Search results for: location routing problem

Authors: E. Montesinos-Pedro, L. G. Toscano-Flores, N. Domínguez-Ramírez

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Water scarcity is a worldwide issue, coupled with climate change is a relevant problem, that affect not only large cities, but also rural areas. The Municipality of Santiago Tilantongo belongs to the district of Nochixtlán Oaxaca, it’s built up from 14 communities, one of them San Martin de las Palmas. This community was founded in 1900, at that time the inhabitants were supplied with water through rivers of the region which were abundant (they used containers filled in the river for that purpose); However, over the years the level of the rivers began to drop and in 1994 specific wells were located to store water and at the same time make it drinkable, this whit support of the state of Oaxaca and the program Procampo. By the year 2000 the shortage of water in the supply sources was notorious, the community requested support from the Oaxaca State government to solve the problem. The government’s response consisted in the implementation of ferro-cement tanks (2005) and water wells (2010), both for rainwater collection, Hower, it was not enough. Now days the community has a population of 60 inhabitants who have resisted and adapted to water scarcity, not only with the programs implemented by the government, but they also have implemented important structural analysis strategies. The objective of this research is to know the adaptation strategies used by the community to analyze them and propose improvements for water conservation and mitigation of this scarcity.

Keywords: adaptation, climate change, mitigation, resiliencia

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Authors: Kittipob Kondee, Chutima Prommak

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In this paper, we propose an optimization technique that can be used to optimize the placements of reference nodes and improve the location determination performance for the multi-floor building. The proposed technique is based on Simulated Annealing algorithm (SA) and is called MSMR-M. The performance study in this work is based on simulation. We compare other node-placement techniques found in the literature with the optimal node-placement solutions obtained from our optimization. The results show that using the optimal node-placement obtained by our proposed technique can improve the positioning error distances up to 20% better than those of the other techniques. The proposed technique can provide an average error distance within 1.42 meters.

Keywords: indoor positioning system, optimization system design, multi-floor building, wireless sensor networks

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Authors: Irina A. Gudkova, Yousra Demigha

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Scientific research is moving more and more towards the study of complex systems in several areas of economics, biology physics, and computer science. In this paper, we will work on complex systems in communication networks, Wireless Sensor Networks (WSN) that are considered as stochastic systems composed of interacting entities. The current advancements of the sensing in computing and communication systems is an investment ground for research in several tracks. A detailed presentation was made for the WSN, their use, modeling, different problems that can occur in their application and some solutions. The main goal of this work reintroduces the idea of mean field method since it is a powerful technique to solve this type of models especially systems that evolve according to a Continuous Time Markov Chain (CTMC). Modeling of a CTMC has been focused; we obtained a large system of interacting Continuous Time Markov Chain with population entities. The main idea was to work on one entity and replace the others with an average or effective interaction. In this context to make the solution easier, we consider a wireless sensor network as a multi-body problem and we reduce it to one body problem. The method was applied to a system of WSN modeled as a Markovian queue showing the results of the used technique.

Keywords: Continuous-Time Markov Chain, Hidden Markov Chain, mean field method, Wireless sensor networks

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Authors: Ernawati Mustafa Kamal, Hasnanywati Hassan, Atasya Osmadi

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The housing industry is crucial for sustainable development of every country. Housing is a basic need that can enhance the quality of life. Owning a house is therefore the main aim of individuals. However, affordability has become a critical issue towards homeownership. In recent years, housing price in the main cities has increased tremendously to unaffordable level. This paper investigates factors influencing the housing price from developer’s perspective and provides recommendation on strategies to tackle this issue. Online and face-to-face survey was conducted on housing developers operating in Penang, Malaysia. The results indicate that (1) location; (2) macroeconomics factor; (3) demographic factors; (4) land/zoning and; (5) industry factors are the main factors influencing the housing price. This paper contributes towards better understanding on developers’ view on how the housing price is determined and form a basis for government to help tackle the housing affordability issue.

Keywords: factors influence, house price, housing developers, Malaysia

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Authors: Tarek Soliman Mostafa Soliman Al-Nana'i

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There are non-steady voiced augments in the Semitic languages, and in the morphological and structural augmentation, two sounds were augments in all Semitic languages at the level of the spoken language and two letters at the level of the written language, which are the hamza and the ta’. This research studies only the second of them; Therefore, we defined it as “The Voiceless Dental- alveolar common augment” (VDACA) to distinguish it from the glottal sound “Hamza”, first, middle, or last, in a noun or in a verb, in Arabic and its equivalent in the Semitic languages. What is meant by “VDACA” is the ta’ that is in addition to the root of the word at the morphological level: the word “voiceless” takes out the voiced sounds that we studied before, and the “dental- alveolar common augment” takes out the laryngeal sound of them, which is the “Hamza”: and the word “common” brings out the uncommon voiceless sounds, which are sīn, shīn, and hā’. The study is limited to the ta' alone among the Arabic sounds, and this title faced a problem in identifying it with the ta'. Because the designation of the ta is not the same in most Semitic languages. Hebrew, for example, has “tav” and is pronounced with the voiced fa (v), which is not in Arabic. It is called different names in other Semitic languages, such as “taw” or “tAu” in old Syriac. And so on. This goes hand in hand with the insistence on distance from the written level and the reference to the phonetic aspect in this study that is closely and closely linked to the morphological level. Therefore, the study is “morphophonemic”. What is meant by Semitic languages in this study are the following: Akkadian, Ugaritic, Hebrew, Syriac, Mandaean, Ge'ez, and Amharic. The problem of the study is the agreement or difference between these languages in the position of that augment, first, middle, or last. And in determining the distinguishing characteristics of each language from the other. As for the study methodology, it is determined by the comparative approach in Semitic languages, which is based on the descriptive approach for each language. The study is divided into an introduction, four sections, and a conclusion: Introduction: It included the subject of the study, its importance, motives, problem, methodology, and division. The first section: VDACA as a non-common phoneme. The second: VDACA as a common phoneme. The third: VDACA as a functional morpheme. The fourth section: Commentary and conclusion with the most important results. The positions of VDACA in Arabic and other Semitic languages, and in nouns and verbs, were limited to first, middle, and last. The research identified the individual addition, which is common with other augments, and the research proved that this augmentation is constant in all Semitic languages, but there are characteristics that distinguish each language from the other.

Keywords: voiceless -, dental- alveolar, augment, Arabic - semitic languages

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Authors: David Ming Liu, Benjamin Hirsch, Bashir Aden

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Syndromic surveillance is to detect or predict disease outbreaks through the analysis of medical sources of data. Using social media data like tweets to do syndromic surveillance becomes more and more popular with the aid of open platform to collect data and the advantage of microblogging text and mobile geographic location features. In this paper, a Syndromic Surveillance Framework is presented with machine learning kernel using tweets data analytics. Influenza and the three cities Abu Dhabi, Al Ain and Dubai of United Arabic Emirates are used as the test disease and trial areas. Hospital cases data provided by the Health Authority of Abu Dhabi (HAAD) are used for the correlation purpose. In our model, Latent Dirichlet allocation (LDA) engine is adapted to do supervised learning classification and N-Fold cross validation confusion matrix are given as the simulation results with overall system recall 85.595% performance achieved.

Keywords: Syndromic surveillance, Tweets, Machine Learning, data mining, Latent Dirichlet allocation (LDA), Influenza

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Authors: Jaechoul Shin, Juhwan Hwang

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In case of applying the BIM method to the civil engineering in the area of free formed structure, we can expect comparatively high rate of construction productivity as it is in the building engineering area. In this research, we developed quantity calculation error applying it to earthwork and bridge construction (e.g. PSC-I type segmental girder bridge amd integrated bridge of steel I-girders and inverted-Tee bent cap), NATM (New Austrian Tunneling Method) tunnel construction, retaining wall construction, culvert construction and implemented BIM based 3D modeling quantity survey. we confirmed high reliability of the BIM-based method in structure work in which errors occurred in range between -6% ~ +5%. Especially, understanding of the problem and improvement of the existing 2D-CAD based of quantity calculation through rock type quantity calculation error in range of -14% ~ +13% of earthwork quantity calculation. It is benefit and applicability of BIM method in civil engineering. In addition, routine method for quantity of earthwork has the same error tolerance negligible for that of structure work. But, rock type's quantity calculated as the error appears significantly to the reliability of 2D-based volume calculation shows that the problem could be. Through the estimating quantity of earthwork based 3D-BIM, proposed method has better reliability than routine method. BIM, as well as the design, construction, maintenance levels of information when you consider the benefits of integration, the introduction of BIM design in civil engineering and the possibility of applying for the effectiveness was confirmed.

Keywords: BIM, 3D modeling, 3D-BIM, quantity of earthwork

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Authors: Alper Akin, Ibrahim Aydogdu

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This study presents a hybrid metaheuristic algorithm to obtain optimum designs for steel space buildings. The optimum design problem of three-dimensional steel frames is mathematically formulated according to provisions of LRFD-AISC (Load and Resistance factor design of American Institute of Steel Construction). Design constraints such as the strength requirements of structural members, the displacement limitations, the inter-story drift and the other structural constraints are derived from LRFD-AISC specification. In this study, a hybrid algorithm by using teaching-learning based optimization (TLBO) and harmony search (HS) algorithms is employed to solve the stated optimum design problem. These algorithms are two of the recent additions to metaheuristic techniques of numerical optimization and have been an efficient tool for solving discrete programming problems. Using these two algorithms in collaboration creates a more powerful tool and mitigates each other’s weaknesses. To demonstrate the powerful performance of presented hybrid algorithm, the optimum design of a large scale steel building is presented and the results are compared to the previously obtained results available in the literature.

Keywords: optimum structural design, hybrid techniques, teaching-learning based optimization, harmony search algorithm, minimum weight, steel space frame

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Authors: Anastasia Tsakiridi

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Geographic information systems (GIS) have been utilized in numerous spatial problems, such as site research, land suitability, and demographic analysis. Besides, GIS has been applied in scientific fields like geography, health, and economics. In business studies, GIS has been used to provide insights and spatial perspectives in demographic trends, spending indicators, and network analysis. To date, the information regarding the available usages of GIS in supply chain management (SCM) and how these analyses can benefit businesses is limited. A systematic literature review (SLR) of the last 5-year peer-reviewed academic literature was conducted, aiming to explore the existing usages of GIS in SCM. The searches were performed in 3 databases (Web of Science, ProQuest, and Business Source Premier) and reported using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology. The analysis resulted in 79 papers. The results indicate that the existing GIS applications used in SCM were in the following domains: a) network/ transportation analysis (in 53 of the papers), b) location – allocation site search/ selection (multiple-criteria decision analysis) (in 45 papers), c) spatial analysis (demographic or physical) (in 34 papers), d) combination of GIS and supply chain/network optimization tools (in 32 papers), and e) visualization/ monitoring or building information modeling applications (in 8 papers). An additional categorization of the literature was conducted by examining the usage of GIS in the supply chain (SC) by the business sectors, as indicated by the volume of the papers. The results showed that GIS is mainly being applied in the SC of the biomass biofuel/wood industry (33 papers). Other industries that are currently utilizing GIS in their SC were the logistics industry (22 papers), the humanitarian/emergency/health care sector (10 papers), the food/agro-industry sector (5 papers), the petroleum/ coal/ shale gas sector (3 papers), the faecal sludge sector (2 papers), the recycle and product footprint industry (2 papers), and the construction sector (2 papers). The results were also presented by the geography of the included studies and the GIS software used to provide critical business insights and suggestions for future research. The results showed that research case studies of GIS in SCM were conducted in 26 countries (mainly in the USA) and that the most prominent GIS software provider was the Environmental Systems Research Institute’s ArcGIS (in 51 of the papers). This study is a systematic literature review of the usage of GIS in SCM. The results showed that the GIS capabilities could offer substantial benefits in SCM decision-making by providing key insights to cost minimization, supplier selection, facility location, SC network configuration, and asset management. However, as presented in the results, only eight industries/sectors are currently using GIS in their SCM activities. These findings may offer essential tools to SC managers who seek to optimize the SC activities and/or minimize logistic costs and to consultants and business owners that want to make strategic SC decisions. Furthermore, the findings may be of interest to researchers aiming to investigate unexplored research areas where GIS may improve SCM.

Keywords: supply chain management, logistics, systematic literature review, GIS

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Authors: Loai AbdAllah, Mahmoud Kaiyal

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Missing values in real-world datasets are a common problem. Many algorithms were developed to deal with this problem, most of them replace the missing values with a fixed value that was computed based on the observed values. In our work, we used a distance function based on Bhattacharyya distance to measure the distance between objects with missing values. Bhattacharyya distance, which measures the similarity of two probability distributions. The proposed distance distinguishes between known and unknown values. Where the distance between two known values is the Mahalanobis distance. When, on the other hand, one of them is missing the distance is computed based on the distribution of the known values, for the coordinate that contains the missing value. This method was integrated with Wikaya, a digital health company developing a platform that helps to improve prevention of chronic diseases such as diabetes and cancer. In order for Wikaya’s recommendation system to work distance between users need to be measured. Since there are missing values in the collected data, there is a need to develop a distance function distances between incomplete users profiles. To evaluate the accuracy of the proposed distance function in reflecting the actual similarity between different objects, when some of them contain missing values, we integrated it within the framework of k nearest neighbors (kNN) classifier, since its computation is based only on the similarity between objects. To validate this, we ran the algorithm over diabetes and breast cancer datasets, standard benchmark datasets from the UCI repository. Our experiments show that kNN classifier using our proposed distance function outperforms the kNN using other existing methods.

Keywords: missing values, incomplete data, distance, incomplete diabetes data

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Authors: Yan-Ren Chen, Jenn-Kaie Lain

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This paper proposes a novel indoor positioning algorithm based on visible light communications, implemented by light-emitting diode fixtures. In the proposed positioning algorithm, distances between light-emitting diode fixtures and mobile terminal are derived from the assumption of ideal Lambertian optic radiation model, and Trilateration positioning method is proceeded immediately to get the coordinates of mobile terminal. The proposed positioning algorithm directly obtains distance information from the optical signal modeling, and therefore, statistical distribution of received signal strength at different positions in interior space has no need to be pre-established. Numerically, simulation results have shown that the proposed indoor positioning algorithm can provide accurate location coordinates estimation.

Keywords: indoor positioning, received signal strength, trilateration, visible light communications

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Authors: Habtamu Garoma Debela, Gemechis File Duressa

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In this work, our primary interest is to provide ε-uniformly convergent numerical techniques for solving singularly perturbed semilinear boundary value problems with non-local boundary condition. These singular perturbation problems are described by differential equations in which the highest-order derivative is multiplied by an arbitrarily small parameter ε (say) known as singular perturbation parameter. This leads to the existence of boundary layers, which are basically narrow regions in the neighborhood of the boundary of the domain, where the gradient of the solution becomes steep as the perturbation parameter tends to zero. Due to the appearance of the layer phenomena, it is a challenging task to provide ε-uniform numerical methods. The term 'ε-uniform' refers to identify those numerical methods in which the approximate solution converges to the corresponding exact solution (measured to the supremum norm) independently with respect to the perturbation parameter ε. Thus, the purpose of this work is to develop, analyze, and improve the ε-uniform numerical methods for solving singularly perturbed problems. These methods are based on nonstandard fitted finite difference method. The basic idea behind the fitted operator, finite difference method, is to replace the denominator functions of the classical derivatives with positive functions derived in such a way that they capture some notable properties of the governing differential equation. A uniformly convergent numerical method is constructed via nonstandard fitted operator numerical method and numerical integration methods to solve the problem. The non-local boundary condition is treated using numerical integration techniques. Additionally, Richardson extrapolation technique, which improves the first-order accuracy of the standard scheme to second-order convergence, is applied for singularly perturbed convection-diffusion problems using the proposed numerical method. Maximum absolute errors and rates of convergence for different values of perturbation parameter and mesh sizes are tabulated for the numerical example considered. The method is shown to be ε-uniformly convergent. Finally, extensive numerical experiments are conducted which support all of our theoretical findings. A concise conclusion is provided at the end of this work.

Keywords: nonlocal boundary condition, nonstandard fitted operator, semilinear problem, singular perturbation, uniformly convergent

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Authors: M. B. Neace, Xin GAo

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Small entrepreneurs are ubiquitous. Regardless of location their success depends on several behavioral characteristics and several market conditions. In this concept paper, we extend this paradigm to include elements from the science of chaos. Our observations, research findings, literature search and intuition lead us to the proposition that all entrepreneurs seek increasing returns, as did the many small entrepreneurs we have interviewed over the years. There will be a few whose initial perturbations may create tsunami-like waves of increasing returns over time resulting in very large market consequences–the butterfly impact. When small entrepreneurs perturb the market-place and their initial efforts take root a series of phase-space transitions begin to occur. They sustain the stream of increasing returns by scaling up. Chaos theory contributes to our understanding of this phenomenon. Sustaining and nourishing increasing returns of small entrepreneurs as complex adaptive systems requires scaling. In this paper we focus on the most critical element of the small entrepreneur scaling process–the mindset of the owner-operator.

Keywords: entrepreneur, increasing returns, scaling, chaos

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Authors: Mahmoud Roushdi, Hany Mostafa, Khaled Kheireldin

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Sinai Peninsula and Suez Canal Corridor are promising and important economic regions in Egypt due to the unique location and development opportunities. Thus, the climate change impacts should be assessed over the mentioned area. Accordingly, this paper aims to assess the climate extreme indices in through the last 35 year over Sinai Peninsula and Suez Canal Corridor in addition to predict the climate extreme indices up to 2100. Present and future climate indices were analyzed with using different RCP scenarios 4.5 and 8.5 from 2010 until 2100 for Sinai Peninsula and Suez Canal Corridor. Furthermore, both CanESM and HadGEM2 global circulation models were used. The results indicate that the number of summer days is predicted to increase, on the other hand the frost days is predicted to decrease. Moreover, it is noted a slight positive trend for the percentile of wet and extremely days R95p and R99p for RCP4.5 and negative trend for RCP8.5.

Keywords: climate change, extreme indices, RCP, Sinai Peninsula

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Authors: Manana Lobzhanidze

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Introduction: The paper will argue that labor migration is the most important problem Georgia faces today. The structure of labor migration by age and gender of Georgia is analyzed. The main driving factors of circular labor migration during the last ten years are identified. While studying migration, it is necessary to discuss the interconnection of economic, social, and demographic features, also taking into consideration the policy of state regulations in terms of education and professional training. Methodology: Different research methods are applied in the presented paper: statistical, such as selection, grouping, observation, trend, and qualitative research methods, namely; analysis, synthesis, induction, deduction, comparison ones. Main Findings: Labour migrants are filling the labor market as a low salary worker. The main positive feedback of migration from developing countries is poverty eradication, but this process is accompanied by problems, such as 'Brain Drain'. The country loses an important part of its intellectual potential, and it is invested by households or state itself. Conclusions: Labor migration is characterized to be temporary, but socio-economic problems of the country often push the labor migration in the direction of longterm and illegal migration. Countries with developed economies try to stricter migration policy and fight illegal migration with different methods; circular migration helps solve this problem. Conclusions and recommendations are included about circular labor migration consequences in Georgia and its influence on the reduction of unemployment level.

Keywords: migration, circular labor migration, labor migration employment, unemployment

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Authors: Weiju Zhou, Alex Hopkins, Ruoling Chen

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Background: China has increased the gap in income between richer and poorer over the past 40 years, and the number of deaths from people with angina has been rising. It is unclear whether socioeconomic status (SES) is associated with increased mortality in older people with angina. Methods: Data from a cohort study of 2,380 participants aged ≥ 65 years, who were randomly recruited from 5-province urban communities were examined in China. The cohort members were interviewed to record socio-demographic and risk factors and document doctor-diagnosed angina at baseline and were followed them up in 3-10 years, including monitoring vital status. Multivariate Cox regression models were employed to examine all-cause mortality in relation to low SES. Results: The cohort follow-up identified 373 deaths occurred; 41 deaths in 208 angina patients. Compared to participants without angina (n=2,172), patients with angina had increased mortality (multivariate adjusted hazard ratio (HR) was 1.41, 95% CI 1.01-1.97). Within angina patients, the risk of mortality increased with low satisfactory income (2.51, 1.08-5.85) and having financial problem (4.00, 1.07-15.00), but significantly with levels of education and occupation. In non-angina participants, none of these four SES indicators were associated with mortality. There was a significant interaction effect between angina and low satisfactory income on mortality. Conclusions: In China, having low income and financial problem increase mortality in older people with angina. Strategies to improve economic circumstances in older people could help reduce inequality in angina survival.

Keywords: angina, mortality, older people, socio-economic status

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Authors: H. J. Wattimanela, U. S. Passaribu, N. T. Puspito, S. W. Indratno

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Banda Sea collision zone (BSCZ) of is the result of the interaction and convergence of Indo-Australian plate, Eurasian plate and Pacific plate. This location in the eastern part of Indonesia. This zone has a very high seismic activity. In this research, we will be calculated rate (λ) and Mean Square Eror (MSE). By this result, we will identification of Poisson distribution of earthquakes in the BSCZ with the point process approach. Chi-square test approach and test Anscombe made in the process of identifying a Poisson distribution in the partition area. The data used are earthquakes with Magnitude ≥ 6 SR and its period 1964-2013 and sourced from BMKG Jakarta. This research is expected to contribute to the Moluccas Province and surrounding local governments in performing spatial plan document related to disaster management.

Keywords: molluca banda sea collision zone, earthquakes, mean square error, poisson distribution, chi-square test, anscombe test

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Authors: David Loh, Wan Chee Wai, Pei Nan, Chen Zhe

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To increase the conveyance capacity to Western Singapore and to meet Singapore’s long-term water needs in a more cost-effective manner, four new transmission pipelines consisting of two 2200 mm diameter water pipes and two 1200mm diameter water pipes will be needed by 2024 to convey water from a Water Reclamation Plant to existing networks in the west region of Singapore. Out of the several possible routes studied, the most cost-effective and technically feasible route was selected to lay the proposed 1.6km-long pipelines that cross a channel via a 6m diameter subsea tunnel. This paper outlines the challenges the team faced throughout the project thus far. It also examined the difficulties such as (1) construction of a 56m-deep launching shaft near a highly sensitive 700mm diameter Gas Transmission Pipeline (GTP) and at a location with high groundwater; (2) manpower and supply disruptions caused by the COVID-19 pandemic situation.

Keywords: underwater tunnel, subsea engineering, subsea tunnel construction, waterpipe construction

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Authors: Alvaro Javier Ortega

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A large number of companies face the challenge of matching highly-skilled professionals to high-end positions by human resource deployment professionals. However, when the professional list and tasks to be matched are larger than a few dozens, this process result is far from optimal and takes a long time to be made. Therefore, an automated assignment algorithm for this workforce management problem is needed. The majority of companies are divided into several sectors or departments, where trained employees with different experience levels deal with a large number of tasks daily. Also, the execution order of all tasks is of mater consequence, due to some of these tasks just can be run it if the result of another task is provided. Thus, a wrong execution order leads to large waiting times between consecutive tasks. The desired goal is, therefore, creating accurate matches and a near-optimal execution order that maximizes the number of tasks performed and minimizes the idle time of the expensive skilled employees. The problem described before can be model as a mixed-integer non-linear programming (MINLP) as it will be shown in detail through this paper. A large number of MINLP algorithms have been proposed in the literature. Here, genetic algorithm solutions are considered and a comparison between two different mutation approaches is presented. The simulated results considering different complexity levels of assignment decisions show the appropriateness of the proposed model.

Keywords: employees, genetic algorithm, industry management, workforce

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Authors: Muhardiyan Erawan, Zaenal Mutaqin

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Balingara River is one of the rivers with the type Gravel-Bed in Indonesia. Gravel-Bed Rivers easily deformed in a relatively short time due to several variables, that are climate (rainfall), river discharge, topography, rock types, and land cover. To determine stream channel changes in Balingara River used Landsat 7 and 8 and analyzed planimetric or two dimensions. Parameters to determine changes in the stream channel are sinuosity ratio, Brice Index, the extent of erosion and deposition. Changes in stream channel associated with changes in land cover then analyze with a descriptive analysis of spatial and temporal. The location of a stream channel has a low gradient in the upstream, and middle watershed with the type of rock in the form of gravel is more easily changed than other locations. Changes in the area of erosion and deposition influence the land cover changes.

Keywords: Brice Index, erosion, deposition, gravel-bed, land cover change, sinuosity ratio, stream channel change

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Authors: Jiao Sun, Li Pan, Shijun Liu

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Recommender systems have been widely used in contemporary industry, and plenty of work has been done in this field to help users to identify items of interest. Collaborative Filtering (CF, for short) algorithm is an important technology in recommender systems. However, less work has been done in automobile recommendation system with the sharp increase of the amount of automobiles. What’s more, the computational speed is a major weakness for collaborative filtering technology. Therefore, using MapReduce framework to optimize the CF algorithm is a vital solution to this performance problem. In this paper, we present a recommendation of the users’ comment on industrial automobiles with various properties based on real world industrial datasets of user-automobile comment data collection, and provide recommendation for automobile providers and help them predict users’ comment on automobiles with new-coming property. Firstly, we solve the sparseness of matrix using previous construction of score matrix. Secondly, we solve the data normalization problem by removing dimensional effects from the raw data of automobiles, where different dimensions of automobile properties bring great error to the calculation of CF. Finally, we use the MapReduce framework to optimize the CF algorithm, and the computational speed has been improved times. UV decomposition used in this paper is an often used matrix factorization technology in CF algorithm, without calculating the interpolation weight of neighbors, which will be more convenient in industry.

Keywords: collaborative filtering, recommendation, data normalization, mapreduce

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Authors: S. R. Santhanam

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A gifted child is one who gives evidence of creativity, good memory, rapid learning. In mathematics, a teacher often comes across some gifted children and they exhibit the following characteristics: unusual alertness, enjoying solving problems, getting bored on repetitions, self-taught, going beyond what teacher taught, ask probing questions, connecting unconnected concepts, vivid imagination, readiness for research work, perseverance of a topic. There are two main areas of research carried out on them: 1)identifying gifted children, 2) interacting and channelizing them. A lack of appropriate recognition will lead the gifted child demotivated. One of the main findings is if proper attention and nourishment are not given then it leads a gifted child to become depressed, underachieving, fail to reach their full potential and sometimes develop negative attitude towards school and study. After identifying them, a mathematics teacher has to develop them into a fall fledged achiever. The responsibility of the teacher is enormous. The teacher has to be resourceful and patient. But interacting with them one finds a lot of surprises and awesomeness. The elementary algebraic identities like (a+b)(a-b)=a²-b², expansion of like (a+b)²(a-b)² and others are taught to students, of age group 13-15 in India. An average child will be satisfied with a single proof and immediate application of these identities. But a gifted child expects more from the teacher and at one stage after a little training will surpass the teacher also. In this short paper, the author shares his experience regarding teaching algebraic identities to gifted children. The following problem was given to a set of 10 gifted children of the specified age group: If a natural number ‘n’ to expressed as the sum of the two squares, will 2n also be expressed as the sum of two squares? An investigation has been done on what multiples of n satisfying the criterion. The attempts of the gifted children were consolidated and conclusion was drawn. A second problem was given to them as: can two natural numbers be found such that the difference of their square is 3? After a successful solution, more situations were analysed. As a third question, the finding of the sign of an algebraic expression in three variables was analysed. As an example: if a,b,c are real and unequal what will be sign of a²+4b²+9c²-4ab-12bc-6ca? Apart from an expression as a perfect square what other methods can be employed to prove an algebraic expression as positive negative or non negative has been analysed. Expressions like 4x²+2y²+13y²-2xy-4yz-6zx were given, and the children were asked to find the sign of the expression for all real values of x,y and z. In all investigations, only basic algebraic identities were used. As a next probe, a divisibility problem was initiated. When a,b,c are natural numbers such that a+b+c is at least 6, and if a+b+c is divisible by 6 then will 6 divide a³+b³+c³. The gifted children solved it in two different ways.

Keywords: algebraic identities, gifted children, Indian scenario, research

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Authors: Paolo Fantozzi, Luigi Laura, Umberto Nanni

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The problem of Entity relation discovery in structured data, a well covered topic in literature, consists in searching within unstructured sources (typically, text) in order to find connections among entities. These can be a whole dictionary, or a specific collection of named items. In many cases machine learning and/or text mining techniques are used for this goal. These approaches might be unfeasible in computationally challenging problems, such as processing massive data streams. A faster approach consists in collecting the cooccurrences of any two words (entities) in order to create a graph of relations - a cooccurrence graph. Indeed each cooccurrence highlights some grade of semantic correlation between the words because it is more common to have related words close each other than having them in the opposite sides of the text. Some authors have used sliding windows for such problem: they count all the occurrences within a sliding windows running over the whole text. In this paper we generalise such technique, coming up to a Weighted-Distance Sliding Window, where each occurrence of two named items within the window is accounted with a weight depending on the distance between items: a closer distance implies a stronger evidence of a relationship. We develop an experiment in order to support this intuition, by applying this technique to a data set consisting in the text of the Bible, split into verses.

Keywords: cooccurrence graph, entity relation graph, unstructured text, weighted distance

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Authors: Sagri Sharma

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Analysis of diseases integrating multi-factors increases the complexity of the problem and therefore, development of frameworks for the analysis of diseases is an issue that is currently a topic of intense research. Due to the inter-dependence of the various parameters, the use of traditional methodologies has not been very effective. Consequently, newer methodologies are being sought to deal with the problem. Supervised Learning Algorithms are commonly used for performing the prediction on previously unseen data. These algorithms are commonly used for applications in fields ranging from image analysis to protein structure and function prediction and they get trained using a known dataset to come up with a predictor model that generates reasonable predictions for the response to new data. Gene expression profiles generated by DNA analysis experiments can be quite complex since these experiments can involve hypotheses involving entire genomes. The application of well-known machine learning algorithm - Support Vector Machine - to analyze the expression levels of thousands of genes simultaneously in a timely, automated and cost effective way is thus used. The objectives to undertake the presented work are development of a methodology to identify genes relevant to Hepatocellular Carcinoma (HCC) from gene expression dataset utilizing supervised learning algorithms and statistical evaluations along with development of a predictive framework that can perform classification tasks on new, unseen data.

Keywords: artificial intelligence, biomarker, gene expression datasets, hepatocellular carcinoma, machine learning, supervised learning algorithms, support vector machine

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Authors: Nagi Mekhiel

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Many applications use vector operations by applying single instruction to multiple data that map to different locations in conventional memory. Transferring data from memory is limited by access latency and bandwidth affecting the performance gain of vector processing. We present a memory system that makes all of its content available to processors in time so that processors need not to access the memory, we force each location to be available to all processors at a specific time. The data move in different orbits to become available to other processors in higher orbits at different time. We use this memory to apply parallel vector operations to data streams at first orbit level. Data processed in the first level move to upper orbit one data element at a time, allowing a processor in that orbit to apply another vector operation to deal with serial code limitations inherited in all parallel applications and interleaved it with lower level vector operations.

Keywords: Memory Organization, Parallel Processors, Serial Code, Vector Processing

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Authors: Ellen Van Den Oord, Julien Marie Jan Ferdinand Van Campen

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This article introduces a computationally efficient method for stacking sequence blending of composite structures. The computational efficiency makes the presented method especially interesting for composite structures with a large number of design regions. Optimization of composite structures with an unequal load distribution may lead to locally optimized thicknesses and ply orientations that are incompatible with one another. Blending constraints can be enforced to achieve structural continuity. In literature, many methods can be found to implement structural continuity by means of stacking sequence blending in one way or another. The complexity of the problem makes the blending of a structure with a large number of adjacent design regions, and thus stacking sequences, prohibitive. In this work the local stacking sequence optimization is preconditioned using a method found in the literature that couples the mechanical behavior of the laminate, in the form of lamination parameters, to blending constraints, yielding near-optimal easy-to-blend designs. The preconditioned design is then fed to the scheme using cellular automata that have been developed by the authors. The method is applied to the benchmark 18-panel horseshoe blending problem to demonstrate its performance. The computational efficiency of the proposed method makes it especially suited for composite structures with a large number of design regions.

Keywords: composite, blending, optimization, lamination parameters

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Authors: Khondaker Sakil Ahmed, Ang Kok Keng, Shah Md Muniruzzaman

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Spherical and Berkovich indentation tests are carried out numerically using finite element method for uniformly dispersed Carbon Nanotube (CNT) in the polymer matrix in which perfectly bonded CNT/matrix interface is considered. The Large strain elasto-plastic analysis is performed to investigate the actual scenario of nanoindentation test. This study investigates how the addition of CNT in polymer matrix influences the mechanical properties like hardness, elastic modulus of the nanocomposite. Since the wall thickness to radius ratio (t/r) is significantly small for SWCNT there is a huge possibility of lateral buckling which is a function of the location of indentation tip as well as the mechanical properties of matrix. Separate finite element models are constructed to compare the result with Berkovich indentation. This study also investigates the buckling behavior of different nanotube in a different polymer matrix.

Keywords: carbon nanotube, elasto-plastic, finite element model, nano-indentation

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Authors: Rob Leslie, Taher Karimian

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The blockage of cross drainage structures is a risk that needs to be understood and managed or lessened through the design. A blockage is a random event, influenced by site-specific factors, which needs to be quantified for design. Under and overestimation of blockage can have major impacts on flood risk and cost associated with drainage structures. The importance of this matter is heightened for those projects located within sensitive lands. It is a particularly complex problem for large linear infrastructure projects (e.g., rail corridors) located within floodplains where blockage factors can influence flooding upstream and downstream of the infrastructure. The selection of the appropriate blockage factors for hydraulic modeling has been subject to extensive research by hydraulic engineers. This paper has been prepared to review the current Australian Rainfall and Runoff 2019 (ARR 2019) methodology for blockage assessment by applying this method to a transport corridor brownfield upgrade case study in New South Wales. The results of applying the method are also validated against asset data and maintenance records. ARR 2019 – Book 6, Chapter 6 includes advice and an approach for estimating the blockage of bridges and culverts. This paper concentrates specifically on the blockage of cross drainage structures. The method has been developed to estimate the blockage level for culverts affected by sediment or debris due to flooding. The objective of the approach is to evaluate a numerical blockage factor that can be utilized in a hydraulic assessment of cross drainage structures. The project included an assessment of over 200 cross drainage structures. In order to estimate a blockage factor for use in the hydraulic model, a process has been advanced that considers the qualitative factors (e.g., Debris type, debris availability) and site-specific hydraulic factors that influence blockage. A site rating associated with the debris potential (i.e., availability, transportability, mobility) at each crossing was completed using the method outlined in ARR 2019 guidelines. The hydraulic results inputs (i.e., flow velocity, flow depth) and qualitative factors at each crossing were developed into an advanced spreadsheet where the design blockage level for cross drainage structures were determined based on the condition relating Inlet Clear Width and L10 (average length of the longest 10% of the debris reaching the site) and the Adjusted Debris Potential. Asset data, including site photos and maintenance records, were then reviewed and compared with the blockage assessment to check the validity of the results. The results of this assessment demonstrate that the estimated blockage factors at each crossing location using ARR 2019 guidelines are well-validated with the asset data. The primary finding of the study is that the ARR 2019 methodology is a suitable approach for culvert blockage assessment that has been validated against a case study spanning a large geographical area and multiple sub-catchments. The study also found that the methodology can be effectively coded within a spreadsheet or similar analytical tool to automate its application.

Keywords: ARR 2019, blockage, culverts, methodology

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Authors: Elmira Shamshity

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This study aimed to explore the economic approach for the Setiu wetland evaluation as a future protection strategy. A questionnaire survey was used based on the single-bounded dichotomous choice, contingent valuation method to differentiate individuals’ Willingness to Pay (WTP) for the conservation of the Setiu wetland. The location of study was Terengganu province in Malaysia. The results of the random questionnaire survey showed that protection of Setiu ecosystem is important to the indigenous community. The mean WTP for protection of ecosystem Setiu wetland was 12.985 Ringgit per month per household for 10 years. There was significant variation in the stated amounts of WTP based on the respondents’ knowledge, household income, educational level, and the bid amounts. The findings of this study may help improving understanding the WTP of indigenous people for the protection of wetland, and providing useful information for policy makers to design an effective program of ecosystem protection.

Keywords: willingness to pay, ecosystem, setiu wetland, Terengganu Malaysia

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Authors: Sidrah Ahmed

Abstract:

The river and lakes flows are modeled mathematically by shallow water equations that are depth-averaged Reynolds Averaged Navier-Stokes equations under Boussinesq approximation. The temperature stratification dynamics influence the water quality and mixing characteristics. It is mainly due to the atmospheric conditions including air temperature, wind velocity, and radiative forcing. The experimental observations are commonly taken along vertical scales and are not sufficient to estimate small turbulence effects of temperature variations induced characteristics of shallow flows. Wind shear stress over the water surface influence flow patterns, heat fluxes and thermodynamics of water bodies as well. Hence it is crucial to couple temperature gradients with shallow water model to estimate the atmospheric effects on flow patterns. The Ripa system has been introduced to study ocean currents as a variant of shallow water equations with addition of temperature variations within the flow. Ripa model is a hyperbolic system of partial differential equations because all the eigenvalues of the system’s Jacobian matrix are real and distinct. The time steps of a numerical scheme are estimated with the eigenvalues of the system. The solution to Riemann problem of the Ripa model is composed of shocks, contact and rarefaction waves. Solving Ripa model with Riemann initial data with the central schemes is difficult due to the eigen structure of the system.This works presents the comparison of four different finite difference schemes for the numerical solution of Riemann problem for Ripa model. These schemes include Lax-Friedrichs, Lax-Wendroff, MacCormack scheme and a higher order finite difference scheme with WENO method. The numerical flux functions in both dimensions are approximated according to these methods. The temporal accuracy is achieved by employing TVD Runge Kutta method. The numerical tests are presented to examine the accuracy and robustness of the applied methods. It is revealed that Lax-Freidrichs scheme produces results with oscillations while Lax-Wendroff and higher order difference scheme produce quite better results.

Keywords: finite difference schemes, Riemann problem, shallow water equations, temperature gradients

Procedia PDF Downloads 203