Search results for: Liouville-type problem

Authors: Ondrej Lufinka, Jan Kaderabek, Juraj Prstek, Jiri Skala, Kamil Kosturik

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This paper deals with the problem of using Autonomous Robotic Platforms (ARP) for the ADAS (Advanced Driver Assistance Systems) testing in automotive. There are different possibilities of the testing already in development, and lately, the autonomous robotic platforms are beginning to be used more and more widely. Autonomous Robotic Platform discussed in this paper explores the hardware and software design possibilities related to the field of embedded systems. The paper focuses on its chapters on the introduction of the problem in general; then, it describes the proposed prototype concept and its principles from the embedded HW and SW point of view. It talks about the key features that can be used for the innovation of these platforms (e.g., modularity, omnidirectional movement, common and non-traditional sensors used for localization, synchronization of more platforms and cars together, or safety mechanisms). In the end, the future possible development of the project is discussed as well.

Keywords: advanced driver assistance systems, ADAS, autonomous robotic platform, embedded systems, hardware, localization, modularity, multiple robots synchronization, omnidirectional movement, safety mechanisms, software

Procedia PDF Downloads 143

Authors: Niousha Bagheri Khulenjani, Mohammad Saniee Abadeh

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Learning from very big datasets is a significant problem for most present data mining and machine learning algorithms. MicroRNA (miRNA) is one of the important big genomic and non-coding datasets presenting the genome sequences. In this paper, a hybrid method for the classification of the miRNA data is proposed. Due to the variety of cancers and high number of genes, analyzing the miRNA dataset has been a challenging problem for researchers. The number of features corresponding to the number of samples is high and the data suffer from being imbalanced. The feature selection method has been used to select features having more ability to distinguish classes and eliminating obscures features. Afterward, a Convolutional Neural Network (CNN) classifier for classification of cancer types is utilized, which employs a Genetic Algorithm to highlight optimized hyper-parameters of CNN. In order to make the process of classification by CNN faster, Graphics Processing Unit (GPU) is recommended for calculating the mathematic equation in a parallel way. The proposed method is tested on a real-world dataset with 8,129 patients, 29 different types of tumors, and 1,046 miRNA biomarkers, taken from The Cancer Genome Atlas (TCGA) database.

Keywords: cancer classification, feature selection, deep learning, genetic algorithm

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Authors: Cheng-Jhe Lee, Chiun-Chieh Hsu

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Due to the rapid development of the Internet and the increased availability of digital documents, the excessive information on the Internet has led to information overflow problem. In order to solve these problems for effective information retrieval, document clustering in text mining becomes a popular research topic. Clustering is the unsupervised classification of data items into groups without the need of training data. Many conventional document clustering methods perform inefficiently for large document collections because they were originally designed for relational database. Therefore they are impractical in real-world document clustering and require special handling for high dimensionality and high volume. We propose the FIHC (Frequent Itemset-based Hierarchical Clustering) method, which is a hierarchical clustering method developed for document clustering, where the intuition of FIHC is that there exist some common words for each cluster. FIHC uses such words to cluster documents and builds hierarchical topic tree. In this paper, we combine FIHC algorithm with ontology to solve the semantic problem and mine the meaning behind the words in documents. Furthermore, we use the closed frequent itemsets instead of only use frequent itemsets, which increases efficiency and scalability. The experimental results show that our method is more accurate than those of well-known document clustering algorithms.

Keywords: FIHC, documents clustering, ontology, closed frequent itemset

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Authors: Gak-Gyu Kim, Won Il Jung

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According to a remarkable development of science and technology, function and role of the system of engineering fields has recently been diversified. The system has become increasingly more complex and precise, and thus, system designers intended to maximize reliability concentrate more effort at the design stage. This study deals with the reliability redundancy optimization problem (RROP) for k-out-of-n: G system configuration with cold standby and warm standby components. This paper further intends to present the optimal mathematical model through which the following three elements of (i) multiple components choices, (ii) redundant components quantity and (iii) the choice of redundancy strategies may be combined in order to maximize the reliability of the system. Therefore, we focus on the following three issues. First, we consider RROP that there exists warm standby state as well as cold standby state of the component. Second, as eliminating an approximation approach of the previous RROP studies, we construct a precise model for system reliability. Third, given transition time when the state of components changes, we present not simply a workable solution but the advanced method. For the wide applicability of RROPs, moreover, we use absorbing continuous time Markov chain and matrix analytic methods in the suggested mathematical model.

Keywords: RROP, matrix analytic methods, k-out-of-n: G system, MTTF, absorbing continuous time Markov Chain

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Authors: Aniket Ganvir, Ritarani Sahu, Suchismita Chinara

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The rapid digitization of various aspects of life is leading to the creation of smart IoT ecosystems, where interconnected devices generate significant amounts of valuable data. However, these IoT devices face constraints such as limited computational resources and bandwidth. Cloud computing emerges as a solution by offering ample resources for offloading tasks efficiently despite introducing latency issues, especially for time-sensitive applications like fog computing. Fog computing (FC) addresses latency concerns by bringing computation and storage closer to the network edge, minimizing data travel distance, and enhancing efficiency. Offloading tasks to fog nodes or the cloud can conserve energy and extend IoT device lifespan. The offloading process is intricate, with tasks categorized as full or partial, and its optimization presents an NP-hard problem. Traditional greedy search methods struggle to address the complexity of task offloading efficiently. To overcome this, the efficient crow search algorithm (ECSA) has been proposed as a meta-heuristic optimization algorithm. ECSA aims to effectively optimize computation offloading, providing solutions to this challenging problem.

Keywords: IoT, fog computing, task offloading, efficient crow search algorithm

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Authors: Shaukat Ali Shahee, Usha Ananthakumar

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A data set exhibits class imbalance problem when one class has very few examples compared to the other class, and this is also referred to as between class imbalance. The traditional classifiers fail to classify the minority class examples correctly due to its bias towards the majority class. Apart from between-class imbalance, imbalance within classes where classes are composed of a different number of sub-clusters with these sub-clusters containing different number of examples also deteriorates the performance of the classifier. Previously, many methods have been proposed for handling imbalanced dataset problem. These methods can be classified into four categories: data preprocessing, algorithmic based, cost-based methods and ensemble of classifier. Data preprocessing techniques have shown great potential as they attempt to improve data distribution rather than the classifier. Data preprocessing technique handles class imbalance either by increasing the minority class examples or by decreasing the majority class examples. Decreasing the majority class examples lead to loss of information and also when minority class has an absolute rarity, removing the majority class examples is generally not recommended. Existing methods available for handling class imbalance do not address both between-class imbalance and within-class imbalance simultaneously. In this paper, we propose a method that handles between class imbalance and within class imbalance simultaneously for binary classification problem. Removing between class imbalance and within class imbalance simultaneously eliminates the biases of the classifier towards bigger sub-clusters by minimizing the error domination of bigger sub-clusters in total error. The proposed method uses model-based clustering to find the presence of sub-clusters or sub-concepts in the dataset. The number of examples oversampled among the sub-clusters is determined based on the complexity of sub-clusters. The method also takes into consideration the scatter of the data in the feature space and also adaptively copes up with unseen test data using Lowner-John ellipsoid for increasing the accuracy of the classifier. In this study, neural network is being used as this is one such classifier where the total error is minimized and removing the between-class imbalance and within class imbalance simultaneously help the classifier in giving equal weight to all the sub-clusters irrespective of the classes. The proposed method is validated on 9 publicly available data sets and compared with three existing oversampling techniques that rely on the spatial location of minority class examples in the euclidean feature space. The experimental results show the proposed method to be statistically significantly superior to other methods in terms of various accuracy measures. Thus the proposed method can serve as a good alternative to handle various problem domains like credit scoring, customer churn prediction, financial distress, etc., that typically involve imbalanced data sets.

Keywords: classification, imbalanced dataset, Lowner-John ellipsoid, model based clustering, oversampling

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Authors: Tajinder Pal Singh

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Teaching of mathematics to engineering students is an open ended problem in education. The main goal of mathematics learning for engineering students is the ability of applying a wide range of mathematical techniques and skills in their engineering classes and later in their professional work. Most of the undergraduate engineering students and faculties feels that no efforts and attempts are made to demonstrate the applicability of various topics of mathematics that are taught thus making mathematics unavoidable for some engineering faculty and their students. The lack of understanding of concepts in engineering mathematics may hinder the understanding of other concepts or even subjects. However, for most undergraduate engineering students, mathematics is one of the most difficult courses in their field of study. Most of the engineering students never understood mathematics or they never liked it because it was too abstract for them and they could never relate to it. A right balance of application and concept based teaching can only fulfill the objectives of teaching mathematics to engineering students. It will surely improve and enhance their problem solving and creative thinking skills. In this paper, some practical (informal) ways of making mathematics-teaching application based for the engineering students is discussed. An attempt is made to understand the present state of teaching mathematics in engineering colleges. The weaknesses and strengths of the current teaching approach are elaborated. Some of the causes of unpopularity of mathematics subject are analyzed and a few pragmatic suggestions have been made. Faculty in mathematics courses should spend more time discussing the applications as well as the conceptual underpinnings rather than focus solely on strategies and techniques to solve problems. They should also introduce more ‘word’ problems as these problems are commonly encountered in engineering courses. Overspecialization in engineering education should not occur at the expense of (or by diluting) mathematics and basic sciences. The role of engineering education is to provide the fundamental (basic) knowledge and to teach the students simple methodology of self-learning and self-development. All these issues would be better addressed if mathematics and engineering faculty join hands together to plan and design the learning experiences for the students who take their classes. When faculties stop competing against each other and start competing against the situation, they will perform better. Without creating any administrative hassles these suggestions can be used by any young inexperienced faculty of mathematics to inspire engineering students to learn engineering mathematics effectively.

Keywords: application based learning, conceptual learning, engineering mathematics, word problem

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Authors: Ode Kenneth Ogbu

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This study was designed as a survey to investigate the incidence of use and abuse of drug as a social problem among the Nigeria youths in the secondary schools in urban centres of Benue state. 500 SS 3 and fresh secondary school graduates in remedial science class of Benue State University Makurdi with mean age of 16.8 were randomly sampled for the study. An instrument called drug use and abuse perception questionnaire (DAPQ) with a reliability coefficient of 74 were administered to the students. Only 337 copies of the questionnaire were properly completed and returned which reduced the sample size of 337. The data were subjected to factor analysis. X2 statistic and frequency distribution using split half method. The result of the analysis showed that: the DAPQ yield seven baseline factors responsible for drug use and abuse; there was appreciable evidence that the study subjects used drugs (42.1%); alcohol topped the list of the drugs consumed; most students use their pocket money to buy drugs; drugs were purchased from unconventional, hidden places and 13 out of the 20 items of DAPQ were perceived as significant factors in drug use and abuse. The paper recommends proper intervention of government, parents and NGO’S among students to reduce cases of drug abuse.

Keywords: drug abuse, psychology, psychiatry, students

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Authors: Vakhtang Geladze, Nana Bolashvili, Nino Machavariani, Tamazi Karalashvili, Nino Chikhradze, Davit Kartvelishvili

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Fresh water deficit is one of the most important global problems today. In the countries with scarce water resources, they often become a reason of armed conflicts. The peaceful settlement of relations connected with management and water consumption issues within and beyond the frontiers of the country is an important guarantee of the region stability. The said problem is urgent in Georgia as well because of its water objects are located at the borders and the transit run-off that is 12% of the total one. Fresh water resources are the major natural resources of Georgia. Despite of this, water supply of population at its Eastern part is an acute issue. Southeastern part of the country has been selected to carry out the research. This region is notable for deficiency of water resources in the country. The region tends to desertification which aggravates fresh water problem even more and presumably may lead to migration of local population from the area. The purpose of study was creation geographical information system (GIS) of water resources. GIS contains almost all layers of different content (water resources, springs, channels, hydrological stations, population water supply, etc.). The results of work provide an opportunity to identify the resource potential of the mentioned region, control and manage it, carry out monitoring and plan regional economy.

Keywords: desertification, GIS, irrigation, water resources

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Authors: Fatemeh Torfi

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Estimation of stochastic demand in physical distribution in general and efficient transport routs management in particular is emerging as a crucial factor in urban planning domain. It is particularly important in some municipalities such as Tehran where a sound demand management calls for a realistic analysis of the routing system. The methodology involved critically investigating a fuzzy least-squares linear regression approach (FLLRs) to estimate the stochastic demands in the vehicle routing problem (VRP) bearing in mind the customer's preferences order. A FLLR method is proposed in solving the VRP with stochastic demands. Approximate-distance fuzzy least-squares (ADFL) estimator ADFL estimator is applied to original data taken from a case study. The SSR values of the ADFL estimator and real demand are obtained and then compared to SSR values of the nominal demand and real demand. Empirical results showed that the proposed methods can be viable in solving problems under circumstances of having vague and imprecise performance ratings. The results further proved that application of the ADFL was realistic and efficient estimator to face the stochastic demand challenges in vehicle routing system management and solve relevant problems.

Keywords: fuzzy least-squares, stochastic, location, routing problems

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Authors: Zelalem Fantahun

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Part-of-speech tagging is the process of assigning a part-of-speech or other lexical class marker to each word into naturally occurring text. Part-of-speech tagging is the most fundamental and basic task almost in all natural language processing. In natural language processing, the problem of providing large amount of manually annotated data is a knowledge acquisition bottleneck. Since, Amharic is one of under-resourced language, the availability of tagged corpus is the bottleneck problem for natural language processing especially for POS tagging. A promising direction to tackle this problem is to provide a system that does not require manually tagged data. In unsupervised learning, the learner is not provided with classifications. Unsupervised algorithms seek out similarity between pieces of data in order to determine whether they can be characterized as forming a group. This paper explicates the development of unsupervised part-of-speech tagger using K-Means clustering for Amharic language since large amount of data is produced in day-to-day activities. In the development of the tagger, the following procedures are followed. First, the unlabeled data (raw text) is divided into 10 folds and tokenization phase takes place; at this level, the raw text is chunked at sentence level and then into words. The second phase is feature extraction which includes word frequency, syntactic and morphological features of a word. The third phase is clustering. Among different clustering algorithms, K-means is selected and implemented in this study that brings group of similar words together. The fourth phase is mapping, which deals with looking at each cluster carefully and the most common tag is assigned to a group. This study finds out two features that are capable of distinguishing one part-of-speech from others these are morphological feature and positional information and show that it is possible to use unsupervised learning for Amharic POS tagging. In order to increase performance of the unsupervised part-of-speech tagger, there is a need to incorporate other features that are not included in this study, such as semantic related information. Finally, based on experimental result, the performance of the system achieves a maximum of 81% accuracy.

Keywords: POS tagging, Amharic, unsupervised learning, k-means

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Authors: Hwang Ho Kim, Do Gyun Kim, Jin Young Choi, Sang Chul Park

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Since tire production process is very complicated, company-wide management of it is very difficult, necessitating considerable amounts of capital and labors. Thus, productivity should be enhanced and maintained competitive by developing and applying effective production plans. Among major processes for tire manufacturing, consisting of mixing component preparation, building and curing, the mixing process is an essential and important step because the main component of tire, called compound, is formed at this step. Compound as a rubber synthesis with various characteristics plays its own role required for a tire as a finished product. Meanwhile, scheduling tire mixing process is similar to flexible job shop scheduling problem (FJSSP) because various kinds of compounds have their unique orders of operations, and a set of alternative machines can be used to process each operation. In addition, setup time required for different operations may differ due to alteration of additives. In other words, each operation of mixing processes requires different setup time depending on the previous one, and this kind of feature, called sequence dependent setup time (SDST), is a very important issue in traditional scheduling problems such as flexible job shop scheduling problems. However, despite of its importance, there exist few research works dealing with the tire mixing process. Thus, in this paper, we consider the scheduling problem for tire mixing process and suggest an efficient particle swarm optimization (PSO) algorithm to minimize the makespan for completing all the required jobs belonging to the process. Specifically, we design a particle encoding scheme for the considered scheduling problem, including a processing sequence for compounds and machine allocation information for each job operation, and a method for generating a tire mixing schedule from a given particle. At each iteration, the coordination and velocity of particles are updated, and the current solution is compared with new solution. This procedure is repeated until a stopping condition is satisfied. The performance of the proposed algorithm is validated through a numerical experiment by using some small-sized problem instances expressing the tire mixing process. Furthermore, we compare the solution of the proposed algorithm with it obtained by solving a mixed integer linear programming (MILP) model developed in previous research work. As for performance measure, we define an error rate which can evaluate the difference between two solutions. As a result, we show that PSO algorithm proposed in this paper outperforms MILP model with respect to the effectiveness and efficiency. As the direction for future work, we plan to consider scheduling problems in other processes such as building, curing. We can also extend our current work by considering other performance measures such as weighted makespan or processing times affected by aging or learning effects.

Keywords: compound, error rate, flexible job shop scheduling problem, makespan, particle encoding scheme, particle swarm optimization, sequence dependent setup time, tire mixing process

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Authors: Nithipattara Balsiri

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The purposes of this research was to develop instructional model by using research-based learning enhancing critical thinking, cognitive skills, and culture and local wisdom knowledge of undergraduate students. The sample consisted of 307 undergraduate students. Critical thinking and cognitive skills test were employed for data collection. Second-order confirmatory factor analysis, t-test, and one-way analysis of variance were employed for data analysis using SPSS and LISREL programs. The major research results were as follows; 1) the instructional model by using research-based learning enhancing critical thinking, cognitive skills, and culture and local wisdom knowledge should be consists of 6 sequential steps, namely (1) the setting research problem (2) the setting research hypothesis (3) the data collection (4) the data analysis (5) the research result conclusion (6) the application for problem solving, and 2) after the treatment undergraduate students possessed a higher scores in critical thinking and cognitive skills than before treatment at the 0.05 level of significance.

Keywords: critical thinking, cognitive skills, culture and local wisdom knowledge

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Authors: Amal Alatar

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The paper focuses on the exploration of architectural characteristics and decorative elements of the temple of Echmun, emphasizing the socio-economic significance of Sidon during the Greek and Roman periods to understand the implications of their spread and development on the Phoenician cities, as well as reveal the symbolical and societal connotations that may have been connected with the buildings, in order to allow a well-founded examination of common characteristics. In general, studying Phoenician archaeology posed some problems. The main problem is that most major Phoenician settlements lay beneath modern urban centers. This situation often prevented or largely restricted full archaeological investigations; the publications are frequently not complete enough to determine the basic characteristics of the architectural elements. Another key problem is the political instability of the region, which affected the archaeological research in the Phoenician homeland for many years. Nevertheless, during the past decades, an ever-growing cache of data was acquired from the archaeological surroundings of the Phoenician sites. Both the architectural elements from the Greek and Roman period have never been studied as a group before. Surprisingly, they have been largely ignored, despite their apparent profusion throughout the cities. The Roman period of Sidon has generally been neglected in preference to earlier periods, where it is often difficult to distinguish between Roman, Bronze age, medieval and Ottoman structures.

Keywords: archaeology, classical, Hellenistic, Eshmun Temple, architecture, Sidon, Lebanon

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Authors: Mohammad Shahid Jamil

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In this study we have investigated students’ learning and satisfaction in one of the course offered in the Foundation Program at Qatar University. We implied innovative teaching methodology that emphasizes on enhancing students’ thinking skills, decision making, and problem solving skills. Some interesting results were found which can be used to further improve the teaching methodology. To make sure the full use of technology in Foundation Program at Qatar University has started implementing new ways of teaching Math course by using Blackboard as an innovative interactive tool to support standard teaching such as Discussion board, Virtual class, and Study plan in My Math Lab “MML”. In MML Study Plan is designed in such a way that the student can improve their skills wherever they face difficulties with in their Homework, Quiz or Test. Discussion board and Virtual Class are collaborative learning tools encourages students to engage outside of class time. These tools are useful to share students’ knowledge and learning experiences, promote independent and active learning and they helps students to improve their critical thinking skills through the learning process.

Keywords: blackboard, discussion board, critical thinking, active learning, independent learning, problem solving

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Authors: Gupta Amit, Kumar Ramesh, P. C. Tewari

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Globalization is putting enormous pressure on the business organizations specially manufacturing one to rethink the supply chain in innovative manners. Inventory consumes major portion of total sale revenue. Effective and efficient inventory management plays a vital role for the successful functioning of any organization. Selection of inventory policy is one of the important purchasing activities. This paper focuses on selection and ranking of alternative inventory policies. A deterministic quantitative model-based on Distance Based Approach (DBA) method has been developed for evaluation and ranking of inventory policies. We have employed this concept first time for this type of the selection problem. Four inventory policies Economic Order Quantity (EOQ), Just in Time (JIT), Vendor Managed Inventory (VMI) and monthly policy are considered. Improper selection could affect a company’s competitiveness in terms of the productivity of its facilities and quality of its products. The ranking of inventory policies is a multi-criteria problem. There is a need to first identify the selection criteria and then processes the information with reference to relative importance of attributes for comparison. Criteria values for each inventory policy can be obtained either analytically or by using a simulation technique or they are linguistic subjective judgments defined by fuzzy sets, like, for example, the values of criteria. A methodology is developed and applied to rank the inventory policies.

Keywords: inventory policy, ranking, DBA, selection criteria

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Authors: Meng Koon Lee, Mohammad Hosseini Fouladi, Satesh Narayana Namasivayam

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Research is focused on the response of soundboards of Classical guitars at frequencies up to 5 kHz as the soundboard is a major contributor to acoustic radiation at high frequencies when compared to the bridge and sound hole. A thin rectangular plate of variable thickness that is simply-supported on all sides is used as an analytical model of the research. This model is used to study the response of the guitar soundboard as the latter can be considered as a modified form of a rectangular plate. Homotopy Perturbation Method (HPM) is selected as a mathematical method to obtain an analytical solution of the 4th-order parabolic partial differential equation of motion of the rectangular plate of constant thickness viewed as a linear problem. This procedure is generalized to the nonlinear problem of the rectangular plate with variable thickness and an analytical solution can also be obtained. Sound power is used as a parameter to investigate the acoustic radiation of soundboards made from spruce using various bracing patterns. The sound power of soundboards made from Malaysian softwood such as damar minyak, sempilor or podo are investigated to determine the viability of replacing spruce as future materials for soundboards of Classical guitars.

Keywords: rectangular plates, analytical solution, homotopy perturbation, natural frequencies

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Authors: Hassidou Saidou, Soulé Aminou

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As in many towns of African countries, the waste management, in particularly solid constitutes a major problem for the municipal authorities of Maradi. The aim of this study is to make a diagnosis of the present system of waste management in the town of Maradi. The approach was consisted to some interviews with the municipal authorities, cleaning up and health technicians and some housewives investigations. According to the health technicians of the town, the causes due to the problem of waste management in Maradi town are: collecting capacity insufficient, lack of effective sensitization of people, undeveloped and uncontrolled rubbish dumps, lack of gutter and its maintenance, and insufficient and unqualified human resources. As to the authorities, they denounce always the attitude and the behavior of citizens on the waste issue. The waste evacuation is doing by municipal collecting or by depositing in wild rubbish dump. Some people eliminate their waste by burning or duping in the streets or in their houses. According to our investigations, 52% of population evacuates their waste daily. The satisfaction rate of municipal collecting is for 32%. The analysis showed that the present system of waste management in Maradi town is failing. As solutions, we proposed to equip the technical offices with appropriated material and financial means, reinforce the involved actor’s capacities and making in application the operatives regulations for the waste management.

Keywords: maradi, municipal authorities, Niger Republic, solid waste management

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Authors: Dawit Thomas Lambamo

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Conduct disorder has become a major health and social problem; it is the most common psychiatric problem diagnosed among students which affect the academic and social interaction of students. This intervention was conducted in Dil Betigil primary school. After identifying six students with conduct disorder in Dil Betigil primary school, the intervention was conducted using a true experimental research design specifically pretest and posttest control group design. Data from teachers and parents of the students with conduct disorder were collected using adapted conduct disorder scale and semi-structured interview. The independent sample t-test of Pretest results of both experimental and control group indicated that there is no statistically significant difference between experimental and control groups. Intervention is carried out to enhance their social interaction and to decrees aggressive, a serious violation of rules and theft behavior of students in collaboration with teachers and parents. After six intervention weeks the post-test result showed that there was statistically significant difference in aggression and serious violation between the experimental and control groups, but there was no statistically significant mean difference regarding deceitful or theft between the experimental and control group.

Keywords: conduct, disorder, social interaction, interaction

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Authors: András Szekrényes

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Delamination is one of the major failure modes in laminated composite structures. Delamination tips are mostly captured by spatial numerical models in order to predict crack growth. This paper presents some mechanical models of delaminated composite shells based on shallow shell theories. The mechanical fields are based on a third-order displacement field in terms of the through-thickness coordinate of the laminated shell. The undelaminated and delaminated parts are captured by separate models and the continuity and boundary conditions are also formulated in a general way providing a large size boundary value problem. The system of differential equations is solved by the state space method for an elliptic delaminated shell having simply supported edges. The comparison of the proposed and a numerical model indicates that the primary indicator of the model is the deflection, the secondary is the widthwise distribution of the energy release rate. The model is promising and suitable to determine accurately the J-integral distribution along the delamination front. Based on the proposed model it is also possible to develop finite elements which are able to replace the computationally expensive spatial models of delaminated structures.

Keywords: J-integral, levy method, third-order shell theory, state space solution

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Authors: Kathie Records, R. Jeanne Ruiz, Kimberly Ayers, Rebecca Pasillas

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Background: Preterm births of less than 37 weeks gestation occur disproportionately to Hispanics living along the U.S.-Mexico border. Prematurity has devastating and costly effects on children, families and the health care system. Few preventive interventions have been tested for this vulnerable group. Objectives: To present the modeling and pilot testing of the theory-based Mastery Lifestyle Intervention (MLI), designed to reduce and prevent PTB among Mexican American women (the terms Hispanics or Latinas will also be used to represent this group) living in the United States. Design and Methods: The conceptualization of the problem of preterm births and the available literature underpinning the mastery lifestyle intervention will be reviewed. The lifestyle intervention includes foundational components of problem solving therapy and acceptance and commitment therapy. Findings from implementation of a one-group pilot test and focus group evaluated the feasibility and acceptability of the MLI. Summary: Participants found the MLI to be feasible and acceptable, and reported perceiving improved health status and familial relationships. Suggestions were provided for modifications prior to efficacy testing. The MLI appears to be a theoretically and empirically grounded intervention that holds promise for preventing preterm births among Latinas.

Keywords: birth, Hispanic, intervention, stress

Procedia PDF Downloads 371

Authors: R. Tlili Yaakoubi, H.Nakouri, O. Blanpain, S. Lallahem

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The current tools for real time management of sewer systems are based on two software tools: the software of weather forecast and the software of hydraulic simulation. The use of the first ones is an important cause of imprecision and uncertainty, the use of the second requires temporal important steps of decision because of their need in times of calculation. This way of proceeding fact that the obtained results are generally different from those waited. The major idea of this project is to change the basic paradigm by approaching the problem by the "automatic" face rather than by that "hydrology". The objective is to make possible the realization of a large number of simulations at very short times (a few seconds) allowing to take place weather forecasts by using directly the real time meditative pluviometric data. The aim is to reach a system where the decision-making is realized from reliable data and where the correction of the error is permanent. A first model of control laws was realized and tested with different return-period rainfalls. The gains obtained in rejecting volume vary from 19 to 100 %. The development of a new algorithm was then used to optimize calculation time and thus to overcome the subsequent combinatorial problem in our first approach. Finally, this new algorithm was tested with 16- year-rainfall series. The obtained gains are 40 % of total volume rejected to the natural environment and of 65 % in the number of discharges.

Keywords: automation, optimization, paradigm, RTC

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Authors: Radim Sip, Denisa Denglerova

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It’s impossible to capture complex phenomena, such as inclusion, with reductionism. The most common form of reductionism is the objectivist approach, where processes and relationships are reduced to entities and clearly outlined phases, with a consequent search for relationships between them. Constructivism as a paradigm and situational analysis as a methodological research portfolio represent a way to avoid the dominant objectivist approach. They work with a situation, i.e. with the essential blending of actors and their environment. Primary transactions are taking place between actors and their surroundings. Researchers create constructs based on their need to solve a problem. Concepts therefore do not describe reality, but rather a complex of real needs in relation to the available options how such needs can be met. For examination of a complex problem, corresponding methodological tools and overall design of the research are necessary. Using an original research on inclusion in the Czech Republic as an example, this contribution demonstrates that inclusion is not a substance easily described, but rather a relationship field changing its forms in response to its actors’ behaviour and current circumstances. Inclusion consists of dynamic relationship between an ideal, real circumstances and ways to achieve such ideal under the given circumstances. Such achievement has many shapes and thus cannot be captured by description of objects. It can be expressed in relationships in the situation defined by time and space. Situational analysis offers tools to examine such phenomena. It understands a situation as a complex of dynamically changing aspects and prefers relationships and positions in the given situation over a clear and final definition of actors, entities, etc. Situational analysis assumes creation of constructs as a tool for solving a problem at hand. It emphasizes the meanings that arise in the process of coordinating human actions, and the discourses through which these meanings are negotiated. Finally, it offers “cartographic tools” (situational maps, socials worlds / arenas maps, positional maps) that are able to capture the complexity in other than linear-analytical ways. This approach allows for inclusion to be described as a complex of phenomena taking place with a certain historical preference, a complex that can be overlooked if analyzed with a more traditional approach.

Keywords: constructivism, situational analysis, objective realism, reductionism, inclusion

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Authors: Abduxukur Zayit, Guo Rui Chen

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Universities play important role for develop and distribute sustainable development ideas. This research based on the current situation of large and widely distributed university campuses in China. In view of the deterioration of campus performance, the aging of function and facilities, the large consumption of energy and resources, a logic of "problem-oriented-goal-oriented- At the level, taking the problem orientation as the focus,this paper analyzes the main influencing factors of the existing characteristics of the university campuses, establishes the digital assessment methods and clarifies the key points of the rennovation. Based on the goal orientation, this paper puts forward the existing university campus design principles, builds the green transformation-carding model and sets up the post-use evaluation model. In the end, with dual guidance as the constraint, we will formulate green design standards for campus greening, construct a greening enhancement measure for campus environment, and develop and promote a green campus after-use assessment platform. It provides useful research methods and research ideas for the reconstruction of the existing campus in China, especially the urban universities.

Keywords: design method, existing university campus, green renovation, sustainable development

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Authors: Bruce Small, Martin Espig, Alyssa Ryan

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In the agricultural sector, the rapid expansion of herbicide resistant weeds is a major threat to the global sustainability of food and fibre production. Efforts to avoid herbicide resistance have primarily focused on new technologies and farmer education. Yet, despite decades of advice to growers from agricultural scientists and extension professionals of the need for management strategies for herbicide use, herbicide resistance continues to increase. Technological options are running out and current extension efforts to change farmer behaviour are failing to curb the problem. As part of a five-year, government funded, research programme to address herbicide resistance in New Zealand, social science theory and practice are being utilised to investigate the complexities of managing herbicide use and controlling resistance. As an initial step, we are utilising a transdisciplinary, multi-level systems approach to examine the problem definition, knowledge beliefs, attitudes and values of different important actors in the agri-business sector. In this paper, we report early project results from qualitative research examining the similarities and contrasts in the perceptions of scientists, farmer/growers, and rural professionals.

Keywords: behaviour change, herbicide resistant weeds, knowledge beliefs, systems perspective

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Authors: Magaji Zainab Musa, Nordin M. A. Rahman, Julaily Aida Jusoh

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This paper discusses the formal specification of web services applications for digital reference services (WSDRS). Digital reference service involves a user requesting for help from a reference librarian and a reference librarian responding to the request of a user all by electronic means. In most cases users do not get satisfied while using digital reference service due to delay of response of the librarians. Another may be due to no response or due to librarian giving an irrelevant solution to the problem submitted by the user. WDSRS is an informal model that claims to reduce the problems of digital reference services in libraries. It uses web services technology to provide efficient way of satisfying users’ need in the reference section of libraries. But informal model is in natural language which is inconsistent and ambiguous that may cause difficulties to the developers of the system. In order to solve this problem we decided to convert the informal specifications into formal specifications. This is supposed to reduce the overall development time and cost. Formal specification can be used to provide an unambiguous and precise supplement to natural language descriptions. It can be rigorously validated and verified leading to the early detection of specification errors. We use Z language to develop the formal model and verify it with Z/EVES theorem prover tool.

Keywords: formal, specifications, web services, digital reference services

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Authors: Natarajan Vijayarangan, Viswanath Kumar Ganesan, G. Kumudhavalli

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This abstract figures out an uncertainty problem pertaining to evaluating business proposals or concept notes in an organisation. Let us consider business proposal evaluation process (BPEP) for execution of corporate research cum business projects in the organisation. Assume that two concept notes X and Y of BPEP are approved: one of them is a full-fledged type (100% financial approval given by the organisation) - X and other one is a conditional type (a partial financial approval given by the organisation) - Y. Then a penalty criteria has been introduced during the process. At the end of annual appraisal, if both of them complete as per the goals and objectives committed or figured out at the time of concept note submission, then both will get an incentive of $N from the organisation. If one of them doesn't fulfill the goals and objectives at the year-end appraisal, then d% reduction or cut will be levied on the project budget for the next year. If X fulfills the goals and objectives and Y doesn't , then X gets a gain of d% on Y's previous year budget and Y gets a loss of d% from the previous year budget for the next year. And vice-versa. Further, an incentive of $N will be given to those who gains. This process is a part of Necktie paradox and inherits an uncertainty principle on X or Y getting more than $N even if X or Y performs well.Solving the above problem and generalizing on finitely many concept notes will be a challenging task.

Keywords: concept notes, necktie paradox, annual appraisal, project budget and gain or loss

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Authors: Sumit Kumar Vishawakarma, Tapas Ranjan Panihari

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The article investigates the propagation behavior of SV-wave, SH-wave, and P-wave in a continuously inhomogeneous cross-anisotropic material, where the material properties such as Young's moduli, shear modulus, and density vary as an arbitrary continuous function of depth. In the considered model, Hook's law, strain-displacement relations along with equilibrium equations have been used to derive the governing equation. The mathematical formulation of this physical problem gives rise to an eigenvalue problem with displacement components as fundamental variables. This leads to achieving the closed-form expressions for quasi-wave velocities of SV-wave, SH-wave, and P-wave in the considered framework. These characteristics of wave propagation along with the above-stated variation have been scrutinized based on their numerical results. This parametric study reveals that wave velocity remarkably fluctuates as the magnitude of inhomogeneity parameters increases and decreases. The prominent effect has been shown depicting the dependence of wave velocity on the degree of material anisotropy. The influence of phase angle and depth of the medium has been remarkably established. The present study may facilitate the theoretical foundation and practical application in the field of earthquake source mechanisms.

Keywords: cross-anisotropic, inhomogeneity, P-wave, SH-wave, SV-wave, shear modulus, Young’s modulus

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Authors: Orhun Aydin, Mark V. Janikas, Rodrigo Alves, Renato Assuncao

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In this paper, a tree-based perturbation methodology for regionalization inference is presented. Regionalization is a constrained optimization problem that aims to create groups with similar attributes while satisfying spatial contiguity constraints. Similar to any constrained optimization problem, the spatial constraint may hinder convergence to some global minima, resulting in spatially contiguous members of a group with dissimilar attributes. This paper presents a general methodology for rigorously perturbing spatial constraints through the use of random spanning trees. The general framework presented can be used to quantify the effect of the spatial constraints in the overall regionalization result. We compare several types of stochastic spanning trees used in inference problems such as fuzzy regionalization and determining the number of regions. Performance of stochastic spanning trees is juxtaposed against the traditional permutation-based hypothesis testing frequently used in spatial statistics. Inference results for fuzzy regionalization and determining the number of regions is presented on the Local Area Personal Incomes for Texas Counties provided by the Bureau of Economic Analysis.

Keywords: regionalization, constrained clustering, probabilistic inference, fuzzy clustering

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Authors: Migena Mana, Ahmed Khalid Syed, Abdul Malik, Nikhil Cherian

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In recent years, advancements in deep learning enabled researchers to tackle the problem of self-driving cars. Car companies use huge datasets to train their deep learning models to make autonomous cars a reality. However, this approach has certain drawbacks in that the state space of possible actions for a car is so huge that there cannot be a dataset for every possible road scenario. To overcome this problem, the concept of reinforcement learning (RL) is being investigated in this research. Since the problem of autonomous driving can be modeled in a simulation, it lends itself naturally to the domain of reinforcement learning. The advantage of this approach is that we can model different and complex road scenarios in a simulation without having to deploy in the real world. The autonomous agent can learn to drive by finding the optimal policy. This learned model can then be easily deployed in a real-world setting. In this project, we focus on three RL algorithms: Q-learning, Deep Deterministic Policy Gradient (DDPG), and Proximal Policy Optimization (PPO). To model the environment, we have used TORCS (The Open Racing Car Simulator), which provides us with a strong foundation to test our model. The inputs to the algorithms are the sensor data provided by the simulator such as velocity, distance from side pavement, etc. The outcome of this research project is a comparative analysis of these algorithms. Based on the comparison, the PPO algorithm gives the best results. When using PPO algorithm, the reward is greater, and the acceleration, steering angle and braking are more stable compared to the other algorithms, which means that the agent learns to drive in a better and more efficient way in this case. Additionally, we have come up with a dataset taken from the training of the agent with DDPG and PPO algorithms. It contains all the steps of the agent during one full training in the form: (all input values, acceleration, steering angle, break, loss, reward). This study can serve as a base for further complex road scenarios. Furthermore, it can be enlarged in the field of computer vision, using the images to find the best policy.

Keywords: autonomous driving, DDPG (deep deterministic policy gradient), PPO (proximal policy optimization), reinforcement learning

Procedia PDF Downloads 149