Search results for: Protein Structure Data.

Authors: S. Jeyarajan

Abstract:

Concept of knowledge is discovered from conducted study for successive Competition in Sri Lankan Non-State Higher Educational Institutes. The Concept discovered out of collected Knowledge Management Practices from Emerald inside likewise reputed literatures and of Non-State Higher Educational sector. A test is conducted to reveal existences and its reason behind of these collected practices in Sri Lankan Non-State Higher Education Institutes. Further, unavailability of such study and uncertain on number of participants for data collection in the Sri Lankan context contributed selection of research method as qualitative method, which used attributes of Delphi Method to manage those likewise uncertainty. Data are collected under Dramaturgical Method, which contributes efficient usage of the Delphi method. Grounded theory is selected as data analysis techniques, which is conducted in intermixed discourse to manage different perspectives of data that are collected systematically through perspective and modified snowball sampling techniques. Data are then analysed using Grounded Theory Development Techniques in Intermix discourses to manage differences in Data. Consequently, Agreement in the results of Grounded theories and of finding in the Foreign Study is discovered in the analysis whereas present study conducted as Qualitative Research and The Foreign Study conducted as Quantitative Research. As such, the Present study widens the discovery in the Foreign Study. Further, having discovered reason behind of the existences, the Present result shows Concept for Knowledge from Sri Lankan Non-State sector to manage higher educational Institutes in successful manner.

Keywords: Adherence of snowball sampling into perspective sampling, Delphi method in qualitative method, grounded theory development in intermix discourses of analysis, knowledge management for success of higher educational institutes.

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Authors: M. K. Pradhan, C. K. Biswas,

Abstract:

In the current research, neuro-fuzzy model and regression model was developed to predict Material Removal Rate in Electrical Discharge Machining process for AISI D2 tool steel with copper electrode. Extensive experiments were conducted with various levels of discharge current, pulse duration and duty cycle. The experimental data are split into two sets, one for training and the other for validation of the model. The training data were used to develop the above models and the test data, which was not used earlier to develop these models were used for validation the models. Subsequently, the models are compared. It was found that the predicted and experimental results were in good agreement and the coefficients of correlation were found to be 0.999 and 0.974 for neuro fuzzy and regression model respectively

Keywords: Electrical discharge machining, material removal rate, neuro-fuzzy model, regression model, mountain clustering.

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Authors: Maria Diogo, Patrícia Diogo

Abstract:

The stone is a constituent part of the geological structure of the Territory, introducing himself as a subject that has always interconnected human and environment in the development of a discourse of meanings and symbols that reflect elements realized in different cultures and experiences. This action meant that the first settlements and their areas of influence gained importance in the field of humanization and spatial organization of the territory, not only for the appropriation that its inhabitants did, but mainly because the community regardless of their economic or social condition, used it as living space and cultural integration. These factors become decisive in the characterization of the landscape area in the northwest of Portugal, because the stone is a material that appears not only in the natural landscape, but is also a strong element in humanized landscape, becoming this relation the main characterization of the study area.

Keywords: Landscape, Men, Stone, Territory.

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Authors: Muhammad Tayyab, Saba Saira

Abstract:

It is an established fact that organizations across the globe consider employees as their assets and try to advance their well-being. However, the local firms of developing countries are mostly profit oriented and do not have much concern about their employees’ engagement or commitment. Like other developing countries, the local organizations of Pakistan are also less concerned about the well-being of their employees. Especially public sector organizations lack concern regarding engagement, satisfaction or commitment of the employees. Therefore, this study aimed at investigating the impact of job recognition and job motivation on organizational commitment in the mediation role of employee engagement. The data were collected from land record officers of board of revenue, Punjab, Pakistan. Structured questionnaire was used to collect data through physically visiting land record officers and also through the internet. A total of 318 land record officers’ responses were finalized to perform data analysis. The data were analyzed through confirmatory factor analysis and structural equation modeling technique. The findings revealed that job recognition and job motivation have direct as well as indirect positive and significant impact on organizational commitment. The limitations, practical implications and future research indications are also explained.

Keywords: Job motivation, job recognition, employee engagement, employee commitment, public sector, land record officers.

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Authors: Thach D. Do, Juhum Kwon, Chang-Joo Moon

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A Ground Control System (GCS), which controls Unmanned Aerial Vehicles (UAVs) and monitors their missionrelated data, is one of the major components of UAVs. In fact, some traditional GCSs were built on an expensive, complicated hardware infrastructure with workstations and PCs. In contrast, a GCS on a portable device – such as an Android phone or tablet – takes advantage of its light-weight hardware and the rich User Interface supported by the Android Operating System. We implemented that kind of GCS and called it Ground System Software (GSS) in this paper. In operation, our GSS communicates with UAVs or other GSS via TCP/IP connection to get mission-related data, visualizes it on the device-s screen, and saves the data in its own database. Our study showed that this kind of system will become a potential instrument in UAV-related systems and this kind of topic will appear in many research studies in the near future.

Keywords: Android Operating System, Ground Control System, Mobile Device, Unmanned Aerial Vehicle.

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Authors: Chintanu K. Sarmah, Sandhya Samarasinghe, Don Kulasiri, Daniel Catchpoole

Abstract:

Gene expression profiling is rapidly evolving into a powerful technique for investigating tumor malignancies. The researchers are overwhelmed with the microarray-based platforms and methods that confer them the freedom to conduct large-scale gene expression profiling measurements. Simultaneously, investigations into cross-platform integration methods have started gaining momentum due to their underlying potential to help comprehend a myriad of broad biological issues in tumor diagnosis, prognosis, and therapy. However, comparing results from different platforms remains to be a challenging task as various inherent technical differences exist between the microarray platforms. In this paper, we explain a simple ratio-transformation method, which can provide some common ground for cDNA and Affymetrix platform towards cross-platform integration. The method is based on the characteristic data attributes of Affymetrix- and cDNA- platform. In the work, we considered seven childhood leukemia patients and their gene expression levels in either platform. With a dataset of 822 differentially expressed genes from both these platforms, we carried out a specific ratio-treatment to Affymetrix data, which subsequently showed an improvement in the relationship with the cDNA data.

Keywords: Gene expression profiling, microarray, cDNA, Affymetrix, childhood leukaemia.

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Authors: Vilasinee Jintalikhitdee, Phusit Phukamchanoad, Sakapas Saengchai

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This research aims to study the level of democratic political culture and the factors that affect the democratic political culture of 5^th and 6^th graders under the authority of Dusit District Office, Bangkok by using stratified sampling for probability sampling and using purposive sampling for non-probability sampling to collect data toward the distribution of questionnaires to 300 respondents. This covers all of the schools under the authority of Dusit District Office. The researcher analyzed the data by using descriptive statistics which include arithmetic mean, standard deviation, and inferential statistics which are Independent Samples T-test (T-test) and One-Way ANOVA (F-test). The researcher also collected data by interviewing the target groups, and then analyzed the data by the use of descriptive analysis. The result shows that 5^th and 6^th graders under the authority of Dusit District Office, Bangkok have exposed to democratic political culture at high level in overall. When considering each part, it found out that the part that has highest mean is “the constitutional democratic governmental system is suitable for Thailand” statement. The part with the lowest mean is “corruption (cheat and defraud) is normal in Thai society” statement. The factor that affects democratic political culture is grade levels, occupations of mothers, and attention in news and political movements.

Keywords: Democratic, Political Culture.

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Authors: A. Ito, S. Okamoto

Abstract:

We constructed an atomic structure model for a PAN-based carbon fiber containing amorphous structures using molecular dynamics methods. It was found that basic physical properties such as crystallinity, Young’s modulus, and thermal conductivity of our model were nearly identical to those of real carbon fibers. We then obtained the tensile strength of a carbon fiber, which has no macro defects. We finally determined that the limitation of the tensile strength was 19 GPa.

Keywords: Amorphous, carbon fiber, molecular dynamics, tensile strength.

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Authors: Jae Chul Cha, Sandeep K. Gupta

Abstract:

The demand for higher performance graphics continues to grow because of the incessant desire towards realism. And, rapid advances in fabrication technology have enabled us to build several processor cores on a single die. Hence, it is important to develop single chip parallel architectures for such data-intensive applications. In this paper, we propose an efficient PIM architectures tailored for computer graphics which requires a large number of memory accesses. We then address the two important tasks necessary for maximally exploiting the parallelism provided by the architecture, namely, partitioning and placement of graphic data, which affect respectively load balances and communication costs. Under the constraints of uniform partitioning, we develop approaches for optimal partitioning and placement, which significantly reduce search space. We also present heuristics for identifying near-optimal placement, since the search space for placement is impractically large despite our optimization. We then demonstrate the effectiveness of our partitioning and placement approaches via analysis of example scenes; simulation results show considerable search space reductions, and our heuristics for placement performs close to optimal – the average ratio of communication overheads between our heuristics and the optimal was 1.05. Our uniform partitioning showed average load-balance ratio of 1.47 for geometry processing and 1.44 for rasterization, which is reasonable.

Keywords: Data Partitioning and Placement, Graphics, PIM, Search Space Reduction.

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Authors: A. Faro, D. Giordano, F. Maiorana

Abstract:

Data mining uses a variety of techniques each of which is useful for some particular task. It is important to have a deep understanding of each technique and be able to perform sophisticated analysis. In this article we describe a tool built to simulate a variation of the Kohonen network to perform unsupervised clustering and support the entire data mining process up to results visualization. A graphical representation helps the user to find out a strategy to optimize classification by adding, moving or delete a neuron in order to change the number of classes. The tool is able to automatically suggest a strategy to optimize the number of classes optimization, but also support both tree classifications and semi-lattice organizations of the classes to give to the users the possibility of passing from one class to the ones with which it has some aspects in common. Examples of using tree and semi-lattice classifications are given to illustrate advantages and problems. The tool is applied to classify macroeconomic data that report the most developed countries- import and export. It is possible to classify the countries based on their economic behaviour and use the tool to characterize the commercial behaviour of a country in a selected class from the analysis of positive and negative features that contribute to classes formation. Possible interrelationships between the classes and their meaning are also discussed.

Keywords: Unsupervised classification, Kohonen networks, macroeconomics, Visual data mining, Cluster interpretation.

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Authors: Selim Yannier, Asif Sabanovic, Ahmet Onat, Muhammet Bastan

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In this work, we suggested a new approach for the control of a mobile robot capable of being a building block of an intelligent agent. This approach includes obstacle avoidance and goal tracking implemented as two different sliding mode controllers. A geometry based behavior arbitration is proposed for fusing the two outputs. Proposed structure is tested on simulations and real robot. Results have confirmed the high performance of the method.

Keywords: Autonomous Mobile Robot, Behavior Based Control, Fast Local Obstacle Avoidance, Sliding Mode Control.

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Authors: Nhien-An Le-Khac, Sammer Markos, M-Tahar Kechadi

Abstract:

Today, money laundering (ML) poses a serious threat not only to financial institutions but also to the nation. This criminal activity is becoming more and more sophisticated and seems to have moved from the cliché of drug trafficking to financing terrorism and surely not forgetting personal gain. Most international financial institutions have been implementing anti-money laundering solutions (AML) to fight investment fraud. However, traditional investigative techniques consume numerous man-hours. Recently, data mining approaches have been developed and are considered as well-suited techniques for detecting ML activities. Within the scope of a collaboration project for the purpose of developing a new solution for the AML Units in an international investment bank, we proposed a data mining-based solution for AML. In this paper, we present a heuristics approach to improve the performance for this solution. We also show some preliminary results associated with this method on analysing transaction datasets.

Keywords: data mining, anti money laundering, clustering, heuristics.

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Authors: Johannes Partzsch, Christian Mayr, Rene Schuffny

Abstract:

Starting from a biologically inspired framework, Gabor filters were built up from retinal filters via LMSE algorithms. Asubset of retinal filter kernels was chosen to form a particular Gabor filter by using a weighted sum. One-dimensional optimization approaches were shown to be inappropriate for the problem. All model parameters were fixed with biological or image processing constraints. Detailed analysis of the optimization procedure led to the introduction of a minimization constraint. Finally, quantization of weighting factors was investigated. This resulted in an optimized cascaded structure of a Gabor filter bank implementation with lower computational cost.

Keywords: Gabor filter, image processing, optimization

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Authors: Kun Sri Budiasih, Chairil Anwar, Sri Juari Santosa, Hilda Ismail

Abstract:

Some Chromium (III) complexes were synthesized with three amino acids: L Glutamic Acid, Glycine, and L-cysteine as the ligands, in order to provide a new supplement containing Cr(III) for patients with type 2 diabetes mellitus. The complexes have been prepared by refluxing a mixture of Chromium(III) chloride in aqueous solution with L-glutamic acid, Glycine, and L-cysteine after pH adjustment by sodium hydroxide. These complexes were characterized by Infrared and Uv-Vis spectrophotometer and Elemental analyzer. The product yields of four products were 87.50 and 56.76% for Cr-Glu complexes, 46.70% for Cr-Gly complex and 40.08% for Cr-Cys complex respectively. The predicted structure of the complexes are [Cr(glu)2(H2O)2].xH2O, Cr(gly)3..xH2O and Cr(cys)3.xH2O., respectively.

Keywords: Cr(III), L-Cysteine L-glutamic Acid, Glycine, complexation.

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Authors: K. Allaw, J. Adjizian Gerard, M. Chehayeb, A. Raad, W. Fahs, A. Badran, A. Fakherdin, H. Madi, N. Badaro Saliba

Abstract:

Population estimation using Geographic Information System (GIS) and remote sensing faces many obstacles such as the determination of permanent residents. A permanent resident is an individual who stays and works during all four seasons in his village. So, all those who move towards other cities or villages are excluded from this category. The aim of this study is to identify the factors affecting the percentage of permanent residents in a village and to determine the attributed weight to each factor. To do so, six factors have been chosen (slope, precipitation, temperature, number of services, time to Central Business District (CBD) and the proximity to conflict zones) and each one of those factors has been evaluated using one of the following data: the contour lines map of 50 m, the precipitation map, four temperature maps and data collected through surveys. The weighting procedure has been done using decision tree method. As a result of this procedure, temperature (50.8%) and percentage of precipitation (46.5%) are the most influencing factors.

Keywords: Remote sensing and GIS, permanent residence, decision tree, Lebanon.

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Authors: Alpha Agape Gopalai, S. M. N. Arosha Senanayake

Abstract:

This paper explores the opportunity of using tri-axial wireless accelerometers for supervised monitoring of sports movements. A motion analysis system for the upper extremities of lawn bowlers in particular is developed. Accelerometers are placed on parts of human body such as the chest to represent the shoulder movements, the back to capture the trunk motion, back of the hand, the wrist and one above the elbow, to capture arm movements. These sensors placement are carefully designed in order to avoid restricting bowler-s movements. Data is acquired from these sensors in soft-real time using virtual instrumentation; the acquired data is then conditioned and converted into required parameters for motion regeneration. A user interface was also created to facilitate in the acquisition of data, and broadcasting of commands to the wireless accelerometers. All motion regeneration in this paper deals with the motion of the human body segment in the X and Y direction, looking into the motion of the anterior/ posterior and lateral directions respectively.

Keywords: Motion Regeneration, Virtual Instrumentation, Wireless Accelerometers.

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Authors: Patience Muchini, Electdom Matandiroya, Emmanuel Mashonjowa

Abstract:

A ground-end manifestation of space weather phenomena is known as geomagnetically induced currents (GICs). GICs flow along the electric power transmission cables connecting the transformers and between the grounding points of power transformers during significant geomagnetic storms. Zimbabwe has no study that notes if grid failures have been caused by GICs. Research and monitoring are needed to investigate this possible relationship purpose of this paper is to characterize GICs with a power grid network. This paper analyses data collected, which are geomagnetic data, which include the Kp index, Disturbance storm time (DST) index, and the G-Scale from geomagnetic storms and also analyses power grid data, which includes reactive power, relay tripping, and alarms from high voltage substations and then correlates the data. This research analysis was first theoretically analyzed by studying geomagnetic parameters and then experimented upon. To correlate, MATLAB was used as the basic software to analyze the data. Latitudes of the substations were also brought into scrutiny to note if they were an impact due to the location as low latitudes areas like most parts of Zimbabwe, there are less severe geomagnetic variations. Based on theoretical and graphical analysis, it has been proven that there is a slight relationship between power system failures and GICs. Further analyses can be done by implementing measuring instruments to measure any currents in the grounding of high-voltage transformers when geomagnetic storms occur. Mitigation measures can then be developed to minimize the susceptibility of the power network to GICs.

Keywords: Adverse space weather, DST index, geomagnetically induced currents, Kp index, reactive power.

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Authors: Lubna Eljabu, Mohammad Etemad, Stan Matwin

Abstract:

The automatic extraction of shipping routes is advantageous for intelligent traffic management systems to identify events and support decision-making in maritime surveillance. At present, there is a high demand for the extraction of maritime traffic networks that resemble the real traffic of vessels accurately, which is valuable for further analytical processing tasks for vessels trajectories (e.g., naval routing and voyage planning, anomaly detection, destination prediction, time of arrival estimation). With the help of big data and processing huge amounts of vessels’ trajectory data, it is possible to learn these shipping routes from the navigation history of past behaviour of other, similar ships that were travelling in a given area. In this paper, we propose a spatial clustering model of vessels’ trajectories (SPTCLUST) to extract spatial representations of sailing routes from historical Automatic Identification System (AIS) data. The whole model consists of three main parts: data preprocessing, path finding, and route extraction, which consists of clustering and representative trajectory extraction. The proposed clustering method provides techniques to overcome the problems of: (i) optimal input parameters selection; (ii) the high complexity of processing a huge volume of multidimensional data; (iii) and the spatial representation of complete representative trajectory detection in the context of trajectory clustering algorithms. The experimental evaluation showed the effectiveness of the proposed model by using a real-world AIS dataset from the Port of Halifax. The results contribute to further understanding of shipping route patterns. This could aid surveillance authorities in stable and sustainable vessel traffic management.

Keywords: Vessel trajectory clustering, trajectory mining, Spatial Clustering, marine intelligent navigation, maritime traffic network extraction, sdailing routes extraction.

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Authors: Mladen Dragičević, Mirjana Pejić Bach, Vanja Šimičević

Abstract:

The purpose of this paper is to develop models that would enable predicting student success. These models could improve allocation of students among colleges and optimize the newly introduced model of government subsidies for higher education. For the purpose of collecting data, an anonymous survey was carried out in the last year of undergraduate degree student population using random sampling method. Decision trees were created of which two have been chosen that were most successful in predicting student success based on two criteria: Grade Point Average (GPA) and time that a student needs to finish the undergraduate program (time-to-degree). Decision trees have been shown as a good method of classification student success and they could be even more improved by increasing survey sample and developing specialized decision trees for each type of college. These types of methods have a big potential for use in decision support systems.

Keywords: Data mining, knowledge discovery in databases, prediction models, student success.

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Authors: Karishma Kashyap, Subha D. Parida

Abstract:

Rapid population growth and urbanization is creating pressure throughout the world. This has a dramatic effect on a lot of elements which include water, food, transportation, energy, infrastructure etc. as few of the key services. Built environment sector is growing concurrently to meet the needs of urbanization. Due to such large scale development of buildings, there is a need for them to be monitored and managed efficiently. Along with appropriate management, climate adaptation is highly crucial as well because buildings are one of the major sources of greenhouse gas emission in their operation phase. Buildings to be adaptive need to provide a triple bottom approach to sustainability i.e., being socially, environmentally and economically sustainable. Hence, in order to deliver these sustainability outcomes, there is a growing understanding and thrive towards switching to green buildings or renovating new ones as per green standards wherever possible. Academic institutions in particular have been following this trend globally. This is highly significant as universities usually have high occupancy rates because they manage a large building portfolio. Also, as universities accommodate the future generation of architects, policy makers etc., they have the potential of setting themselves as a best industry practice model for research and innovation for the rest to follow. Hence their climate adaptation, sustainable growth and performance management becomes highly crucial in order to provide the best services to users. With the objective of evaluating appropriate management mechanisms within academic institutions, a feasibility study was carried out in a recent 5-Star Green Star rated university building (housing the School of Construction) in Victoria (south-eastern state of Australia). The key aim was to understand the behavioral and social aspect of the building users, management and the impact of their relationship on overall building sustainability. A survey was used to understand the building occupant’s response and reactions in terms of their work environment and management. A report was generated based on the survey results complemented with utility and performance data which were then used to evaluate the management structure of the university. Followed by the report, interviews were scheduled with the facility and asset managers in order to understand the approach they use to manage the different buildings in their university campuses (old, new, refurbished), respective building and parameters incorporated in maintaining the Green Star performance. The results aimed at closing the communication and feedback loop within the respective institutions and assist the facility managers to deliver appropriate stakeholder engagement. For the wider design community, analysis of the data highlights the applicability and significance of prioritizing key stakeholders, integrating desired engagement policies within an institution’s management structures and frameworks and their effect on building performance

Keywords: Building Optimization, Green Building, Post Occupancy Evaluation, Stakeholder Engagement.

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Authors: Alireza Azimi Sani , Shahram Chaharmahalie

Abstract:

Internal controls of accounting are an essential business function for a growth-oriented organization, and include the elements of risk assessment, information communications and even employees' roles and responsibilities. Internal controls of accounting systems are designed to protect a company from fraud, abuse and inaccurate data recording and help organizations keep track of essential financial activities. Internal controls of accounting provide a streamlined solution for organizing all accounting procedures and ensuring that the accounting cycle is completed consistently and successfully. Implementing a formal Accounting Procedures Manual for the organization allows the financial department to facilitate several processes and maintain rigorous standards. Internal controls also allow organizations to keep detailed records, manage and organize important financial transactions and set a high standard for the organization's financial management structure and protocols. A well-implemented system also reduces the risk of accounting errors and abuse. A well-implemented controls system allows a company's financial managers to regulate and streamline all functions of the accounting department. Internal controls of accounting can be set up for every area to track deposits, monitor check handling, keep track of creditor accounts, and even assess budgets and financial statements on an ongoing basis. Setting up an effective accounting system to monitor accounting reports, analyze records and protect sensitive financial information also can help a company set clear goals and make accurate projections. Creating efficient accounting processes allows an organization to set specific policies and protocols on accounting procedures, and reach its financial objectives on a regular basis. Internal accounting controls can help keep track of such areas as cash-receipt recording, payroll management, appropriate recording of grants and gifts, cash disbursements by authorized personnel, and the recording of assets. These systems also can take into account any government regulations and requirements for financial reporting.

Keywords: Internal controls, risk assessment, financial management.

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Authors: R. Karami, A. Gharaei

Abstract:

This study was undertaken at four different sites (north polluted, south polluted, south healthy and north healthy) in Tehran, in order to examine whether there was a relationship between publicly available air quality data and the public’s perception of air quality and to suggest some guidelines for reducing air pollution. A total of 200 people were accidentally filled out the research questionnaires at mentioned sites and air quality data were obtained simultaneously from the Air Quality Control Department. Data was analyzed in Excel and SPSS software’s. Clean air and job security were of great importance to people comparing to other pleasant aspect of life. Also air pollution and serious diseases were the most important of people concerns. Street monitors and news paper services on air quality were little used by the public as a means of obtaining information on air pollution. Using public transportation and avoiding inevitable journeys are the most important ways for reducing air pollution. The results reveal that the public’s perception of air quality is not a reliable indicator of the actual levels of air pollution.

Keywords: Air pollution, Quality of life, Opinion poll, Public participation.

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Authors: Yeliz Ekinci, Raife Merve Ön

Abstract:

Nowadays, technological progress is one of the most important components of economic growth and the efficiency of R&D activities is particularly essential for countries. This study is an attempt to analyze the R&D efficiencies of EU countries. The indicators related to R&D efficiencies should be determined in advance in order to use DEA. For this reason a list of input and output indicators are derived from the literature review. Considering the data availability, a final list is given for the numerical analysis for future research.

Keywords: Data envelopment analysis, economic growth, EU Countries, R&D efficiency.

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Authors: M. F. Haroun, T. A. Gulliver

Abstract:

In this paper, an encryption algorithm is proposed for real-time image encryption. The scheme employs a dual chaotic generator based on a three dimensional (3D) discrete Lorenz attractor. Encryption is achieved using non-autonomous modulation where the data is injected into the dynamics of the master chaotic generator. The second generator is used to permute the dynamics of the master generator using the same approach. Since the data stream can be regarded as a random source, the resulting permutations of the generator dynamics greatly increase the security of the transmitted signal. In addition, a technique is proposed to mitigate the error propagation due to the finite precision arithmetic of digital hardware. In particular, truncation and rounding errors are eliminated by employing an integer representation of the data which can easily be implemented. The simple hardware architecture of the algorithm makes it suitable for secure real-time applications.

Keywords: Chaotic systems, image encryption, 3D Lorenz attractor, non-autonomous modulation, FPGA.

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Authors: L. Richter, J. Lübkemann, P. Nyhuis

Abstract:

In order to remain competitive in what is a turbulent environment; businesses must be able to react rapidly to change. The past response to volatile market conditions was to introduce an element of flexibility to production. Nowadays, what is often required is a redesign of factory structures in order to cope with the state of constant flux. The Institute of Production Systems and Logistics is currently developing a descriptive and causal model for the redesign of plant structures as part of an ongoing research project. This article presents the first research findings attained in devising this model.

Keywords: Causal model, change driven factory redesign, factory planning, plant structure.

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Authors: Dilek Özdemir, Gül Tekin Temur

Abstract:

In Supply Chain Management (SCM), strengthening partnerships with suppliers is a significant factor for enhancing competitiveness. Hence, firms increasingly emphasize supplier evaluation processes. Supplier evaluation systems are basically developed in terms of criteria such as quality, cost, delivery, and flexibility. Because there are many variables to be analyzed, this process becomes hard to execute and needs expertise. On this account, this study aims to develop an expert system on supplier evaluation process by designing Artificial Neural Network (ANN) that is supported with Data Envelopment Analysis (DEA). The methods are applied on the data of 24 suppliers, which have longterm relationships with a medium sized company from German Iron and Steel Industry. The data of suppliers consists of variables such as material quality (MQ), discount of amount (DOA), discount of cash (DOC), payment term (PT), delivery time (DT) and annual revenue (AR). Meanwhile, the efficiency that is generated by using DEA is added to the supplier evaluation system in order to use them as system outputs.

Keywords: Artificial Neural Network (ANN), DataEnvelopment Analysis (DEA), Supplier Evaluation System.

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Authors: Vasudha Bhatnagar, Ahmed Sultan Al-Hegami, Naveen Kumar

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Rule Discovery is an important technique for mining knowledge from large databases. Use of objective measures for discovering interesting rules lead to another data mining problem, although of reduced complexity. Data mining researchers have studied subjective measures of interestingness to reduce the volume of discovered rules to ultimately improve the overall efficiency of KDD process. In this paper we study novelty of the discovered rules as a subjective measure of interestingness. We propose a hybrid approach that uses objective and subjective measures to quantify novelty of the discovered rules in terms of their deviations from the known rules. We analyze the types of deviation that can arise between two rules and categorize the discovered rules according to the user specified threshold. We implement the proposed framework and experiment with some public datasets. The experimental results are quite promising.

Keywords: Knowledge Discovery in Databases (KDD), Data Mining, Rule Discovery, Interestingness, Subjective Measures, Novelty Measure.

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Authors: Joo-Han Kim, Jung-Moo Seo, Ha Gyeong Sung, Se Hyun Rhyu

Abstract:

This study presents a blower for air management system of fuel cell modules. A blower is composed of BLDC motor and impeller. Magnetic equivalent circuit model and finite element analysis are used to design the motor, and an improved structure is considered to reduce a mechanical loss induced from bearing units. Finally, air blower system combined with the motor and an impeller is manufactured and output properties, such as an air pressure and an amount of flowing air, are measured. Through the experimental results, a validity of the simulated one is confirmed.

Keywords: Fuel cell modules, BLDC motor, Impeller, Air management

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Authors: Xiaohuan Li, Wangmin Yi, Xinghui Wu

Abstract:

In order to verify the performance of lunar lander structure, landing-impact test is urgently needed. And the test equipment is necessary for the test. The functions and the key points of the equipment are presented to satisfy the requirements of the test, and the design scheme is proposed. The composition, the major function and the critical parts’ design of the equipment are introduced. By the load test of releasing device and single-beam hoist, and the compatibility test of landing-impact testing system, the rationality and reliability of the equipment is proved.

Keywords: Landing-impact test, lunar lander, releasing device, test equipment.

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Authors: Chien-Chun Hung, Chun-Fong Wu

Abstract:

It is important for a commander to have real-time information to aware situations and to make decision in the battlefield. Results of modern technique developments have brought in this kind of information for military purposes. Unmanned aerial vehicle (UAV) is one of the means to gather intelligence owing to its widespread applications. It is still not clear whether or not the mini UAV with short-range wireless transmission system is used as a reconnaissance system in Taiwanese. In this paper, previous experience on the research of the sort of aerial vehicles has been applied with a data-relay system using the ZigBee modulus. The mini UAV developed is expected to be able to collect certain data in some appropriate theaters. The omni-directional antenna with high gain is also integrated into mini UAV to fit the size-reducing trend of airborne sensors. Two advantages are so far obvious. First, mini UAV can fly higher than usual to avoid being attacked from ground fires. Second, the data will be almost gathered during all maneuvering attitudes.

Keywords: Mini UAV, reconnaissance, wireless transmission, ZigBee modulus.

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