Search results for: memory optimization

Authors: Katielly Vianna Polkowski, Rodrigo Denizarte de Oliveira Polkowski, Cristiano Grings Herbert

Abstract:

The use of nanomaterials in the formulation of polymeric materials modifies their molecular structure, offering an infinite range of possibilities for the development of smart products, being of great importance for science and contemporary industry. Shape memory polymers are generally lightweight, have high shape recovery capabilities, they are easy to process and have properties that can be adapted for a variety of applications. Shape memory materials are active materials that have attracted attention due to their superior damping properties when compared to conventional structural materials. The development of methodologies capable of preparing new materials, which use graphene in their structure, represents technological innovation that transforms low-cost products into advanced materials with high added value. To obtain an improvement in the shape memory effect (SME) of polymeric materials, it is possible to use graphene in its composition containing low concentration by mass of graphene nanoplatelets (GNP), graphene oxide (GO) or other functionalized graphene, via different mixture process. As a result, there was an improvement in the SME, regarding the increase in the values of maximum strain. In addition, the use of graphene contributes to obtaining nanocomposites with superior electrical properties, greater crystallinity, as well as resistance to material degradation. The methodology used in the research is Systematic Review, scientific investigation, gathering relevant studies on influence of nanomaterials on the properties of shape memory polymeric, using the literature database as a source and study methods. In the present study, a systematic reviewwas performed of all papers published from 2014 to 2022 regarding graphene and shape memory polymeric througha search of three databases. This study allows for easy identification of themost relevant fields of study with respect to graphene and shape memory polymeric, as well as the main gaps to beexplored in the literature. The addition of graphene showed improvements in obtaining higher values of maximum deformation of the material, attributed to a possible slip between stacked or agglomerated nanostructures, as well as an increase in stiffness due to the increase in the degree of phase separation that results in a greater amount physical cross-links, referring to the formation of shortrange rigid domains.

Keywords: graphene, shape memory, smart materials, polymers, nanomaterials

Procedia PDF Downloads 51

Authors: Seyed Abbas Tabatabaei, Marjan Naderan Tahan, Arman Kadkhodai

Abstract:

An efficient optimization approach, called feasible gate (FG), is developed to enhance the computation efficiency and solution quality of the previously developed highway alignment optimization (HAO) model. This approach seeks to realistically represent various user preferences and environmentally sensitive areas and consider them along with geometric design constraints in the optimization process. This is done by avoiding the generation of infeasible solutions that violate various constraints and thus focusing the search on the feasible solutions. The proposed method is simple, but improves significantly the model’s computation time and solution quality. On the other, highway alignment optimization through Feasible Gates, eventuates only economic model by considering minimum design constrains includes minimum reduce of circular curves, minimum length of vertical curves and road maximum gradient. This modelling can reduce passenger comfort and road safety. In most of highway optimization models, by adding penalty function for each constraint, final result handles to satisfy minimum constraint. In this paper, we want to propose a safety-function solution by introducing gift function.

Keywords: safety, highway geometry, optimization, alignment

Procedia PDF Downloads 383

Authors: Camille Charlebois-Plante, Marie-Ève Bourassa, Gaelle Dumel, Meriem Sabir, Louis De Beaumont

Abstract:

To the extent of our knowledge, there has been little interest in the chronic effects of mild traumatic brain injury (mTBI) on cognition during normal aging. This is rather surprising considering the impacts on daily and social functioning. In addition, sustaining a mTBI during late adulthood may increase the effect of normal biological aging in individuals who consider themselves normal and healthy. The objective of this study was to characterize the persistent neuropsychological repercussions of mTBI sustained during late adulthood, on average 12 months prior to testing. To this end, 35 mTBI patients and 42 controls between the ages of 50 and 69 completed an exhaustive neuropsychological assessment lasting three hours. All mTBI patients were asymptomatic and all participants had a score ≥ 27 at the MoCA. The evaluation consisted of 20 standardized neuropsychological tests measuring memory, attention, executive and language functions, as well as information processing speed. Performance on tests of visual (Brief Visuospatial Memory Test Revised) and verbal memory (Rey Auditory Verbal Learning Test and WMS-IV Logical Memory subtest), lexical access (Boston Naming Test) and response inhibition (Stroop) revealed to be significantly lower in the mTBI group. These findings suggest that a mTBI sustained during late adulthood induces lasting effects on cognitive function. Episodic memory and executive functions seem to be particularly vulnerable to enduring mTBI effects.

Keywords: cognitive function, late adulthood, mild traumatic brain injury, neuropsychology

Procedia PDF Downloads 146

Authors: Hussain Syed Asad, Richard Kwok Kit Yuen, Gongsheng Huang

Abstract:

Real-time optimization has been considered an effective approach for improving energy efficient operation of heating, ventilation, and air-conditioning (HVAC) systems. In model-based real-time optimization, model mismatches cannot be avoided. When model mismatches are significant, the performance of the real-time optimization will be impaired and hence the expected energy saving will be reduced. In this paper, the model mismatches for chiller plant on real-time optimization are considered. In the real-time optimization of the chiller plant, simplified semi-physical or grey box model of chiller is always used, which should be identified using available operation data. To overcome the model mismatches associated with the chiller model, hybrid Genetic Algorithms (HGAs) method is used for online real-time training of the chiller model. HGAs combines Genetic Algorithms (GAs) method (for global search) and traditional optimization method (i.e. faster and more efficient for local search) to avoid conventional hit and trial process of GAs. The identification of model parameters is synthesized as an optimization problem; and the objective function is the Least Square Error between the output from the model and the actual output from the chiller plant. A case study is used to illustrate the implementation of the proposed method. It has been shown that the proposed approach is able to provide reliability in decision making, enhance the robustness of the real-time optimization strategy and improve on energy performance.

Keywords: energy performance, hybrid adaptive modeling, hybrid genetic algorithms, real-time optimization, heating, ventilation, and air-conditioning

Procedia PDF Downloads 385

Authors: Badr M. Alshammari, T. Guesmi

Abstract:

In this paper, the concept of a non-dominated sorting multi-objective particle swarm optimization with local search (NSPSO-LS) is presented for the optimal design of multimachine power system stabilizers (PSSs). The controller design is formulated as an optimization problem in order to shift the system electromechanical modes in a pre-specified region in the s-plan. A composite set of objective functions comprising the damping factor and the damping ratio of the undamped and lightly damped electromechanical modes is considered. The performance of the proposed optimization algorithm is verified for the 3-machine 9-bus system. Simulation results based on eigenvalue analysis and nonlinear time-domain simulation show the potential and superiority of the NSPSO-LS algorithm in tuning PSSs over a wide range of loading conditions and large disturbance compared to the classic PSO technique and genetic algorithms.

Keywords: multi-objective optimization, particle swarm optimization, power system stabilizer, low frequency oscillations

Procedia PDF Downloads 402

Authors: Gagandeep Singh

Abstract:

The sensor field optimization is a serious issue in WSNs and has been ignored by many researchers. As in numerous real-time sensing fields the sensor nodes on the corners i.e. on the segment boundaries will become lifeless early because no extraordinary safety is presented for them. Accordingly, in this research work the central objective is on the segment based optimization by separating the sensor field between advance and normal segments. The inspiration at the back this sensor field optimization is to extend the time spam when the first sensor node dies. For the reason that in normal sensor nodes which were exist on the borders may become lifeless early because the space among them and the base station is more so they consume more power so at last will become lifeless soon.

Keywords: WSNs, ECRSEP, SEP, field optimization, energy

Procedia PDF Downloads 266

Authors: J. Fox, J. Randhawa, M. Chan, L. Campbell, A. Weakely, D. J. Harvey, S. Tomaszewski Farias

Abstract:

Early identification of individuals at risk for conversion to dementia provides an opportunity for preventative treatment. Many older adults (30-60%) report specific subjective cognitive decline (SCD); however, previous research is inconsistent in terms of what types of complaints predict future cognitive decline. The purpose of this study is to identify which specific complaints from the Everyday Cognition Scales (ECog) scales, a measure of self-reported concerns for everyday abilities across six cognitive domains, are associated with: 1) conversion from a clinical diagnosis of normal to either MCI or dementia (categorical variable) and 2) progressive cognitive decline in memory and executive function (continuous variables). 415 cognitively normal older adults were monitored annually for an average of 5 years. Cox proportional hazards models were used to assess associations between self-reported ECog items and progression to impairment (MCI or dementia). A total of 114 individuals progressed to impairment; the mean time to progression was 4.9 years (SD=3.4 years, range=0.8-13.8). Follow-up models were run controlling for depression. A subset of individuals (n=352) underwent repeat cognitive assessments for an average of 5.3 years. For those individuals, mixed effects models with random intercepts and slopes were used to assess associations between ECog items and change in neuropsychological measures of episodic memory or executive function. Prior to controlling for depression, subjective concerns on five of the eight Everyday Memory items, three of the nine Everyday Language items, one of the seven Everyday Visuospatial items, two of the five Everyday Planning items, and one of the six Everyday Organization items were associated with subsequent diagnostic conversion (HR=1.25 to 1.59, p=0.003 to 0.03). However, after controlling for depression, only two specific complaints of remembering appointments, meetings, and engagements and understanding spoken directions and instructions were associated with subsequent diagnostic conversion. Episodic memory in individuals reporting no concern on ECog items did not significantly change over time (p>0.4). More complaints on seven of the eight Everyday Memory items, three of the nine Everyday Language items, and three of the seven Everyday Visuospatial items were associated with a decline in episodic memory (Interaction estimate=-0.055 to 0.001, p=0.003 to 0.04). Executive function in those reporting no concern on ECog items declined slightly (p <0.001 to 0.06). More complaints on three of the eight Everyday Memory items and three of the nine Everyday Language items were associated with a decline in executive function (Interaction estimate=-0.021 to -0.012, p=0.002 to 0.04). These findings suggest that specific complaints across several cognitive domains are associated with diagnostic conversion. Specific complaints in the domains of Everyday Memory and Language are associated with a decline in both episodic memory and executive function. Increased monitoring and treatment of individuals with these specific SCD may be warranted.

Keywords: alzheimer’s disease, dementia, memory complaints, mild cognitive impairment, risk factors, subjective cognitive decline

Procedia PDF Downloads 50

Authors: Kirsten A. Bartels

Abstract:

'Never again' and 'Lest we forget' have long been messages associated with the events of the Shoah. Yet as we attempt to learn from the past, we must find new ways to engage with its memories. The preservation of the culture and the value of tradition are critical factors in Jane Yolen's works of Holocaust fiction, The Devil's Arithmetic and Mapping the Bones, emphasized through the importance of remembering. That word, in its multitude of forms (remember, remembering, memories), occurs no less than ten times in the first four pages and over one hundred times in the one hundred and sixty-four-page narrative The Devil’s Arithmetic. While Yolen takes a different approach to showcasing the importance of memory in Mapping the Bones, it is of equal import in this work and arguably to the future of Holocaust knowing. The idea of remembering, the desire to remember, and the ability to remember, are explored in three divergent ways in The Devil’s Arithmetic. First, in the importance to remember a past which is not her own – to understand history or acquired memories. Second, in the protagonist's actual or initial memories, those of her life in modern-day New York. Third, in a reverse mode of forgetting and trying to reacquire that which has been lost -- as Hannah is processed in the camp and she forgets everything, all worlds prior to the camp are lost to her. As numbers replace names, Yolen stresses the importance of self-identity or owned memories. In addition, the importance of relaying memory, the transitions of memory from perspective, and the ideas of reflective telling are explored in Mapping the Bones -- through the telling of the story through the lens of one of the twins as the events are unfolding; and then the through the reflective telling from the lens of the other twin. Parallel to the exploration of the intersemiosis of memory is the discussion of literary shadows (foreshadowing, backshadowing, and side-shadowing) and their impact on the reader's experience with Yolen's narrative. For in this type of exploration, one cannot look at the events described in Yolen's work and not also contemplate the figurative shadows cast.

Keywords: holocaust literature, memory, narrative, Yolen

Procedia PDF Downloads 206

Authors: H. Ghodbane, A. A. Taleb, O. Kraa

Abstract:

This paper presents geometric design of induction heating system. The objective of this design is to improve the temperature distribution in the load. The study of such a device requires the use of models or modeling representation, physical, mathematical, and numerical. This modeling is the basis of the understanding, the design, and optimization of these systems. The optimization technique is to find values of variables that maximize or minimize the objective function.

Keywords: optimization, modeling, geometric design system, temperature increase

Procedia PDF Downloads 499

Authors: Abiodun Ladanu Ajala, Wuyi Oke

Abstract:

Mathematical simulation and optimization models packaged within interactive computer programs provide a common way for planners and managers to predict the behaviour of any proposed water resources system design or management policy before it is implemented. Modeling presents a principal technique of predicting the behaviour of the proposed infrastructural designs or management policies. Models can be developed and used to help identify specific alternative plans that best meet those objectives. This study discusses various types of models, their development, architecture, data requirements, and applications in the field of engineering. It also outlines the advantages and limitations of each the optimization and simulation models presented. The techniques explored in this review include; dynamic programming, linear programming, fuzzy optimization, evolutionary algorithms and finally artificial intelligence techniques. Previous studies carried out using some of the techniques mentioned above were reviewed, and most of the results from different researches showed that indeed optimization and simulation provides viable alternatives and predictions which form a basis for decision making in building engineering structures and also in engineering planning and management.

Keywords: linear programming, mutation, optimization, simulation

Procedia PDF Downloads 557

Authors: Pulak Swain, A. K. Ojha

Abstract:

Portfolio optimization is based on dealing with the problems of efficient asset allocation. Risk and Expected return are two conflicting criteria in such problems, where the investor prefers the return to be high and the risk to be low. Using multi-objective approach we can solve those type of problems. However the information which we have for the input parameters are generally ambiguous and the input values can fluctuate around some nominal values. We can not ignore the uncertainty in input values, as they can affect the asset allocation drastically. So we use Robust Optimization approach to the problems where the input parameters comes under box uncertainty. In this paper, we solve the multi criteria robust problem with the help of  E- constraint method.

Keywords: portfolio optimization, multi-objective optimization, ϵ - constraint method, box uncertainty, robust optimization

Procedia PDF Downloads 111

Authors: Susanta Kumar Gachhayat, S. K. Dash

Abstract:

Multi objective non-convex economic dispatch problems of a thermal power plant are of grave concern for deciding the cost of generation and reduction of emission level for diminishing the global warming level for improving green-house effect. This paper deals with ramp rate constraints for achieving better inequality constraints so as to incorporate valve point loading for cost of generation in thermal power plant through ramp rate biogeography based optimization involving mutation and migration. Through 50 out of 100 trials, the cost function and emission objective function were found to have outperformed other classical methods such as lambda iteration method, quadratic programming method and many heuristic methods like particle swarm optimization method, weight improved particle swarm optimization method, constriction factor based particle swarm optimization method, moderate random particle swarm optimization method etc. Ramp rate biogeography based optimization applications prove quite advantageous in solving non convex multi objective economic dispatch problems subjected to nonlinear loads that pollute the source giving rise to third harmonic distortions and other such disturbances.

Keywords: economic load dispatch, ELD, biogeography-based optimization, BBO, ramp rate biogeography-based optimization, RRBBO, valve-point loading, VPL

Procedia PDF Downloads 354

Authors: Osman Adiguzel

Abstract:

Shape memory effect is a peculiar property exhibited by certain alloy systems and based on martensitic transformation, and shape memory properties are closely related to the microstructures of the material. Shape memory effect is linked with martensitic transformation, which is a solid state phase transformation and occurs with the cooperative movement of atoms by means of lattice invariant shears on cooling from high-temperature parent phase. Lattice twinning and detwinning can be considered as elementary processes activated during the transformation. Thermally induced martensite occurs as martensite variants, in self-accommodating manner and consists of lattice twins. Also, this martensite is called the twinned martensite or multivariant martensite. Deformation of shape memory alloys in martensitic state proceeds through a martensite variant reorientation. The martensite variants turn into the reoriented single variants with deformation, and the reorientation process has great importance for the shape memory behavior. Copper based alloys exhibit this property in metastable β- phase region, which has DO3 –type ordered lattice in ternary case at high temperature, and these structures martensiticaly turn into the layered complex structures with lattice twinning mechanism, on cooling from high temperature parent phase region. The twinning occurs as martensite variants with lattice invariant shears in two opposite directions, <110 > -type directions on the {110}- type plane of austenite matrix. Lattice invariant shear is not uniform in copper based ternary alloys and gives rise to the formation of unusual layered structures, like 3R, 9R, or 18R depending on the stacking sequences on the close-packed planes of the ordered lattice. The unit cell and periodicity are completed through 18 atomic layers in case of 18R-structure. On the other hand, the deformed material recovers the original shape on heating above the austenite finish temperature. Meanwhile, the material returns to the twinned martensite structures (thermally induced martensite structure) in one way (irreversible) shape memory effect on cooling below the martensite finish temperature, whereas the material returns to the detwinned martensite structure (deformed martensite) in two-way (reversible) shape memory effect. Shortly one can say that the microstructural mechanisms, responsible for the shape memory effect are the twinning and detwinning processes as well as martensitic transformation. In the present contribution, x-ray diffraction, transmission electron microscopy (TEM) and differential scanning calorimetry (DSC) studies were carried out on two copper-based ternary alloys, CuZnAl, and CuAlMn.

Keywords: shape memory effect, martensitic transformation, twinning and detwinning, layered structures

Procedia PDF Downloads 403

Authors: Lev Bertovsky

Abstract:

The purpose of this study was to determine the reasons for the formation of false testimony from witnesses and make recommendations on the recognition of such cases. During the studies, which were based on the achievements of professionals in the field of psychology, as well as personal investigative practice, the stages of perception of the information were studied, as well as the process of its reclaim from the memory and transmission to the communicator upon request. Based on the principles of the human brain, kinds of conscientious witness mistakes were systematized. Proposals were formulated for the optimization of investigative actions in cases where the witnesses make an honest mistake with respect to the effects previously observed by them.

Keywords: criminology, eyewitness testimony, honest mistake, information, investigator, investigation, questioning

Procedia PDF Downloads 164

Authors: Dorottya Horváth, Tímea Harmath-Tánczos

Abstract:

Attention deficit hyperactivity disorder (ADHD) and learning disabilities are common neurocognitive disorders that can have a significant impact on a child's academic performance. ADHD is characterized by inattention, hyperactivity, and impulsivity, while learning disabilities are characterized by difficulty with specific academic skills, such as reading, writing, or math. The aim of this study was to investigate the working memory, executive, and attention functions of neurotypical children and children with ADHD and learning disabilities in order to fill the gaps in the Hungarian mean test scores of these cognitive functions in children with neurocognitive disorders. Another aim was to specify the neuropsychological differential diagnostic toolkit in terms of the relationships and peculiarities between these cognitive functions. The research question addressed in this study was: How do the working memory, executive, and attention functions of neurotypical children compare to those of children with ADHD and learning disabilities? A self-administered test battery was used as a research tool. Working memory was measured with the Non-Word Repetition Test, the Listening Span Test, the Digit Span Test, and the Reverse Digit Span Test; executive function with the Letter Fluency, Semantic Fluency, and Verb Fluency Tests; and attentional concentration with the d2-R Test. The data for this study was collected from 115 children aged 9-14 years. The children were divided into three groups: neurotypical children (n = 44), children with ADHD without learning disabilities (n = 23), and children with ADHD with learning disabilities (n = 48). The data was analyzed using a variety of statistical methods, including t-tests, ANOVAs, and correlational analyses. The results showed that the performance of children with neurocognitive involvement in working memory, executive functions, and attention was significantly lower than the performance of neurotypical children. However, the results of children with ADHD and ADHD with learning disabilities did not show a significant difference. The findings of this study are important because they provide new insights into the cognitive profiles of children with ADHD and learning disabilities and suggest that working memory, executive functions, and attention are all impaired in children with neurocognitive involvement, regardless of whether they have ADHD or learning disabilities. This information can be used to develop more effective diagnostic and treatment strategies for these disorders.

Keywords: ADHD, attention functions, executive functions, learning disabilities, working memory

Procedia PDF Downloads 54

Authors: Bhrugesh Radadiya, Jaydeep Shah

Abstract:

In Indian foundry industry, there is a need of defect free casting with minimum production cost in short lead time. Casting defect is a very large issue in foundry shop which increases the rejection rate of casting and wastage of materials. The various parameters influences on casting process such as mold machine related parameters, green sand related parameters, cast metal related parameters, mold related parameters and shake out related parameters. The mold related parameters are most influences on casting defects in sand casting process. This paper review the casting produced by foundry with shrinkage and blow holes as a major defects was analyzed and identified that mold related parameters such as mold temperature, pouring temperature and runner size were not properly set in sand casting process. These parameters were optimized using different optimization techniques such as Taguchi method, Response surface methodology, Genetic algorithm and Teaching-learning based optimization algorithm. Finally, concluded that a Teaching-learning based optimization algorithm give better result than other optimization techniques.

Keywords: casting defects, genetic algorithm, parametric optimization, Taguchi method, TLBO algorithm

Procedia PDF Downloads 701

Authors: I. Brandys, M. Levy, K. Harush, Y. Haim, M. Korngold

Abstract:

Theoretical optimization of a copper-water negative inclination heat pipe with internal composite wick structure has been performed, regarding a new introduced parameter: the ratio between the coarse mesh wraps and the fine mesh wraps of the composite wick. Since in many cases, the design of a heat pipe matches specific thermal requirements and physical limitations, this work demonstrates the optimization of a 1 m length, 8 mm internal diameter heat pipe without an adiabatic section, at a negative inclination angle of -10º. The optimization is based on a new introduced parameter, LR: the ratio between the coarse mesh wraps and the fine mesh wraps.

Keywords: heat pipe, inclination, optimization, ratio

Procedia PDF Downloads 299

Authors: Gong Zhilin, Jing Yang, Jian Yin

Abstract:

The purpose of this paper is to develop a novel system for credit card fraud detection based on sequential modeling of data using hybrid deep learning models. The projected model encapsulates five major phases are pre-processing, imbalance-data handling, feature extraction, optimal feature selection, and fraud detection with an ensemble classifier. The collected raw data (input) is pre-processed to enhance the quality of the data through alleviation of the missing data, noisy data as well as null values. The pre-processed data are class imbalanced in nature, and therefore they are handled effectively with the K-means clustering-based SMOTE model. From the balanced class data, the most relevant features like improved Principal Component Analysis (PCA), statistical features (mean, median, standard deviation) and higher-order statistical features (skewness and kurtosis). Among the extracted features, the most optimal features are selected with the Self-improved Arithmetic Optimization Algorithm (SI-AOA). This SI-AOA model is the conceptual improvement of the standard Arithmetic Optimization Algorithm. The deep learning models like Long Short-Term Memory (LSTM), Convolutional Neural Network (CNN), and optimized Quantum Deep Neural Network (QDNN). The LSTM and CNN are trained with the extracted optimal features. The outcomes from LSTM and CNN will enter as input to optimized QDNN that provides the final detection outcome. Since the QDNN is the ultimate detector, its weight function is fine-tuned with the Self-improved Arithmetic Optimization Algorithm (SI-AOA).

Keywords: credit card, data mining, fraud detection, money transactions

Procedia PDF Downloads 102

Authors: Vassilios Moussas, Dimos N. Pantazis, Panagioths Stratakis

Abstract:

The aim of this paper is to present the optimization methodology developed in the frame of a Coastal Transport Information System. The system will be used for the effective design of coastal transportation lines and incorporates subsystems that implement models, tools and techniques that may support the design of improved networks. The role of the optimization and decision subsystem is to provide the user with better and optimal scenarios that will best fulfill any constrains, goals or requirements posed. The complexity of the problem and the large number of parameters and objectives involved led to the adoption of an evolutionary method (Genetic Algorithms). The problem model and the subsystem structure are presented in detail, and, its support for simulation is also discussed.

Keywords: coastal transport, modeling, optimization

Procedia PDF Downloads 472

Authors: H. Nikzad, S. Yoshitomi

Abstract:

In this paper, an optimization procedure is applied for 3D Reinforced concrete building structure with shear wall.  In the optimization problem, cross sections of beams, columns and shear wall dimensions are considered as design variables and the optimal cross sections can be derived to minimize the total cost of the structure. As for final design application, the most suitable sections are selected to satisfy ACI 318-14 code provision based on static linear analysis. The validity of the method is examined through numerical example of 15 storied 3D RC building with shear wall.  This optimization method is expected to assist in providing a useful reference in design early stage, and to be an effective and powerful tool for structural design of RC shear wall structures.

Keywords: structural optimization, linear static analysis, ETABS, MATLAB, RC moment frame, RC shear wall structures

Procedia PDF Downloads 232

Authors: İrem Bulut, Mustafa Z. Söyük, Ertuğrul Yalçın, Simge Şişman-Bal

Abstract:

Eyewitness testimony is one of the most frequently used methods in criminal cases for the determination of crime and perpetrator. In the literature, the number of studies about the reliability of eyewitness testimony is increasing. The study aims to reveal the factors that affect the short-term and long-term visual memory performance of the participants in the event of an accident. In this context, the effect of the emotional content of the accident and the sounds during the accident on visual memory performance was investigated with eye-tracking. According to the results, the presence of visual and auditory stimuli with emotional content during the accident decreases the participants' both short-term and long-term recall performance. Moreover, the data obtained from the eye monitoring device showed that the participants had difficulty in answering even the questions they focused on at the time of the accident.

Keywords: eye tracking, eyewitness testimony, long-term recall, short-term recall, visual memory

Procedia PDF Downloads 128

Authors: Subodh Kumar, Amit Varde

Abstract:

Typical on-premises high-performance computing (HPC) environments consist of a fixed number and a fixed set of computing hardware. During the design of the HPC environment, the hardware components, including but not limited to CPU, Memory, GPU, and networking, are carefully chosen from select vendors for optimal performance. High capital cost for building the environment is a prime factor influencing the design environment. A class of software called “Job Schedulers” are critical to maximizing these resources and running multiple workloads to extract the maximum value for the high capital cost. In principle, schedulers work by preventing workloads and users from monopolizing the finite hardware resources by queuing jobs in a workload. A cloud-based HPC environment does not have the limitations of fixed (type of and quantity of) hardware resources. In theory, users and workloads could spin up any number and type of hardware resource. This paper discusses the limitations of using traditional scheduling algorithms for cloud-based HPC workloads. It proposes a new set of features, called “HPC optimizers,” for maximizing the benefits of the elasticity and scalability of the cloud with the goal of cost-performance optimization of the workload.

Keywords: high performance computing, HPC, cloud computing, optimization, schedulers

Procedia PDF Downloads 56

Authors: Joseph Bostick

Abstract:

A method of decreasing the heating load of HVAC systems in a single-dwelling model of a multifamily building, by controlling movable insulation through the optimization of flux, time, surface incident solar radiation, and temperature thresholds. Simulations are completed using a co-simulation between EnergyPlus and MATLAB as an optimization tool to find optimal control thresholds. Optimization of the control thresholds leads to a significant decrease in total heating energy expenditure.

Keywords: energy plus, MATLAB, simulation, energy efficiency

Procedia PDF Downloads 144

Authors: Abolfazl Hosseinpour, Javad Marzbanrad

Abstract:

In this research, the topology and shape optimization of a Macpherson control arm has been accomplished to achieve lighter weight. Present automotive market demands low cost and light weight component to meet the need of fuel efficient and cost effective vehicle. This in turn gives the rise to more effective use of materials for automotive parts which can reduce the mass of vehicle. Since automotive components are under dynamic loads which cause fatigue damage, considering fatigue criteria seems to be essential in designing automotive components. At first, in order to create severe loading condition for control arm, some rough roads are generated through power spectral density. Then, the most critical loading conditions are obtained through multibody dynamics analysis of a full vehicle model. Then, the topology optimization is performed based on fatigue life criterion using HyperMesh software, which resulted to 50 percent mass reduction. In the next step a CAD model is created using CATIA software and shape optimization is performed to achieve accurate dimensions with less mass.

Keywords: topology optimization, shape optimization, fatigue life, MacPherson control arm

Procedia PDF Downloads 289

Authors: Agarana Michael C., Akinlabi Esther T., Pule Kholopane

Abstract:

Innovation in manufacturing process technologies and associated product design affects the prospects for manufacturing today and in near future. In this study some theoretical methods, useful as tools in advanced manufacturing, are considered. In particular, some basic Mathematical, Operational Research, Heuristic, and Statistical techniques are discussed. These techniques/methods are very handy in many areas of advanced manufacturing processes, including process planning optimization, modelling and analysis. Generally the production rate requires the application of Mathematical methods. The Emerging Trends Processes in Advanced Manufacturing can be enhanced by using Mathematical Modelling and Optimization techniques.

Keywords: mathematical modelling, optimization, emerging trends, advanced manufacturing

Procedia PDF Downloads 262

Authors: Anastasia V. Kovaleva, Alena A. Ryabova, Vladimir N. Kasatkin

Abstract:

Background: The most simple form of entrainment to a sensory (typically auditory) rhythmic stimulus involves perceiving and synchronizing movements with an isochronous beat with one level of periodicity, such as that produced by a metronome. Children with pediatric cancer usually treated with chemo- and radiotherapy. Because of such treatment, psychologists and health professionals declare cognitive and motor abilities decline in cancer patients. The purpose of our study was to measure working memory characteristics with association with audio-motor synchronization tasks, also involved some memory resources, in children with different degrees of central nervous system lesions: posterior fossa tumors, acute lymphoblastic leukemia, and healthy controls. Methods: Our sample consisted of three groups of children: children treated for posterior fossa tumors (PFT-group, n=42, mean age 12.23), children treated for acute lymphoblastic leukemia (ALL-group, n=11, mean age 11.57) and neurologically healthy children (control group, n=36, mean age 11.67). Participants were tested for working memory characteristics with Cambridge Neuropsychological Test Automated Battery (CANTAB). Pattern recognition memory (PRM) and spatial working memory (SWM) tests were applied. Outcome measures of PRM test include the number and percentage of correct trials and latency (speed of participant’s response), and measures of SWM include errors, strategy, and latency. In the synchronization tests, the instruction was to tap out a regular beat (40, 60, 90 and 120 beats per minute) in synchrony with the rhythmic sequences that were played. This meant that for the sequences with an isochronous beat, participants were required to tap into every auditory event. Variations of inter-tap-intervals and deviations of children’s taps from the metronome were assessed. Results: Analysis of variance revealed the significant effect of group (ALL, PFT and control) on such parameters as short-term PRM, SWM strategy and errors. Healthy controls demonstrated more correctly retained elements, better working memory strategy, compared to cancer patients. Interestingly that ALL patients chose the bad strategy, but committed significantly less errors in SWM test then PFT and controls did. As to rhythmic ability, significant associations of working memory were found out only with 40 bpm rhythm: the less variable were inter-tap-intervals of the child, the more elements in memory he/she could retain. The ability to audio-motor synchronization may be related to working memory processes mediated by the prefrontal cortex whereby each sensory event is actively retrieved and monitored during rhythmic sequencing. Conclusion: Our results suggest that working memory, tested with appropriate cognitive methods, is associated with the ability to synchronize movements with rhythmic sounds, especially in sub-second intervals (40 per minute).

Keywords: acute lymphoblastic leukemia (ALL), audio-motor synchronization, posterior fossa tumor, working memory

Procedia PDF Downloads 277

Authors: Fuzhang Zhao

Abstract:

Particle swarm optimization (PSO) is becoming one of the most important swarm intelligent paradigms for solving global optimization problems. Although some progress has been made to improve PSO algorithms over the last two decades, additional work is still needed to balance parameters to achieve better numerical properties of accuracy, efficiency, and stability. In the optimal PSO algorithm, the optimal weightings of (√ 5 − 1)/2 and (3 − √5)/2 are used for the cognitive factor and the social factor, respectively. By the same token, the same optimal weightings have been applied for intensification searches and diversification searches, respectively. Perturbation and constriction effects are optimally balanced. Simulations of the de Jong, the Rosenbrock, and the Griewank functions show that the optimal PSO algorithm indeed achieves better numerical properties and outperforms the canonical PSO algorithm.

Keywords: diversification search, intensification search, optimal weighting, particle swarm optimization

Procedia PDF Downloads 545

Authors: Mohammed Jamal Al-Mansor, Kok Beng Gan

Abstract:

This paper develops an optimized embedding of payload in medical image by using genetic optimization. The goal is to preserve region of interest from being distorted because of the watermark. By using this developed system there is no need of manual defining of region of interest through experts as the system will apply the genetic optimization to select the parts of image that can carry the watermark with guaranteeing less distortion. The experimental results assure that genetic based optimization is useful for performing steganography with less mean square error percentage.

Keywords: AES, DWT, genetic algorithm, watermarking

Procedia PDF Downloads 382

Authors: Radhwan Yousif Sedik Al-Jawadi

Abstract:

Optimization is necessary for finding appropriate solutions to a range of real-life problems. In particular, genetic (or more generally, evolutionary) algorithms have proved very useful in solving many problems for which analytical solutions are not available. In this paper, we present an optimization algorithm called Dynamic Schema with Dissimilarity and Similarity of Chromosomes (DSDSC) which is a variant of the classical genetic algorithm. This approach constructs new chromosomes from a schema and pairs of existing ones by exploring their dissimilarities and similarities. To show the effectiveness of the algorithm, it is tested and compared with the classical GA, on 15 two-dimensional optimization problems taken from literature. We have found that, in most cases, our method is better than the classical genetic algorithm.

Keywords: chromosome injection, dynamic schema, genetic algorithm, similarity and dissimilarity

Procedia PDF Downloads 314

Authors: Rafi Ullah, Shah Muhammad Emaduddin, Taha Jilani

Abstract:

Vehicle Adhoc Networks (VANET) belongs to a special class of Mobile Adhoc Network (MANET) with high mobility. Network is created by road side vehicles equipped with communication devices like GPS and Wifi etc. Since the environment is highly dynamic due to difference in speed and high mobility of vehicles and weak stability of the network connection, it is a challenging task to design an efficient routing protocol for such an unstable environment. Our proposed algorithm uses heuristic for the calculation of optimal path for routing the packet efficiently in collaboration with several other parameters like geographical location, speed, priority, the distance among the vehicles, communication range, and networks congestion. We have incorporated probabilistic, heuristic and machine learning based approach inconsistency with the relay function of the memory buffer to keep the packet moving towards the destination. These parameters when used in collaboration provide us a very strong and admissible heuristics. We have mathematically proved that the proposed technique is efficient for the routing of packets, especially in a medical emergency situation. These networks can be used for medical emergency, security, entertainment and routing purposes.

Keywords: heuristics routing, intelligent routing, VANET, route optimization

Procedia PDF Downloads 148