Search results for: Ekrem Manisali

Authors: Mohammad Lemar Zalmai, Mustafa Nabi Kocakaya, Cemil Akcay, Ekrem Manisali

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In recent years, the Building Information Modeling (BIM) approach has been developed expeditiously. As people see the benefits of this approach, it has begun to be used widely in construction projects and some countries made it mandatory to get more benefits from it. To promote the implementation of BIM in construction projects, it will be helpful to get some relevant information from surveys and interviews. The purpose of this study is to research the current adoption and implementation of BIM in public projects in Turkey. This study specified the challenges of BIM implementation in Turkey and proposed some solutions to overcome them. In this context, the challenges for BIM implementation and the factors that affect the BIM usage are determined based on previous academic researches and expert opinions by conducting interviews and questionnaire surveys. Several methods are used to process information in order to obtain weights of different factors to make BIM widespread in Turkey. This study concluded interviews' and questionnaire surveys' outcomes and proposed some suggestions to promote the implementation of BIM in Turkey. We believe research findings will be a good reference for boosting BIM implementation in Turkey.

Keywords: building information modelling, BIM implementations, Turkish construction industry, Turkish government sector projects

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Authors: Mohammad Lemar Zalmai, Osman Hurol Turkakin, Cemil Akcay, Ekrem Manisali

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Most of the construction projects are exposed to time and cost overruns due to various factors and this is a major problem. As a solution to this, the Earned Value Management (EVM) method is considered. EVM is a powerful and well-known method used in monitoring and controlling the project. EVM is a technique that project managers use to track the performance of their project against project baselines. EVM gives an early indication that either project is delayed or not, and the project is either over budget or under budget at any particular day by tracking it. Thus, it helps to improve the management control system of a construction project, to detect and control the problems in potential risk areas and to suggest the importance and purpose of monitoring the construction work. This paper explains the main parameters of the EVM system involved in the calculation of time and cost for construction projects. In this study, the project management software Primavera P6 is used to deals with the project monitoring process of a seven-storeyed (G+6) faculty building whose construction is in progress at Istanbul, Turkey. A comparison between the planned progress of construction activities and actual progress is performed, and the analysis results are interpreted. This case study justifies the benefits of using EVM for project cash flow analysis and forecasting.

Keywords: earned value management (EVM), construction cost management, construction planning, primavera P6, project management, project scheduling

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Authors: Mohammad Lemar Zalmai, Osman Hurol Turkakin, Cemil Akcay, Ekrem Manisali

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In public construction projects, determining the contract period in the award phase is one of the most important factors. The contract period establishes the baseline for creating the cash flow curve and progress payment planning in the post-award phase. If overestimated, project duration causes losses for both the owner and the contractor. Therefore, it is essential to base construction project duration on reliable forecasting. In Turkey, schedules are usually built using the bar chart (Gantt) schedule, especially for governmental construction agencies. The usage of these schedules is limited for bidding purposes. Although the bar-chart schedule is useful in some cases, it lacks logical connections between activities; it would be harder to obtain the activities that have more effects than others on the project's total duration, especially in large complex projects. In this study, a construction schedule is prepared with Critical Path Method (CPM) that addresses the above-mentioned discrepancies. CPM is a simple and effective method that displays project time and critical paths, showing results of forward and backward calculations with considering the logic relationships between activities; it is a powerful tool for planning and managing all kinds of construction projects and is a very convenient method for the construction industry. CPM provides a much more useful and precise approach than traditional bar-chart diagrams that form the basis of construction planning and control. CPM has two main application utilities in the construction field; the first one is obtaining project duration, which is called an as-planned schedule that includes as-planned activity durations with relationships between subsequent activities. Another utility is during the project execution; each activity is tracked, and their durations are recorded in order to obtain as-built schedule, which is named as a black box of the project. The latter is more useful for delay analysis, and conflict resolutions. These features of CPM have been popular around the world. However, it has not been yet extensively used in Turkey. In this study, a real construction project is investigated as a case study; CPM-based scheduling is used for establishing both of as-built and as-planned schedules. Problems that emerged during the construction phase are identified and categorized. Subsequently, solutions are suggested. Two scenarios were considered. In the first scenario, project progress was monitored based as CPM was used to track and manage progress; this was carried out based on real-time data. In the second scenario, project progress was supposedly tracked based on the assumption that the Gantt chart was used. The S-curves of the two scenarios are plotted and interpreted. Comparing the results, possible faults of the latter scenario are highlighted, and solutions are suggested. The importance of CPM implementation has been emphasized and it has been proposed to make it mandatory for preparation of construction schedule based on CPM for public construction projects contracts.

Keywords: as-built, case-study, critical path method, Turkish government sector projects

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Authors: Ekrem Aksoy, Nihat Adar, Selçuk Canbek

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Ambient Computing or Ambient Intelligence (AmI) is emerging area in computer science aiming to create intelligently connected environments and Internet of Things. In this paper, we propose communication middleware architecture for AmI. This middleware architecture addresses problems of communication, networking, and abstraction of applications, although there are other aspects (e.g. HCI and Security) within general AmI framework. Within this middleware architecture, any application developer might address HCI and Security issues with extensibility features of this platform.

Keywords: AmI, ambient computing, middleware, distributed-systems, software-defined networking

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Authors: Güneş Aydın, Razi Kalantari Osgouei, Murat Emre Öztürk, Ahmad Partovi Meran, Ekrem Tüfekçi

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Advanced lightweight laminated composite shells are increasingly being used in all types of modern structures, for enhancing their structural efficiency and performance. Such thin-walled structures are susceptible to buckling when subjected to various loading. This paper focuses on the buckling of cylindrical shells under axial compression and torsional loads. Effects of fiber orientation on the maximum buckling load of carbon fiber reinforced polymer (CFRP) shells are optimized. Optimum fiber angles have been calculated analytically by using MATLAB program. Numerical models have been carried out by using Finite Element Method program ABAQUS. Results from analytical and numerical analyses are also compared.

Keywords: buckling, composite, cylindrical shell, finite element, compression, torsion, MATLAB, optimization

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Authors: Ashkan Zakaryazad, Ekrem Duman

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A typical classification technique ranks the instances in a data set according to the likelihood of belonging to one (positive) class. A credit card (CC) fraud detection model ranks the transactions in terms of probability of being fraud. In fact, this approach is often criticized, because firms do not care about fraud probability but about the profitability or costliness of detecting a fraudulent transaction. The key contribution in this study is to focus on the profit maximization in the model building step. The artificial neural network proposed in this study works based on profit maximization instead of minimizing the error of prediction. Moreover, some studies have shown that the back propagation algorithm, similar to other gradient–based algorithms, usually gets trapped in local optima and swarm-based algorithms are more successful in this respect. In this study, we train our profit maximization ANN using the Migrating Birds optimization (MBO) which is introduced to literature recently.

Keywords: neural network, profit-based neural network, sum of squared errors (SSE), MBO, gradient descent

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Authors: Ekrem Erdem, Can Tansel Tugcu

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Improved resource efficiency of production is a key requirement for sustainable growth, worldwide. In this regards, by considering the energy and tourism as the extra inputs to the classical Coub-Douglas production function, this study aims at investigating the efficiency changes in the North African countries. To this end, the study uses panel data for the period 1995-2010 and adopts the Malmquist index based on the data envelopment analysis. Results show that tourism increases technical and scale efficiencies, while it decreases technological and total factor productivity changes. On the other hand, when the production function is augmented by the energy input, technical efficiency change decreases, while the technological change, scale efficiency change and total factor productivity change increase. Thus, in order to satisfy the needs for sustainable growth, North African governments should take some measures for increasing the contribution that the tourism makes to economic growth and some others for efficient use of resources in the energy sector.

Keywords: data envelopment analysis, economic efficiency, North African countries, sustainable growth

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Authors: Ekrem Canli, Thomas Glade

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The precise prediction of rainfall in space and time is a key element to most landslide early warning systems. Unfortunately, the spatial variability of rainfall in many early warning applications is often disregarded. A common simplification is to use uniformly distributed rainfall to characterize aerial rainfall intensity. With spatially differentiated rainfall information, real-time comparison with rainfall thresholds or the implementation in process-based approaches might form the basis for improved landslide warnings. This study suggests an automated workflow from the hourly, web-based collection of rain gauge data to the generation of spatially differentiated rainfall predictions based on kriging. Because the application of kriging is usually a labor intensive task, a simplified and consequently automated variogram modeling procedure was applied to up-to-date rainfall data. The entire workflow was carried out purely with open source technology. Validation results, albeit promising, pointed out the challenges that are involved in pure distance based, automated geostatistical interpolation techniques for ever-changing environmental phenomena over short temporal and spatial extent.

Keywords: kriging, landslide early warning system, spatial rainfall prediction, variogram modelling, web scraping

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Authors: Mert Kıranç, Ekrem Duman, Murat Özbilen

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In order to achieve new product development (NPD) activities on time and within budgetary constraints, the NPD managers need a well-designed methodology. This study intends to create an integrated project management methodology for the ones who focus on new product development projects. In the scope of the study, four different management systems are combined. These systems are called as 'Schedule-oriented Stage-Gate Method, Risk Management, Change Management and Earned Value Management'. New product development term is quite common in many different industries such as defense industry, construction, health care/dental, higher education, fast moving consumer goods, white goods, electronic devices, marketing and advertising and software development. All product manufacturers run against each other’s for introducing a new product to the market. In order to achieve to produce a more competitive product in the market, an optimum project management methodology is chosen, and this methodology is adapted to company culture. The right methodology helps the company to present perfect product to the customers at the right time. The benefits of proposed methodology are discussed as an application by a company. As a result, how the integrated methodology improves the efficiency and how it achieves the success of the project are unfolded.

Keywords: project, project management, management methodology, new product development, risk management, change management, earned value, stage-gate

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Authors: H. Selcuk Halkacı, Mevlüt Türköz, Ekrem Öztürk, Murat Dilmec

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Various attempts concerning the low formability issue for lightweight materials like aluminium and magnesium alloys are being investigated in many studies. Advanced forming processes such as hydroforming is one of these attempts. In last decades sheet hydroforming process has an increasing interest, particularly in the automotive and aerospace industries. This process has many advantages such as enhanced formability, the capability to form complex parts, higher dimensional accuracy and surface quality, reduction of tool costs and reduced die wear compared to the conventional sheet metal forming processes. There are two types of sheet hydroforming. One of them is hydromechanical deep drawing (HDD) that is a special drawing process in which pressurized fluid medium is used instead of one of the die half compared to the conventional deep drawing (CDD) process. Another one is sheet hydroforming with die (SHF-D) in which blank is formed with the act of fluid pressure and it takes the shape of die half. In this study, transition of cup height according to cup diameter between the processes was determined by performing simulation of the processes in Finite Element Analysis. Firstly SHF-D process was simulated for 40 mm cup diameter at different cup heights chancing from 10 mm to 30 mm and the cup height to diameter ratio value in which it is not possible to obtain a successful forming was determined. Then the same ratio was checked for a different cup diameter of 60 mm. Then thickness distributions of the cups formed by SHF-D and HDD processes were compared for the cup heights. Consequently, it was found that the thickness distribution in HDD process in the analyses was more uniform.

Keywords: finite element analysis, HDD, hydroforming sheet metal forming, SHF-D

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Authors: Mehmet Halkaci, Ekrem Öztürk, Mevlüt Türköz, H. Selçuk Halkacı

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Hydromechanical deep drawing (HMD) process is an advanced manufacturing process used to form deep parts with only one forming step. In this process, sheet metal blank can be drawn deeper by means of fluid pressure acting on sheet surface in the opposite direction of punch movement. High limiting drawing ratio, good surface quality, less springback characteristic and high dimensional accuracy are some of the advantages of this process. The performance of the HMD process is affected by various process parameters such as fluid pressure, blank holder force, punch-die radius, pre-bulging pressure and height, punch diameter, friction between sheet-die and sheet-punch. The fluid pressure and bank older force are the main loading parameters and affect the formability of HMD process significantly. The punch diameter also influences the limiting drawing ratio (the ratio of initial sheet diameter to punch diameter) of the sheet metal blank. In this research, optimal loading (fluid pressure and blank holder force) profiles were determined for AA 5754-O sheet material through fuzzy control algorithm developed in previous study using LS-DYNA finite element analysis (FEA) software. In the preceding study, the fuzzy control algorithm was developed utilizing geometrical criteria such as thinning and wrinkling. In order to obtain the final desired part with the developed algorithm in terms of the punch diameter requested, the effect of punch diameter, which is the one of the process parameters, on loading profiles was investigated separately using blank thickness of 1 mm. Thus, the practicality of the previously developed fuzzy control algorithm with different punch diameters was clarified. Also, thickness distributions of the sheet metal blank along a curvilinear distance were compared for the FEA in which different punch diameters were used. Consequently, it was found that the use of different punch diameters did not affect the optimal loading profiles too much.

Keywords: Finite Element Analysis (FEA), fuzzy control, hydromechanical deep drawing, optimal loading profiles, punch diameter

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Authors: Taylan Kabbani, Ekrem Duman

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The design of adaptive systems that take advantage of financial markets while reducing the risk can bring more stagnant wealth into the global market. However, most efforts made to generate successful deals in trading financial assets rely on Supervised Learning (SL), which suffered from various limitations. Deep Reinforcement Learning (DRL) offers to solve these drawbacks of SL approaches by combining the financial assets price "prediction" step and the "allocation" step of the portfolio in one unified process to produce fully autonomous systems capable of interacting with its environment to make optimal decisions through trial and error. In this paper, a continuous action space approach is adopted to give the trading agent the ability to gradually adjust the portfolio's positions with each time step (dynamically re-allocate investments), resulting in better agent-environment interaction and faster convergence of the learning process. In addition, the approach supports the managing of a portfolio with several assets instead of a single one. This work represents a novel DRL model to generate profitable trades in the stock market, effectively overcoming the limitations of supervised learning approaches. We formulate the trading problem, or what is referred to as The Agent Environment as Partially observed Markov Decision Process (POMDP) model, considering the constraints imposed by the stock market, such as liquidity and transaction costs. More specifically, we design an environment that simulates the real-world trading process by augmenting the state representation with ten different technical indicators and sentiment analysis of news articles for each stock. We then solve the formulated POMDP problem using the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm, which can learn policies in high-dimensional and continuous action spaces like those typically found in the stock market environment. From the point of view of stock market forecasting and the intelligent decision-making mechanism, this paper demonstrates the superiority of deep reinforcement learning in financial markets over other types of machine learning such as supervised learning and proves its credibility and advantages of strategic decision-making.

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

Procedia PDF Downloads 178