Search results for: Intelligent living space.

Authors: Weiming Hu, Xu Li, Xiaonan Li, Zhong Xu, Li Yuan, Xuan Dong

Abstract:

Maneuver decision-making plays a critical role in high-performance intelligent driving. This paper proposes a risk assessment-based decision-making network (RADMN) to address the problem of driving strategy for the commercial vehicle. RADMN integrates two networks, aiming at identifying the risk degree of collision and rollover and providing decisions to ensure the effectiveness and reliability of driving strategy. In the risk assessment module, risk degrees of the backward collision, forward collision and rollover are quantified for hazard recognition. In the decision module, a deep reinforcement learning based on multi-objective optimization (DRL-MOO) algorithm is designed, which comprehensively considers the risk degree and motion states of each traffic participant. To evaluate the performance of the proposed framework, Prescan/Simulink joint simulation was conducted in highway scenarios. Experimental results validate the effectiveness and reliability of the proposed RADMN. The output driving strategy can guarantee the safety and provide key technical support for the realization of autonomous driving of commercial vehicles.

Keywords: Decision-making strategy, risk assessment, multi-objective optimization, commercial vehicle.

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Authors: Muchiri Josephine, Qdero Agnes

Abstract:

The current study was conducted during the coronavirus pandemic (COVID-19) period, soon after the lifting of the lockdown measures and schools had just re-opened. It investigated the sociodemographic correlates of Post-Traumatic Stress Disorder (PTSD) among adolescents (13-18 years) who had undergone domestic violence (DV) in Kajiado County, Kenya. The adolescents were administered a sociodemographic questionnaire to ascertain the forms of DV experienced, and those who met the criteria were assessed for the presence of PTSD using the Harvard Trauma Questionnaire (HTQ). Overall, 93 (90.3%) had experienced DV, and 57 (61.3%) had PTSD; where the severity and prevalence of PTSD increased with increased age, and it also increased significantly among those in higher academic levels, indicating that PTSD prevalence was chronic and additionally influenced by increased academic pressure. Social connections seemed to mitigate PTSD prevalence, whereas, regarding the family background, those living with guardians seemed to have more severe PTSD.

Keywords: Age, education level, gender, post-traumatic stress disorder.

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Authors: Kazuki Sonoda, Masahiro Hori

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When designing information systems that deal with large amount of domain knowledge, system designers need to consider ambiguities of labeling termsin domain vocabulary for navigating users in the information space. The goal of this study is to develop a methodology for system designers to label navigation items, taking account of ambiguities stems from synonyms or polysemes of labeling terms. In this paper, we propose a method for concept labeling based on mappings between domain ontology andthesaurus, and report results of an empirical evaluation.

Keywords: Concept Labeling, Ontology, Thesaurus, VocabularyProblem

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Authors: Safae El Alaoui, Mohamed Ouzahra

Abstract:

In this work, we investigate the exponential stability of a linear system described by x˙ (t) = Ax(t) − ρBx(t). Here, A generates a semigroup S(t) on a Hilbert space, the operator B is supposed to be of Desch-Schappacher type, which makes the investigation more interesting in many applications. The case of Miyadera-Voigt perturbations is also considered. Sufficient conditions are formulated in terms of admissibility and observability inequalities and the approach is based on some energy estimates. Finally, the obtained results are applied to prove the uniform exponential stabilization of bilinear partial differential equations.

Keywords: Exponential stabilization, unbounded operator, Desch-Schappacher, Miyadera-Voigt operator.

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Authors: T.C. Manjunath,

Abstract:

This paper features the trajectory planning design of a indigenously developed 4-Axis SCARA robot which is used for doing successful robotic manipulation task in the laboratory. Once, a trajectory is being designed and given as input to the robot, the robot's gripper tip moves along that specified trajectory. Trajectories have to be designed in the work space only. The main idea of this paper is to design a continuous path trajectory model for the indigenously developed SCARA robot arm during its maneuvering from one point to another point (during pick and place operations) in a workspace avoiding all the obstacles in its path of motion.

Keywords: SCARA, Trajectory, Planning.

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Authors: Md. Ashikur Rahman Khan, M. M. Rahman, K. Kadirgama

Abstract:

Artificial neural networks (ANN) are used in distinct researching fields and professions, and are prepared by cooperation of scientists in different fields such as computer engineering, electronic, structure, biology and so many different branches of science. Many models are built correlating the parameters and the outputs in electrical discharge machining (EDM) concern for different types of materials. Up till now model for Ti-5Al-2.5Sn alloy in the case of electrical discharge machining performance characteristics has not been developed. Therefore, in the present work, it is attempted to generate a model of material removal rate (MRR) for Ti-5Al-2.5Sn material by means of Artificial Neural Network. The experimentation is performed according to the design of experiment (DOE) of response surface methodology (RSM). To generate the DOE four parameters such as peak current, pulse on time, pulse off time and servo voltage and one output as MRR are considered. Ti-5Al-2.5Sn alloy is machined with positive polarity of copper electrode. Finally the developed model is tested with confirmation test. The confirmation test yields an error as within the agreeable limit. To investigate the effect of the parameters on performance sensitivity analysis is also carried out which reveals that the peak current having more effect on EDM performance.

Keywords: Ti-5Al-2.5Sn, material removal rate, copper tungsten, positive polarity, artificial neural network, multi-layer perceptron.

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Authors: Xijian Wang

Abstract:

This paper is concerned with the numerical minimization of energy functionals in BV ( ) (the space of bounded variation functions) involving total variation for gray-scale 1-dimensional inpainting problem. Applications are shown by finite element method and discontinuous Galerkin method for total variation minimization. We include the numerical examples which show the different recovery image by these two methods.

Keywords: finite element method, discontinuous Galerkin method, total variation minimization, inpainting

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Authors: Joan Goh, Ahmad Abd. Majid, Ahmad Izani Md. Ismail

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In this paper, collocation based cubic B-spline and extended cubic uniform B-spline method are considered for solving one-dimensional heat equation with a nonlocal initial condition. Finite difference and θ-weighted scheme is used for time and space discretization respectively. The stability of the method is analyzed by the Von Neumann method. Accuracy of the methods is illustrated with an example. The numerical results are obtained and compared with the analytical solutions.

Keywords: Heat equation, Collocation based, Cubic Bspline, Extended cubic uniform B-spline.

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Authors: Tuğrul Varol, Halil Barış Özel

Abstract:

In this study which has been conducted in Akçasu Forest Range District of Devrek Forest Directorate; 3 methods (weed control with labourer power, cover removal with Hitachi F20 Excavator, and weed control with agricultural equipment mounted on a Ferguson 240S agriculture tractor) were utilized in weed control efforts in regeneration of degraded oriental beech forests have been compared. In this respect, 3 methods have been compared by determining certain work hours and standard durations of unit areas (1 hectare). For this purpose, evaluating the tasks made with human and machine force from the aspects of duration, productivity and costs, it has been aimed to determine the most productive method in accordance with the actual ecological conditions of research field. Within the scope of the study, the time studies have been conducted for 3 methods used in weed control efforts. While carrying out those studies, the performed implementations have been evaluated by dividing them into business stages. Also, the actual data have been used while calculating the cost accounts. In those calculations, the latest formulas and equations which are also used in developed countries have been utilized. The variance of analysis (ANOVA) was used in order to determine whether there is any statistically significant difference among obtained results, and the Duncan test was used for grouping if there is significant difference. According to the measurements and findings carried out within the scope of this study, it has been found during living cover removal efforts in regeneration efforts in demolished oriental beech forests that the removal of weed layer in 1 hectare of field has taken 920 hours with labourer force, 15.1 hours with excavator and 60 hours with an equipment mounted on a tractor. On the other hand, it has been determined that the cost of removal of living cover in unit area (1 hectare) was 3220.00 TL for labourer power, 1250 TL for excavator and 1825 TL for equipment mounted on a tractor. According to the obtained results, it has been found that the utilization of excavator in weed control effort in regeneration of degraded oriental beech regions under actual ecological conditions of research field has been found to be more productive from both of aspects of duration and costs. These determinations carried out should be repeated in weed control efforts in degraded forest fields with different ecological conditions, it is compulsory for finding the most efficient weed control method. These findings will light the way of technical staff of forestry directorate in determination of the most effective and economic weed control method. Thus, the more actual data will be used while preparing the weed control budgets, and there will be significant contributions to national economy. Also the results of this and similar studies are very important for developing the policies for our forestry in short and long term.

Keywords: Artificial regeneration, weed control, oriental beech, productivity, mechanization, man power, cost analysis.

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Authors: Heba Mohammed Nagy, Walid Mohamed Aly, Osama Fathy Hegazy

Abstract:

Educational  data mining  is  a  specific  data   mining field applied to data originating from educational environments, it relies on different  approaches to discover hidden knowledge  from  the  available   data. Among these approaches are   machine   learning techniques which are used to build a system that acquires learning from previous data. Machine learning can be applied to solve different regression, classification, clustering and optimization problems.

In  our  research, we propose  a “Student  Advisory  Framework” that  utilizes  classification  and  clustering  to  build  an  intelligent system. This system can be used to provide pieces of consultations to a first year  university  student to  pursue a  certain   education   track   where  he/she  will  likely  succeed  in, aiming  to  decrease   the  high  rate   of  academic  failure   among these  students.  A real case study  in Cairo  Higher  Institute  for Engineering, Computer  Science  and  Management  is  presented using  real  dataset   collected  from  2000−2012.The dataset has two main components: pre-higher education dataset and first year courses results dataset. Results have proved the efficiency of the suggested framework.

Keywords: Classification, Clustering, Educational Data Mining (EDM), Machine Learning.

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Authors: N. Singh, N. Sharma, J. K. Katnoria

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Water a vital component for all living forms is derived from variety of sources, including surface water (rivers, lakes, reservoirs and ponds) and ground water (aquifers). Over the years of time, water bodies are subjected to human interference regularly resulting in deterioration of water quality. Therefore, pollution of water bodies has become matter of global concern. As the water quality closely relate to human health, water analysis before usage is of immense importance. Improper management of water bodies can cause serious problems in availability and quality of water. The quality of water may be described according to their physico-chemical and microbiological characteristics. For effective maintenance of water quality through appropriate control measures, continuous monitoring of metals, physico-chemical and biological parameter is essential for the establishment of baseline data for the water quality in any study area. The present study has focused on to explore the status of water pollution in various areas and to estimate the magnitude of its toxicity using different bioassay.

Keywords: Genotoxicity, Heavy metals, Mutagenicity, Physico-chemical analysis.

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Authors: Yilun Shang

Abstract:

We study a long-range percolation model in the hierarchical lattice ΩN of order N where probability of connection between two nodes separated by distance k is of the form min{αβ−k, 1}, α ≥ 0 and β > 0. The parameter α is the percolation parameter, while β describes the long-range nature of the model. The ΩN is an example of so called ultrametric space, which has remarkable qualitative difference between Euclidean-type lattices. In this paper, we characterize the sizes of large clusters for this model along the line of some prior work. The proof involves a stationary embedding of ΩN into Z. The phase diagram of this long-range percolation is well understood.

Keywords: percolation, component, hierarchical lattice, phase transition.

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Authors: Akbar Seraly, Kazbek Primbetov, Gulmira Abdiraiymova, Gulnapis Abdikerova

Abstract:

the article analyzes the development prospects of education system in Kazakhstan. Education is among key sources of culture and social mobility. Modern education must become civic which means availability of high quality education to all people irrespective of their racial, ethnic, religious, social, gender and any other differences. Socially focused nature of modernization of Kazakhstan-s society is predicated upon formation of a civic education model in the future. Kazakhstan-s education system undergoes intensive reforms first of all intended to achieve international education standards and integration into the global educational and information space.

Keywords: Education system, Kazakhstan , Modernization

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Authors: Suhadiyana Hanapi, Alhassan Salami Tijani, W. A. N Wan Mohamed

Abstract:

In this paper, a prototype PEM fuel cell vehicle integrated with a 1 kW air-blowing proton exchange membrane fuel cell (PEMFC) stack as a main power sources has been developed for a lightweight cruising vehicle. The test vehicle is equipped with a PEM fuel cell system that provides electric power to a brushed DC motor. This vehicle was designed to compete with industrial lightweight vehicle with the target of consuming least amount of energy and high performance. Individual variations in driving style have a significant impact on vehicle energy efficiency and it is well established from the literature. The primary aim of this study was to assesses the power and fuel consumption of a hydrogen fuel cell vehicle operating at three difference driving technique (i.e. 25 km/h constant speed, 22-28 km/h speed range, 20-30 km/h speed range). The goal is to develop the best driving strategy to maximize performance and minimize fuel consumption for the vehicle system. The relationship between power demand and hydrogen consumption has also been discussed. All the techniques can be evaluated and compared on broadly similar terms. Automatic intelligent controller for driving prototype fuel cell vehicle on different obstacle while maintaining all systems at maximum efficiency was used. The result showed that 25 km/h constant speed was identified for optimal driving with less fuel consumption.

Keywords: Prototype fuel cell electric vehicles, energy efficient, control/driving technique, fuel economy.

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Authors: Khalid Ali, Manar Jammal

Abstract:

In order to meet the stringent latency and reliability requirements of the upcoming 5G networks, Open Radio Access Networks (O-RAN) have been proposed. The virtualization of O-RAN has allowed it to be treated as a Network Function Virtualization (NFV) architecture, while its components are considered Virtualized Network Functions (VNFs). Hence, intelligent Machine Learning (ML) based solutions can be utilized to apply different resource management and allocation techniques on O-RAN. However, intelligently allocating resources for O-RAN VNFs can prove challenging due to the dynamicity of traffic in mobile networks. Network providers need to dynamically scale the allocated resources in response to the incoming traffic. Elastically allocating resources can provide a higher level of flexibility in the network in addition to reducing the OPerational EXpenditure (OPEX) and increasing the resources utilization. Most of the existing elastic solutions are reactive in nature, despite the fact that proactive approaches are more agile since they scale instances ahead of time by predicting the incoming traffic. In this work, we propose and evaluate traffic forecasting models based on the ML algorithm. The algorithms aim at predicting future O-RAN traffic by using previous traffic data. Detailed analysis of the traffic data was carried out to validate the quality and applicability of the traffic dataset. Hence, two ML models were proposed and evaluated based on their prediction capabilities.

Keywords: O-RAN, traffic forecasting, NFV, ARIMA, LSTM, elasticity.

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Authors: Dimitrios Ntardas, Alexandros Tzanetos, Georgios Dounias

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High Voltage Substations (HVS) are the intermediate step between production of power and successfully transmitting it to clients, making them one of the most important checkpoints in power grids. Nowadays - renewable resources and consequently distributed generation are growing fast, the construction of HVS is of high importance both in terms of quality and time completion so that new energy producers can quickly and safely intergrade in power grids. The resources needed, such as machines and workers, should be carefully allocated so that the construction of a HVS is completed on time, with the lowest possible cost (e.g. not spending additional cost that were not taken into consideration, because of project delays), but in the highest quality. In addition, there are milestones and several checkpoints to be precisely achieved during construction to ensure the cost and timeline control and to ensure that the percentage of governmental funding will be granted. The management of such a demanding project is a NP-hard problem that consists of prerequisite constraints and resource limits for each task of the project. In this work, a hybrid meta-heuristic method is implemented to solve this problem. Meta-heuristics have been proven to be quite useful when dealing with high-dimensional constraint optimization problems. Hybridization of them results in boost of their performance.

Keywords: High voltage substations, nature-inspired algorithms, project management, meta-heuristics.

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Authors: Patrycja J. Haupt

Abstract:

Today we tend to go back to the past to our root relation to nature. Therefore in search of friendly spaces there are elements of natural environment introduced as elements of spatial composition. Though reinvented through the use of the new substance such as greenery, water etc. made possible by state of the art technologies, still, in principal, they remain the same. As a result, sustainable design, based upon the recognized means of composition in addition to the relation of architecture and urbanism vs. nature introduces a new aesthetical values into architectural and urban space.

Keywords: architectural composition, biodiversity, elements of composition, green architecture, sustainable design, urban composition, water management.

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Authors: Ashly Joseph

Abstract:

Cloud computing has become an essential component of enterprises and organizations globally in the current era of digital technology. The cloud has a multitude of advantages, including scalability, flexibility, and cost-effectiveness, rendering it an appealing choice for data storage and processing. The increasing storage of sensitive information in cloud environments has raised significant concerns over the security of such systems. The frequency of cyber threats and attacks specifically aimed at cloud infrastructure has been increasing, presenting substantial dangers to the data, reputation, and financial stability of enterprises. Conventional security methods can become inadequate when confronted with ever intricate and dynamic threats. Artificial Intelligence (AI) technologies possess the capacity to significantly transform cloud security through their ability to promptly identify and thwart assaults, adjust to emerging risks, and offer intelligent perspectives for proactive security actions. The objective of this research study is to investigate the utilization of AI technologies in augmenting the security measures within cloud computing systems. This paper aims to offer significant insights and recommendations for businesses seeking to protect their cloud-based assets by analyzing the present state of cloud security, the capabilities of AI, and the possible advantages and obstacles associated with using AI into cloud security policies.

Keywords: Machine Learning, Natural Learning Processing, Denial-of-Service attacks, Sentiment Analysis, Cloud computing.

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Authors: R.L. Sanders, L. McKeown

Abstract:

An international cooperation between educators in Australia and the US has led to a reconceptualization of the teaching of a library science course at Appalachian State University. The pedagogy of Action Learning coupled with a 3D virtual learning environment immerses students in a social constructivist learning space that incorporates and supports interaction and reflection. The intent of this study was to build a bridge between theory and practice by providing students with a tool set that promoted personal and social reflection, and created and scaffolded a community of practice. Besides, action learning is an educational process whereby the fifty graduate students experienced their own actions and experience to improve performance.

Keywords: action learning, action research, reflection, metacognition, virtual worlds

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Authors: Yiannis G. Smirlis

Abstract:

The classification and the prediction of efficiencies in Data Envelopment Analysis (DEA) is an important issue, especially in large scale problems or when new units frequently enter the under-assessment set. In this paper, we contribute to the subject by proposing a grid structure based on interval segmentations of the range of values for the inputs and outputs. Such intervals combined, define hyper-rectangles that partition the space of the problem. This structure, exploited by Interval DEA models and a dominance relation, acts as a DEA pre-processor, enabling the classification and prediction of efficiency scores, without applying any DEA models.

Keywords: Data envelopment analysis, interval DEA, efficiency classification, efficiency prediction.

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Authors: Azam Anaraki Firooz, Ali Reza Mahjoub, Reza Donyaei Ziba

Abstract:

A simple and dexterous in situ method was introduced to load CdS nanocrystals into organofunctionalized mesoporous, which used an ion-exchange method. The products were extensively characterized by combined spectroscopic methods. X- ray diffraction (XRD) and high-resolution transmission electron microscopy (HRTEM) demonstrated both the maintenance of pore symmetry (space group p6mm) of SBA-15 and the presence of CdS nanocrystals with uniform sizes of about 6 - 8 nm inside the functionalized SBA-15 channels. These mesoporous silica-supported CdS composites showed room temperature photoluminescence properties with a blue shift, indicating the quantum size effect of nanocrystalline CdS.

Keywords: Semiconductors, luminescence, mesoporous material, CdS.

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Authors: Taylan Kabbani, Ekrem Duman

Abstract:

Deep Reinforcement Learning (DRL) algorithms can scale to previously intractable problems. The automation of profit generation in the stock market is possible using DRL, by combining  the financial assets price ”prediction” step and the ”allocation” step of the portfolio in one unified process to produce fully autonomous systems capable of interacting with its environment to make optimal decisions through trial and error. This work represents a DRL model to generate profitable trades in the stock market, effectively overcoming the limitations of supervised learning approaches. We formulate the trading problem as a Partially observed Markov Decision Process (POMDP) model, considering the constraints imposed by the stock market, such as liquidity and transaction costs. We then solved the formulated POMDP problem using the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm and achieved a 2.68 Sharpe ratio on the test dataset. From the point of view of stock market forecasting and the intelligent decision-making mechanism, this paper demonstrates the superiority of DRL in financial markets over other types of machine learning and proves its credibility and advantages of strategic decision-making.

Keywords: Autonomous agent, deep reinforcement learning, MDP, sentiment analysis, stock market, technical indicators, twin delayed deep deterministic policy gradient.

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Authors: Ilze Stokmane

Abstract:

Economic processes underway in the country directly and indirectly affect the welfare of the people and the social environment, starting with job security and having a direct impact on the qualitative and safe living environment.

The paper describes existing situation and gives analysis of the regional development policy determination and implementation in the all three Baltic countries. According statistical indicators there are differences between implementation of the regional development activities between all Baltic countries and in regions of inside each country.

It is analyzed more detail differences between regions in Latvia, Lithuania and Estonia according possibility to evaluate success of development processes in regions of the Baltic countries. The descriptive analyze of documents, statistical indicators at national level and regional level were used in the research.

Keywords: Baltic countries, city environment, regional development, urban areas.

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Authors: Xun Ge, Jinjin Li, Ying Ge

Abstract:

Adopting Zakowski-s upper approximation operator C and lower approximation operator C, this paper investigates granularity-wise separations in covering approximation spaces. Some characterizations of granularity-wise separations are obtained by means of Pawlak rough sets and some relations among granularitywise separations are established, which makes it possible to research covering approximation spaces by logical methods and mathematical methods in computer science. Results of this paper give further applications of Pawlak rough set theory in pattern recognition and artificial intelligence.

Keywords: Rough set, covering approximation space, granularitywise separation.

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Authors: Hyung-Nam Kim, Won-Yong Chae, Dong-Sul Shin, Ho-Sung Kim, Hee-Je Kim

Abstract:

A wireless power transfer system can attribute to the fields in robot, aviation and space in which lightening the weight of device and improving the movement play an important role. A wireless power transfer system was investigated to overcome the inconvenience of using power cable. Especially a wireless power transfer technology is important element for mobile robots. We proposed the wireless power transfer system of the half-bridge resonant converter with the frequency tracking and optimized power transfer control unit. And the possibility of the application and development system was verified through the experiment with LED loads.

Keywords: Wireless Power Transmission (WPT), resonancefrequency, protection circuit. LED.

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Authors: Li Xiguang

Abstract:

In this paper, by constructing a special operator and using fixed point index theorem of cone, we get the sufficient conditions for symmetric positive solution of a class of nonlinear singular boundary value problems with p-Laplace operator, which improved and generalized the result of related paper.

Keywords: Banach space, cone, fixed point index, singular differential equation, p-Laplace operator, symmetric solutions.

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Authors: Hidehiko Okada, Yuki Fujii

Abstract:

Researchers have been applying artificial/ computational intelligence (AI/CI) methods to computer games. In this research field, further researchesare required to compare AI/CI methods with respect to each game application. In thispaper, we report our experimental result on the comparison of evolution strategy, genetic algorithm and their hybrids, applied to evolving controller agents for MarioAI. GA revealed its advantage in our experiment, whereas the expected ability of ES in exploiting (fine-tuning) solutions was not clearly observed. The blend crossover operator and the mutation operator of GA might contribute well to explore the vast search space.

Keywords: Evolutionary algorithm, autonomous game controller agent, neuroevolutions, MarioAI

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Authors: Sunitha Ramanujam, Hany El Yamany, Miriam A. M. Capretz

Abstract:

Software reliability, defined as the probability of a software system or application functioning without failure or errors over a defined period of time, has been an important area of research for over three decades. Several research efforts aimed at developing models to improve reliability are currently underway. One of the most popular approaches to software reliability adopted by some of these research efforts involves the use of operational profiles to predict how software applications will be used. Operational profiles are a quantification of usage patterns for a software application. The research presented in this paper investigates an innovative multiagent framework for automatic creation and management of operational profiles for generic distributed systems after their release into the market. The architecture of the proposed Operational Profile MAS (Multi-Agent System) is presented along with detailed descriptions of the various models arrived at following the analysis and design phases of the proposed system. The operational profile in this paper is extended to comprise seven different profiles. Further, the criticality of operations is defined using a new composed metrics in order to organize the testing process as well as to decrease the time and cost involved in this process. A prototype implementation of the proposed MAS is included as proof-of-concept and the framework is considered as a step towards making distributed systems intelligent and self-managing.

Keywords: Software reliability, Software testing, Metrics, Distributed systems, Multi-agent systems

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Authors: T. Ahmed, Z. Butt, M. Ali, S. Attiq, M. Ali

Abstract:

A series of Ti based shape memory alloys with composition of Ti50Ni49Cr1, Ti50Ni47Cr3 and Ti50Ni45Cr5 were developed by vacuum arc-melting under a purified argon atmosphere. The histometric and corrosion evaluation of Ti-Ni-Cr shape memory alloys have been considered in this research work. The alloys were developed by vacuum arc melting and implanted subcutaneously in rabbits for 4, 8 and 12 weeks. Metallic implants were embedded in order to determine the outcome of implantation on histometric and corrosion evaluation of Ti-Ni-Cr metallic strips. Encapsulating membrane formation around the alloys was minimal in the case of all materials. After histomorphometric analyses it was possible to demonstrate that there were no statistically significant differences between the materials. Corrosion rate was also determined in this study which is within acceptable range. The results showed the Ti- Ni-Cr alloy was neither cytotoxic, nor have any systemic reaction on living system in any of the test performed. Implantation shows good compatibility and a potential of being used directly in vivo system.

Keywords: Shape memory alloy, Ti-Ni-Fe, histomorphometric, corrosion.

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Authors: Dongsu Wu, Hongbin Gu

Abstract:

A motion protection system is designed for a parallel motion platform with subsided cabin. Due to its complex structure, parallel mechanism is easy to encounter interference problems including link length limits, joints limits and self-collision. Thus a virtual spring algorithm in operational space is developed for the motion protection system to avoid potential damages caused by interference. Simulation results show that the proposed motion protection system can effectively eliminate interference problems and ensure safety of the whole motion platform.

Keywords: Motion protection, motion platform, parallelmechanism, Stewart platform, collision avoidance.

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