths. Structural analyses demonstrated that duplexes (D1 and D2) folded into B-form with different cations in the absence and presence of glucose while duplex (D3) folded into mixed A and B-form. Moreover, we demonstrated that the duplex was more stable in the absence of glucose, and marginally destabilized in its presence because glucose act as a weak structure breaker on the tetrahedral network of water. In the absence of glucose, the values of ΔG°25 for duplex (D1) were -13.56, -13.76, -12.46, and -12.36 kcal/mol, for duplex (D2) were -13.64, -12.93, -12.86, and -12.30 kcal/mol, for duplex (D3) were -10.05, -11.76, -9.91, -9.70 kcal/mol in the presence of Na+, K+, Na+ + Mg++ and K+ + Mg++ respectively. At high concentration of glucose (1:10000), there was increase in ΔG°25 for duplex (D1) -12.47, -12.37, -11.96, -11.55 kcal/mol, for duplex (D2) -12.37, -11.47, -11.98, -11.01 kcal/mol and for duplex (D3) -8.47, -9.17, -9.16, -8.66 kcal/mol. Our results provide the information that structure and stability of DNA duplex depends on the structure of molecular crowding agent present in its close vicinity. In this study, I have taken the hydration of simple sugar as an essential model for understanding interactions between hydrophilic groups and interfacial water molecules and its effect on hydrogen bonded DNA duplexes. On the basis of these relatively simple building blocks I hope to gain some insights for understanding more generally the properties of sugar–water–salt systems with DNA duplexes.

Keywords: natural molecular crowding, DNA Duplex, structure of DNA, bioengineering and life sciences

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Authors: Shonak Bansal, Prince Jain, Arun Kumar Singh, Neena Gupta

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Recently nature–inspired algorithms have widespread use throughout the tough and time consuming multi–objective scientific and engineering design optimization problems. In this paper, we present extended forms of firefly algorithm to find optimal Golomb ruler (OGR) sequences. The OGRs have their one of the major application as unequally spaced channel–allocation algorithm in optical wavelength division multiplexing (WDM) systems in order to minimize the adverse four–wave mixing (FWM) crosstalk effect. The simulation results conclude that the proposed optimization algorithm has superior performance compared to the existing conventional computing and nature–inspired optimization algorithms to find OGRs in terms of ruler length, total optical channel bandwidth and computation time.

Keywords: channel allocation, conventional computing, four–wave mixing, nature–inspired algorithm, optimal Golomb ruler, lévy flight distribution, optimization, improved multi–objective firefly algorithms, Pareto optimal

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Authors: Tomas Barnak, Libor Matejka

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The aim of this study is to create a standard application using multi-criteria evaluation in the field of forensic engineering. This situation can occur in the professional assessment in several cases such as when it is necessary to consider more criteria variant of the structural subsystems, more variants according to several criteria based on a court claim, which requires expert advice. A problematic situation arises when it is necessary to clearly determine the ranking of the options according to established criteria, and reduce subjective evaluation. For the procurement in the field of construction which is based on the prepared text of the law not only economic criteria but also technical, technological and environmental criteria will be determined. This fact substantially changes the style of evaluation of individual bids. For the above-mentioned needs of procurement, the unification of expert’s decisions and the use of multi-criteria assessment seem to be a reasonable option. In the case of experimental verification when using multi-criteria evaluation of alternatives construction subsystem the economic, technical, technological and environmental criteria will be compared. The core of the solution is to compare a selected number of set criteria, application methods and evaluation weighting based on the weighted values assigned to each of the criteria to use multi-criteria evaluation methods. The sequence of individual variations is determined by the evaluation of the importance of the values of corresponding criteria concerning expertise in the problematic of outside wall constructional subsystems.

Keywords: criteria, expertise, multi-criteria evaluation, outside wall subsystems

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Authors: C. Li, G. Coates, N. Johnson, M. Mc Guinness

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In the UK, flooding is responsible for significant losses to the economy due to the impact on businesses, the vast majority of which are Small and Medium Enterprises (SMEs). Businesses of this nature tend to lack formal plans to aid their response to and recovery from disruptive events such as flooding. This paper reports on work on how an agent-based model (ABM) is being developed based on interview data gathered from SMEs at-risk of flooding and/or have direct experience of flooding. The ABM will enable simulations to be performed allowing investigations of different response strategies which SMEs may employ to lessen the impact of flooding, thus strengthening their resilience.

Keywords: ABM, flood response, SMEs, business continuity

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Authors: Ahmed Madian, Muaz Aljarhi

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Coordinate Rotation Digital Computer (CORDIC) is a unique digital computing unit intended for the computation of mathematical operations and functions. This paper presents a multi-CORDIC processor that integrates different CORDIC architectures on a single FPGA chip and allows the user to select the CORDIC architecture to proceed with based on what he wants to calculate and his/her needs. Synthesis show that radix 2 CORDIC has the lowest clock delay, radix 8 CORDIC has the highest LUT usage and lowest register usage while Hybrid Radix 4 CORDIC had the highest clock delay.

Keywords: multi, CORDIC, FPGA, processor

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Authors: Fouzia Qamar, Shahida Hasnain

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The present study is primarily concerned with the alteration in haemocyte profile of adult male Periplaneta americana with emphasis on the effect of bacterial inoculations on the haemogram i.e., total haemocyte count (THC) and differential haemocyte count (DHC) of different haemocyte types of the target insect. Haemolymph cellular profile showed considerable alterations under the effect of nine strains of Agrobacterium tumefaciens after 8, 16 and 24 hrs of treatment thereby signifying the potential role of Agrobacterium tumefaciens as a possible biocontrol agent against the house hold pests.

Keywords: Agrobacterium tumefaciens, Periplaneta americana, Haemolymph, cellular parametes

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Authors: Aydin Teymourifar, Gurkan Ozturk

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In this paper, a hybrid Tabu Search (TS) algorithm is suggested for the multi-objective job shop scheduling problems (MO-JSSPs). The algorithm integrates several shifting bottleneck based neighborhood structures with the Giffler & Thompson algorithm, which improve efficiency of the search. Diversification and intensification are provided with local and global left shift algorithms application and also new semi-active, active, and non-delay schedules creation. The suggested algorithm is tested in the MO-JSSPs benchmarks from the literature based on the Pareto optimality concept. Different performances criteria are used for the multi-objective algorithm evaluation. The proposed algorithm is able to find the Pareto solutions of the test problems in shorter time than other algorithm of the literature.

Keywords: tabu search, heuristics, job shop scheduling, multi-objective optimization, Pareto optimality

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Authors: Zijian Zhang, Yangyang Dong

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Synchronization is of great importance to ensure the multi-arm robot to complete the task. Therefore, a synchronous controller is designed to coordinate task space motion of the multi-arm in the paper. The position error, the synchronous position error, and the coupling position error are all considered in the controller. Besides, an adaptive control method is used to adjust parameters of the controller to improve the effectiveness of coordinated control performance. Simulation in the Matlab shows the effectiveness of the method. At last, a robot experiment platform with two 7-DOF (Degree of Freedom) robot arms has been established and the synchronous controller simplified to control dual-arm robot has been validated on the experimental set-up. Experiment results show the position error decreased 10% and the corresponding frequency is also greatly improved.

Keywords: synchronous control, space robot, task space control, multi-arm robot

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Authors: Liwei Liu, Shuguo Pan, Wang Gao

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In order to take full advantages of the BDS-3 penta-frequency signals in the long-baseline RTK positioning, a long-baseline RTK positioning method based on the BDS-3 penta-frequency ionospheric-reduced (IR) combinations is proposed. First, the low noise and weak ionospheric delay characteristics of the multi-frequency combined observations of BDS-3is analyzed. Second, the multi-frequency extra-wide-lane (EWL)/ wide-lane (WL) combinations with long-wavelengths are constructed. Third, the fixed IR EWL combinations are used to constrain the IR WL, then constrain narrow-lane (NL)ambiguityies and start multi-epoch filtering. There is no need to consider the influence of ionospheric parameters in the third step. Compared with the estimated ionospheric model, the proposed method reduces the number of parameters by half, so it is suitable for the use of multi-frequency and multi-system real-time RTK. The results using real data show that the stepwise fixed model of the IR EWL/WL/NL combinations can realize long-baseline instantaneous cimeter-level positioning.

Keywords: penta-frequency, ionospheric-reduced (IR), RTK positioning, long-baseline

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Authors: Chia Jui Hsieh, Jyh Cheng Chen, Chih Wei Kuo, Ruei Teng Wang, Woei Chyn Chu

Abstract:

Compressed sensing (CS) based computed tomographic (CT) reconstruction algorithm utilizes total variation (TV) to transform CT image into sparse domain and minimizes L1-norm of sparse image for reconstruction. Different from the traditional CS based reconstruction which only calculates x-coordinate and y-coordinate TV to transform CT images into sparse domain, we propose a multi-directional TV to transform tomographic image into sparse domain for low-dose reconstruction. Our method considers all possible directions of TV calculations around a pixel, so the sparse transform for CS based reconstruction is more accurate. In 2D CT reconstruction, we use eight-directional TV to transform CT image into sparse domain. Furthermore, we also use 26-directional TV for 3D reconstruction. This multi-directional sparse transform method makes CS based reconstruction algorithm more powerful to reduce noise and increase image quality. To validate and evaluate the performance of this multi-directional sparse transform method, we use both Shepp-Logan phantom and a head phantom as the targets for reconstruction with the corresponding simulated sparse projection data (angular sampling interval is 5 deg and 6 deg, respectively). From the results, the multi-directional TV method can reconstruct images with relatively less artifacts compared with traditional CS based reconstruction algorithm which only calculates x-coordinate and y-coordinate TV. We also choose RMSE, PSNR, UQI to be the parameters for quantitative analysis. From the results of quantitative analysis, no matter which parameter is calculated, the multi-directional TV method, which we proposed, is better.

Keywords: compressed sensing (CS), low-dose CT reconstruction, total variation (TV), multi-directional gradient operator

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Authors: A.N. Moulay Khatir, A. Guen-Bouazza, B. Bouazza

Abstract:

SOI-Multifin-FET shows excellent transistor characteristics, ideal sub-threshold swing, low drain induced barrier lowering (DIBL) without pocket implantation and negligible body bias dependency. In this work, we analyzed this combination by a three-dimensional numerical device simulator to investigate the influence of fins number on corner effect by analyzing its electrical characteristics and potential distribution in the oxide and the silicon in the section perpendicular to the flow of the current for SOI-single-fin FET, three-fin and five-fin, and we provide a comparison with a Trigate SOI Multi-FinFET structure.

Keywords: SOI, FinFET, corner effect, dual-gate, tri-gate, Multi-Fin FET

Procedia PDF Downloads 447

Authors: Vincent Andrew Cappellano

Abstract:

In the early phases of critical infrastructure system design, translating distributed computing requirements to an architecture has risk given the multitude of approaches (e.g., cloud, edge, fog). In many systems, a single requirement for system uptime / availability is used to encompass the system’s intended operations. However, when architected systems may perform to those availability requirements only during normal operations and not during component failure, or during outages caused by adversary attacks on critical infrastructure (e.g., physical, cyber). System designers lack a structured method to evaluate availability requirements against candidate system architectures through deep degradation scenarios (i.e., normal ops all the way down to significant damage of communications or physical nodes). This increases risk of poor selection of a candidate architecture due to the absence of insight into true performance for systems that must operate as a piece of critical infrastructure. This research effort proposes a process to analyze critical infrastructure system availability requirements and a candidate set of systems architectures, producing a metric assessing these architectures over a spectrum of degradations to aid in selecting appropriate resilient architectures. To accomplish this effort, a set of simulation and evaluation efforts are undertaken that will process, in an automated way, a set of sample requirements into a set of potential architectures where system functions and capabilities are distributed across nodes. Nodes and links will have specific characteristics and based on sampled requirements, contribute to the overall system functionality, such that as they are impacted/degraded, the impacted functional availability of a system can be determined. A machine learning reinforcement-based agent will structurally impact the nodes, links, and characteristics (e.g., bandwidth, latency) of a given architecture to provide an assessment of system functional uptime/availability under these scenarios. By varying the intensity of the attack and related aspects, we can create a structured method of evaluating the performance of candidate architectures against each other to create a metric rating its resilience to these attack types/strategies. Through multiple simulation iterations, sufficient data will exist to compare this availability metric, and an architectural recommendation against the baseline requirements, in comparison to existing multi-factor computing architectural selection processes. It is intended that this additional data will create an improvement in the matching of resilient critical infrastructure system requirements to the correct architectures and implementations that will support improved operation during times of system degradation due to failures and infrastructure attacks.

Keywords: architecture, resiliency, availability, cyber-attack

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Authors: O. Adjoul, A. Feugier, K. Benfriha, A. Aoussat

Abstract:

In general, issues related to design and maintenance are considered in an independent manner. However, the decisions made in these two sets influence each other. The design for maintenance is considered an opportunity to optimize the life cycle cost of a product, particularly in the nuclear or aeronautical field, where maintenance expenses represent more than 60% of life cycle costs. The design of large-scale systems starts with product architecture, a choice of components in terms of cost, reliability, weight and other attributes, corresponding to the specifications. On the other hand, the design must take into account maintenance by improving, in particular, real-time monitoring of equipment through the integration of new technologies such as connected sensors and intelligent actuators. We noticed that different approaches used in the Design For Maintenance (DFM) methods are limited to the simultaneous characterization of the reliability and maintainability of a multi-component system. This article proposes a method of DFM that assists designers to propose dynamic maintenance for multi-component industrial systems. The term "dynamic" refers to the ability to integrate available monitoring data to adapt the maintenance decision in real time. The goal is to maximize the availability of the system at a given life cycle cost. This paper presents an approach for simultaneous optimization of the design and maintenance of multi-component systems. Here the design is characterized by four decision variables for each component (reliability level, maintainability level, redundancy level, and level of monitoring data). The maintenance is characterized by two decision variables (the dates of the maintenance stops and the maintenance operations to be performed on the system during these stops). The DFM model helps the designers choose technical solutions for the large-scale industrial products. Large-scale refers to the complex multi-component industrial systems and long life-cycle, such as trains, aircraft, etc. The method is based on a two-level hybrid algorithm for simultaneous optimization of design and maintenance, using genetic algorithms. The first level is to select a design solution for a given system that considers the life cycle cost and the reliability. The second level consists of determining a dynamic and optimal maintenance plan to be deployed for a design solution. This level is based on the Maintenance Free Operating Period (MFOP) concept, which takes into account the decision criteria such as, total reliability, maintenance cost and maintenance time. Depending on the life cycle duration, the desired availability, and the desired business model (sales or rental), this tool provides visibility of overall costs and optimal product architecture.

Keywords: availability, design for maintenance (DFM), dynamic maintenance, life cycle cost (LCC), maintenance free operating period (MFOP), simultaneous optimization

Procedia PDF Downloads 91