Search results for: Genomic analysis.

Authors: Chanchal Biswas, Anrin Bhattacharyya, Gopes Chandra Das, Mahua Ghosh Chaudhuri, Rajib Dey

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Boiler coals with low fixed carbon and higher ash content have always challenged the metallurgists to develop a suitable method for their utilization. In the present study, an attempt is made to establish an energy effective method for the reduction of iron ore fines in the form of nuggets by using ‘Syngas’. By devolatisation (expulsion of volatile matter by applying heat) of boiler coal, gaseous product (enriched with reducing agents like CO, CO2, H2, and CH4 gases) is generated. Iron ore nuggets are reduced by this syngas. For that reason, there is no direct contact between iron ore nuggets and coal ash. It helps to control the minimization of the sulphur intake of the reduced nuggets. A laboratory scale devolatisation furnace designed with reduction facility is evaluated after in-depth studies and exhaustive experimentations including thermo-gravimetric (TG-DTA) analysis to find out the volatile fraction present in boiler grade coal, gas chromatography (GC) to find out syngas composition in different temperature and furnace temperature gradient measurements to minimize the furnace cost by applying one heating coil. The nuggets are reduced in the devolatisation furnace at three different temperatures and three different times. The pre-reduced nuggets are subjected to analytical weight loss calculations to evaluate the extent of reduction. The phase and surface morphology analysis of pre-reduced samples are characterized using X-ray diffractometry (XRD), energy dispersive x-ray spectrometry (EDX), scanning electron microscopy (SEM), carbon sulphur analyzer and chemical analysis method. Degree of metallization of the reduced nuggets is 78.9% by using boiler grade coal. The pre-reduced nuggets with lesser sulphur content could be used in the blast furnace as raw materials or coolant which would reduce the high quality of coke rate of the furnace due to its pre-reduced character. These can be used in Basic Oxygen Furnace (BOF) as coolant also.

Keywords: Alternative ironmaking, coal devolatisation, extent of reduction, nugget making, syngas based DRI, solid state reduction.

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Authors: Sanjeev Kumar Appicharla

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This paper presents the results of the modelling and analysis of the European Railway Traffic Management (ERTMS) safety critical incident to raise awareness of biases in systems engineering process on the Cambrian Railway in the UK using the RAIB 17/2019 as a primary input. The RAIB, the UK independent accident investigator, published the Report- RAIB 17/2019 giving the details of their investigation of the focal event in the form of immediate cause, causal factors and underlying factors and recommendations to prevent a repeat of the safety-critical incident on the Cambrian Line. The Systems for Investigation of Railway Interfaces (SIRI) is the Methodology used to model and analyse the safety-critical incident. The SIRI Methodology uses the Swiss Cheese Model to model the incident and identify latent failure conditions (potentially less than adequate conditions) by means of the Management Oversight and Risk Tree technique. The benefits of the SIRI Methodology are threefold: first is that it incorporates “Heuristics and Biases” approach, in the Management Oversight and Risk Tree technique to identify systematic errors. Civil engineering and programme management railway professionals are aware of role “optimism bias” plays in programme cost overruns and are aware of bow tie (fault and event tree) model-based safety risk modelling technique. However, the role of systematic errors due to “Heuristics and Biases” is not appreciated as yet. This overcomes the problems of omission of human and organisational factors from accident analysis. Second, the scope of the investigation includes all levels of the socio-technical system, including government, regulatory, railway safety bodies, duty holders, signalling firms and transport planners, and front-line staff such that lessons learned at the decision making and implementation level as well. Third, the author’s past accident case studies are supplemented with research pieces of evidence drawn from the practitioner’s and academic researchers’ publications as well. This is to discuss the role of system thinking to improve the decision making and risk management processes and practices in the IEC 15288 Systems Engineering standard, and in the industrial context such as the GB railways and Artificial Intelligence (AI) contexts as well.

Keywords: Accident analysis, AI algorithm internal audit, bounded rationality, Byzantine failures, heuristics and biases approach.

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Authors: Pratch Kittipongpattana, Thongchai Fongsamootr

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This research aimed to study the influences of a soot blowing operation and geometrical variables to the stress characteristic of water wall tubes located in soot blowing areas which caused the boilers of Mae Moh power plant to lose their generation hour. The research method is divided into 2 parts (a) measuring the strain on water wall tubes by using 3-element rosette strain gages orientation during a full capacity plant operation and in periods of soot blowing operations (b) creating a finite element model in order to calculate stresses on tubes and validating the model by using experimental data in a steady state plant operation. Then, the geometrical variables in the model were changed to study stresses on the tubes. The results revealed that the stress was not affected by the soot blowing process and the finite element model gave the results 1.24% errors from the experiment. The geometrical variables influenced the stress, with the most optimum tubes design in this research reduced the average stress from the present design 31.28%.

Keywords: Boiler water wall tube, Finite element, Stress analysis, Strain gage rosette.

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Authors: Fahim Kahlouche, Alaoua Bouaicha, Sihem Chaîbeddra, Sid-Ali Rafa, Abdelhamid Benouali

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A designing of a structure requires its realization on rough or sloping ground. Besides the problem of the stability of the landslide, the behavior of the foundations that are bearing the structure is influenced by the destabilizing effect of the ground’s slope. This article focuses on the analysis of the slope stability exposed to loading by introducing the different factors influencing the slope’s behavior on the one hand, and on the influence of this slope on the foundation’s behavior on the other hand. This study is about the elastoplastic modelization using FLAC 2D. This software is based on the finite difference method, which is one of the older methods of numeric resolution of differential equations system with initial and boundary conditions. It was developed for the geotechnical simulation calculation. The aim of this simulation is to demonstrate the notable effect of shear modulus « G », cohesion « C », inclination angle (edge) « β », and distance between the foundation and the head of the slope on the stability of the slope as well as the stability of the foundation. In our simulation, the slope is constituted by homogenous ground. The foundation is considered as rigid/hard; therefore, the loading is made by the application of the vertical strengths on the nodes which represent the contact between the foundation and the ground. 

Keywords: Slope, shallow foundation, numeric method, FLAC 2D.

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Authors: A. I. A. Rahman, Sh-Hussain Salleh, K. Ahmad, K. Anuar

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Analysis of vocal fold vibration is essential for understanding the mechanism of voice production and for improving clinical assessment of voice disorders. This paper presents a Dynamic Time Warping (DTW) based approach to analyze and objectively classify vocal fold vibration patterns. The proposed technique was designed and implemented on a Glottal Area Waveform (GAW) extracted from high-speed laryngeal images by delineating the glottal edges for each image frame. Feature extraction from the GAW was performed using Linear Predictive Coding (LPC). Several types of voice reference templates from simulations of clear, breathy, fry, pressed and hyperfunctional voice productions were used. The patterns of the reference templates were first verified using the analytical signal generated through Hilbert transformation of the GAW. Samples from normal speakers’ voice recordings were then used to evaluate and test the effectiveness of this approach. The classification of the voice patterns using the technique of LPC and DTW gave the accuracy of 81%.

Keywords: Dynamic Time Warping, Glottal Area Waveform, Linear Predictive Coding, High-Speed Laryngeal Images, Hilbert Transform.

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Authors: Ahmed Kiani

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The United Arab Emirates is clearly facing a multitude of challenges in curbing its greenhouse gas emissions to meet its pre-allotted framework of Kyoto protocol and COP21 targets due to its hunger for modernization, industrialization, infrastructure growth, soaring population and oil and gas activity. In this work, we focus on the bonafide zero emission electric vehicles market penetration in the country’s transport industry for emission reduction. We study the global electric vehicle market trends, the complementary battery technologies and the trends by manufacturers, emission standards across borders and prioritized advancements which will ultimately dictate the terms of future conditions for the United Arab Emirate transport industry. Based on our findings and analysis at every stage of current viability and state-of-transport-affairs, we postulate policy recommendations to local governmental entities from a supply and demand perspective covering aspects of technology, infrastructure requirements, change in power dynamics, end user incentives program, market regulators behavior and communications amongst key stakeholders. 

Keywords: Electric vehicles, greenhouse gas emission reductions, market analysis, policy recommendations.

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Authors: Hamid R. S. Mojaveri, Seyed S. Mousavi, Mojtaba Heydar, Ahmad Aminian

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The aim of this paper is to present a methodology in three steps to forecast supply chain demand. In first step, various data mining techniques are applied in order to prepare data for entering into forecasting models. In second step, the modeling step, an artificial neural network and support vector machine is presented after defining Mean Absolute Percentage Error index for measuring error. The structure of artificial neural network is selected based on previous researchers' results and in this article the accuracy of network is increased by using sensitivity analysis. The best forecast for classical forecasting methods (Moving Average, Exponential Smoothing, and Exponential Smoothing with Trend) is resulted based on prepared data and this forecast is compared with result of support vector machine and proposed artificial neural network. The results show that artificial neural network can forecast more precisely in comparison with other methods. Finally, forecasting methods' stability is analyzed by using raw data and even the effectiveness of clustering analysis is measured.

Keywords: Artificial Neural Networks (ANN), bullwhip effect, demand forecasting, Support Vector Machine (SVM).

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Authors: Kiyoko Yoshimura, Yasunobu Kino

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Focusing on professional call centers where workers with expertise perform services, this study aims to clarify the relationships between emotional labor and job satisfaction and the effects of recognition of customer feedback. Since the professional call center operators consist of professional license holders (qualification holders) and those who do not (non-holders), the following three points are analyzed in the two groups by using covariance structure analysis and simultaneous multi-population analysis: 1) The relationship between emotional labor and job satisfaction, 2) customer feedback and job satisfaction, and 3) the intermediation effect between the emotional labor of customer feedback and job satisfaction. The following results are obtained: i) No direct effect is found between job satisfaction and emotional labor for qualification holders and non-holders, ii) for qualification holders and non-holders, recognition of positive feedback and recognition of negative feedback had positive and negative effects on job satisfaction, respectively, iii) for qualification and non-holders, “consideration for colleagues” influences job satisfaction by recognizing positive feedback, and iv) only for qualification holders, the factors “customer-oriented emotional expression” and “emotional disharmony” have a positive and negative effect on job satisfaction, respectively, through recognition of positive feedback and recognition of negative feedback.

Keywords: Call center, emotional labor, professional service, job satisfaction, customer feedback.

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Authors: Markus Kaiser, Johannes Buchmann

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In this article, a formal specification and verification of the Rabin public-key scheme in a formal proof system is presented. The idea is to use the two views of cryptographic verification: the computational approach relying on the vocabulary of probability theory and complexity theory and the formal approach based on ideas and techniques from logic and programming languages. A major objective of this article is the presentation of the first computer-proved implementation of the Rabin public-key scheme in Isabelle/HOL. Moreover, we explicate a (computer-proven) formalization of correctness as well as a computer verification of security properties using a straight-forward computation model in Isabelle/HOL. The analysis uses a given database to prove formal properties of our implemented functions with computer support. The main task in designing a practical formalization of correctness as well as efficient computer proofs of security properties is to cope with the complexity of cryptographic proving. We reduce this complexity by exploring a light-weight formalization that enables both appropriate formal definitions as well as efficient formal proofs. Consequently, we get reliable proofs with a minimal error rate augmenting the used database, what provides a formal basis for more computer proof constructions in this area.

Keywords: public-key encryption, Rabin public-key scheme, formalproof system, higher-order logic, formal verification.

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Authors: M. M. Rahman, Thamir K. Ibrahim, M. Y. Taib, M. M. Noor, Rosli A. Bakar

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Regenerative gas turbine engine cycle is presented that yields higher cycle efficiencies than simple cycle operating under the same conditions. The power output, efficiency and specific fuel consumption are simulated with respect to operating conditions. The analytical formulae about the relation to determine the thermal efficiency are derived taking into account the effected operation conditions (ambient temperature, compression ratio, regenerator effectiveness, compressor efficiency, turbine efficiency and turbine inlet temperature). Model calculations for a wide range of parameters are presented, as are comparisons with simple gas turbine cycle. The power output and thermal efficiency are found to be increasing with the regenerative effectiveness, and the compressor and turbine efficiencies. The efficiency increased with increase the compression ratio to 5, then efficiency decreased with increased compression ratio, but in simple cycle the thermal efficiency always increase with increased in compression ratio. The increased in ambient temperature caused decreased thermal efficiency, but the increased in turbine inlet temperature increase thermal efficiency.

Keywords: Gas turbine, power plant, thermal analysis, regeneration

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Authors: Amruta Khairnar, Joy Sen

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Disparity in India has been persisting since independence causing many socioeconomic problems and its removal has become the most prime objective of the planned development in India. Hence the paper attempts to study the disparity at State and Regional level and gives inclusive planning guidelines to achieve balanced regional development. At State level, the relative socioeconomic backwardness of Vidarbha Region based on Interregional analysis using selected indicators like Foreign Direct Investment, Human Development Index, Per Capita District Domestic Product has been assessed and broad guidelines have been proposed. In the later part at Regional level, the relative backwardness of districts based on Intraregional analysis using socioeconomic indicators has been assessed within Nagpur sub region and factors responsible for backwardness & disparity have been indicated. The policy guidelines for Identified sub region have been proposed based on the most significant factor and their extent of relationship explaining backwardness Nagpur sub region.

Keywords: Balanced Growth, Foreign Direct Investment, Human Development Index, Per Capita District Domestic Product, Regional Disparity, Socioeconomic Inequality, Vidarbha Region.

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Authors: Kh.Farhangdoust, H.Kamankesh

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Undoubtedly, chassis is one of the most important parts of a vehicle. Chassis that today are produced for vehicles are made up of four parts. These parts are jointed together by screwing. Transverse parts are called cross member. This study reviews the stress generated by cyclic laboratory loads in front cross member of Peugeot 405. In this paper the finite element method is used to simulate the welding process and to determine the physical response of the spot-welded joints. Analysis is done by the Abaqus software. The Stresses generated in cross member structure are generally classified into two groups: The stresses remained in form of residual stresses after welding process and the mechanical stress generated by cyclic load. Accordingly the total stress must be obtained by determining residual stress and mechanical stress separately and then sum them according to the superposition principle. In order to improve accuracy, material properties including physical, thermal and mechanical properties were supposed to be temperature-dependent. Simulation shows that maximum Von Misses stresses are located at special points. The model results are then compared to the experimental results which are reported by producing factory and good agreement is observed.

Keywords: Chassis, cross member, residual stress, resistancespot weld.

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Authors: Jonmichael A. Weaver, David A. Miller

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Ultra High Molecular Weight Polyethylene (UHMWPE) presents several distinct advantages as a material with a high strength to weight ratio, durability, and neutron stability. Understanding the change in the mechanical performance of UHMWPE due to environmental exposure is key to safety for future applications. Dyneema® HB-210, a 15 µm diameter UHMWPE multi-filament fiber laid up in a polyurethane matrix in [0/ 90]2, with a thickness of 0.17 mm is compared to the same fiber and orientation system, HB-212, with a rubber-based matrix under UV aging conditions. UV aging tests according to ASTM-G154 were performed on both HB-210 and HB-212 to interrogate the change in mechanical properties, as measured through dynamic mechanical analysis and imaged using a scanning electron microscope. These results showed a decrease in both the storage modulus and loss modulus of the aged material compared to the unaged, even though the tan δ slightly increased. Material degradation occurred at a higher rate in Dyneema® HB-212 compared to HB-210. The HB-210 was characterized for the effects of 100 hours of UV aging via dynamic mechanical analysis. Scanning electron microscope images were taken of the HB-210 and HB-212 to identify the primary damage mechanisms in the matrix. Embrittlement and matrix spall were the products of prolonged UV exposure and erosion, resulting in decreased mechanical properties.

Keywords: Composite materials, material characterization, UV aging, UHMWPE.

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Authors: S. A. Nta, M. J. Ayotamuno, I. J. Udom

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The work presents result of laboratory analysis of the effects of landfill leachate on engineering properties of test soil. The soil used for the present study was a sandy loam soil and acidic in nature. It was collected at a depth of 0.9 m. The landfill leachate used was collected from a hole dug some meters away from dumped solid waste and analyzed to identify the pollutants and its effect on engineering properties of the test soil. The test soil applied with landfill leachate was collected at 0.25 and 0.50 m radial distances at a depth of 0.15, 0.30, 0.45 and 0.60 m from the point of application of leachate after 50 days were the application of the leachate end and 80 days from the start of the experiment for laboratory analysis. Engineering properties such as particle size distribution, specific gravity, optimum moisture content, maximum dry density, unconfined compressive strength, liquid limit, plastic limit and shrinkage limit were considered. The concentration of various chemicals at 0.25 and 0.50 radial distances and 0.15, 0.30, 0.45 and 0.6 m depth from the point of application of leachate were different. This study founds the effect of landfill leachate on the engineering properties of soil. It can be concluded that, the type of soil, chemical composition of the leachate, infiltration rate, aquifers, ground water table etc., will have a major role on the area of influence zone of the pollutants in a landfill.

Keywords: Engineering properties of test soil, landfill leachate, Municipal solid waste.

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Authors: Chung-Hung Tsai

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Global environmental changes lead to increased frequency and scale of natural disaster, Taiwan is under the influence of global warming and extreme weather. Therefore, the vulnerability was increased and variability and complexity of disasters is relatively enhanced. The purpose of this study is to consider the source and magnitude of hazard characteristics on the tourism industry. Using modern risk management concepts, integration of related domestic and international basic research, this goes beyond the Taiwan typhoon disaster risk assessment model and evaluation of loss. This loss evaluation index system considers the impact of extreme weather, in particular heavy rain on the tourism industry in Taiwan. Consider the extreme climate of the compound impact of disaster for the tourism industry; we try to make multi-hazard risk assessment model, strategies and suggestions. Related risk analysis results are expected to provide government department, the tourism industry asset owners, insurance companies and banking include tourist disaster risk necessary information to help its tourism industry for effective natural disaster risk management.

Keywords: Tourism industry, extreme weather, multi-hazard, vulnerability analysis, loss exceeding probability, risk management.

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Authors: Martin J.-D. Otis, Thien-Ly Nguyen-Dang, Thierry Laliberte, Denis Ouellet, Denis Laurendeau, Clement Gosselin

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A Cable-Driven Locomotion Interface provides a low inertia haptic interface and is used as a way of enabling the user to walk and interact with virtual surfaces. These surfaces generate Cartesian wrenches which must be optimized for each motorized reel in order to reproduce a haptic sensation in both feet. However, the use of wrench control requires a measure of the cable tensions applied to the moving platform. The latter measure may be inaccurate if it is based on sensors located near the reel. Moreover, friction hysteresis from the reel moving parts needs to be compensated for with an evaluation of low angular velocity of the motor shaft. Also, the pose of the platform is not known precisely due to cable sagging and mechanical deformation. This paper presents a non-ideal motorized reel design with its corresponding control strategy that aims at overcoming the aforementioned issues. A transfert function of the reel based on frequency responses in function of cable tension and cable length is presented with an optimal adaptative PIDF controller. Finally, an hybrid position/tension control is discussed with an analysis of the stability for achieving a complete functionnality of the haptic platform.

Keywords: haptic, reel, transparency, cable, tension, control

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Authors: Ben-Edigbe J, RahmanR

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Since primary school trips usually start from home, attention by many scholars have been focused on the home end for data gathering. Thereafter category analysis has often been relied upon when predicting school travel demands. In this paper, school end was relied on for data gathering and multivariate regression for future travel demand prediction. 9859 pupils were surveyed by way of questionnaires at 21 primary schools. The town was divided into 5 zones. The study was carried out in Skudai Town, Malaysia. Based on the hypothesis that the number of primary school trip ends are expected to be the same because school trips are fixed, the choice of trip end would have inconsequential effect on the outcome. The study compared empirical data for home and school trip end productions and attractions. Variance from both data results was insignificant, although some claims from home based family survey were found to be grossly exaggerated. Data from the school trip ends was relied on for travel demand prediction because of its completeness. Accessibility, trip attraction and trip production were then related to school trip rates under daylight and dry weather conditions. The paper concluded that, accessibility is an important parameter when predicting demand for future school trip rates.

Keywords: Trip generation, regression analysis, multiple linearregressions

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Authors: Julian Pigott

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This paper presents the Language Learning as a Means of Drive Engagement (LLMDE) theory, derived from a grounded theory analysis of interviews with Japanese university students. According to LLMDE theory, language learning can be understood as a means of engaging one or more of four self-fulfillment drives: the drive to expand one’s horizons (perspective drive); the drive to make a success of oneself (status drive); the drive to engage in interaction with others (communication drive); and the drive to obtain intellectual and affective stimulation (entertainment drive). While many theories of learner psychology focus on conscious agency, LLMDE theory addresses the role of the unconscious. In addition, supplementary thematic analysis of the data revealed the role of context in mediating drive engagement. Unexpected memorable events, for example, play a key role in instigating and, indirectly, in regulating learning, as do institutional and cultural contexts. Given the apparent importance of such factors beyond the immediate control of the learner, and given the pervasive role of habit and drives, it is argued that the concept of motivation merits theoretical reappraisal. Rather than an underlying force determining language learning success or failure, it can be understood to emerge sporadically in consciousness to promote behavioral change, or to protect habitual behavior from disruption.

Keywords: Drives, grounded theory, motivation, significant events.

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Authors: Ju-Young Kim, Tae-Heon Moon, Jung-Hun Cho

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Urban regeneration projects have been actively promoted in Korea. In particular, Jeonju Hanok Village is evaluated as one of representative cases in terms of utilizing local cultural heritage sits in the urban regeneration project. However, recently, there has been a growing concern in this area, due to the ‘gentrification’, caused by the excessive commercialization and surging tourists. This trend was changing land and building use and resulted in the loss of identity of the region. In this regard, this study analyzed the land use transformation between 2010 and 2016 to identify the commercialization trend in Jeonju Hanok Village. In addition, it conducted SNS big data analysis on Jeonju Hanok Village from February 14th, 2016 to March 31st, 2016 to identify visitors’ awareness of the village. The study results demonstrate that rapid commercialization was underway, unlikely the initial intention, so that planners and officials in city government should reconsider the project direction and rebuild deliberate management strategies. This study is meaningful in that it analyzed the land use transformation and SNS big data to identify the current situation in urban regeneration area. Furthermore, it is expected that the study results will contribute to the vitalization of regeneration area.

Keywords: Land use, SNS, text mining, urban regeneration.

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Authors: Najmeh Bolbolamiri, Maryam Setayesh Sanai, Ahmad Mirabadi

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This paper deals with condition monitoring of electric switch machine for railway points. Point machine, as a complex electro-mechanical device, switch the track between two alternative routes. There has been an increasing interest in railway safety and the optimal management of railway equipments maintenance, e.g. point machine, in order to enhance railway service quality and reduce system failure. This paper explores the development of Kolmogorov- Smirnov (K-S) test to detect some point failures (external to the machine, slide chairs, fixing, stretchers, etc), while the point machine (inside the machine) is in its proper condition. Time-domain stator Current signatures of normal (healthy) and faulty points are taken by 3 Hall Effect sensors and are analyzed by K-S test. The test is simulated by creating three types of such failures, namely putting a hard stone and a soft stone between stock rail and switch blades as obstacles and also slide chairs- friction. The test has been applied for those three faults which the results show that K-S test can effectively be developed for the aim of other point failures detection, which their current signatures deviate parametrically from the healthy current signature. K-S test as an analysis technique, assuming that any defect has a specific probability distribution. Empirical cumulative distribution functions (ECDF) are used to differentiate these probability distributions. This test works based on the null hypothesis that ECDF of target distribution is statistically similar to ECDF of reference distribution. Therefore by comparing a given current signature (as target signal) from unknown switch state to a number of template signatures (as reference signal) from known switch states, it is possible to identify which is the most likely state of the point machine under analysis.

Keywords: stator currents monitoring, railway points, point failures, fault detection and diagnosis, Kolmogorov-Smirnov test, time-domain analysis.

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Authors: Lin Yang, Zhian Mi, Jiacheng Xiao, Rong Li

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Swimming with the tide of deep learning, the field of music information retrieval (MIR) experiences parallel development and a sheer variety of feature-learning models has been applied to music classification and tagging tasks. Among those learning techniques, the deep convolutional neural networks (CNNs) have been widespreadly used with better performance than the traditional approach especially in music genre classification and prediction. However, regarding the music recommendation, there is a large semantic gap between the corresponding audio genres and the various aspects of a song that influence user preference. In our study, aiming to bridge the gap, we strive to construct an automatic music aesthetic annotation model with MIDI format for better comparison and measurement of the similarity between music pieces in the way of harmonic analysis. We use the matrix of qualification converted from MIDI files as input to train two different classifiers, support vector machine (SVM) and Decision Tree (DT). Experimental results in performance of a tag prediction task have shown that both learning algorithms are capable of extracting high-level properties in an end-to end manner from music information. The proposed model is helpful to learn the audience taste and then the resulting recommendations are likely to appeal to a niche consumer.

Keywords: Harmonic analysis, machine learning, music classification and tagging, MIDI.

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Authors: Rungchat Chompu-Inwai, Akararit Charoenkasemsuk

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The use of electronic sensors in the electronics industry has become increasingly popular over the past few years, and it has become a high competition product. The frequency adjustment process is regarded as one of the most important process in the electronic sensor manufacturing process. Due to inaccuracies in the frequency adjustment process, up to 80% waste can be caused due to rework processes; therefore, this study aims to provide a preliminary understanding of the role of parameters used in the frequency adjustment process, and also make suggestions in order to further improve performance. Four parameters are considered in this study: air pressure, dispensing time, vacuum force, and the distance between the needle tip and the product. A full factorial design for experiment 2k was considered to determine those parameters that significantly affect the accuracy of the frequency adjustment process, where a deviation in the frequency after adjustment and the target frequency is expected to be 0 kHz. The experiment was conducted on two levels, using two replications and with five center-points added. In total, 37 experiments were carried out. The results reveal that air pressure and dispensing time significantly affect the frequency adjustment process. The mathematical relationship between these two parameters was formulated, and the optimal parameters for air pressure and dispensing time were found to be 0.45 MPa and 458 ms, respectively. The optimal parameters were examined by carrying out a confirmation experiment in which an average deviation of 0.082 kHz was achieved.

Keywords: Design of Experiment, Electronic Sensor, Frequency Adjustment, Parametric Analysis

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Authors: Emad E Abdallah, A.F. Otoom, ArwaSaqer, Ola Abu-Aisheh, Diana Omari, Ghadeer Salem

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As emails communications have no consistent authentication procedure to ensure the authenticity, we present an investigation analysis approach for detecting forged emails based on Random Forests and Naïve Bays classifiers. Instead of investigating the email headers, we use the body content to extract a unique writing style for all the possible suspects. Our approach consists of four main steps: (1) The cybercrime investigator extract different effective features including structural, lexical, linguistic, and syntactic evidence from previous emails for all the possible suspects, (2) The extracted features vectors are normalized to increase the accuracy rate. (3) The normalized features are then used to train the learning engine, (4) upon receiving the anonymous email (M); we apply the feature extraction process to produce a feature vector. Finally, using the machine learning classifiers the email is assigned to one of the suspects- whose writing style closely matches M. Experimental results on real data sets show the improved performance of the proposed method and the ability of identifying the authors with a very limited number of features.

Keywords: Digital investigation, cybercrimes, emails forensics, anonymous emails, writing style, and authorship analysis

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Authors: Anita Khadka, Gregory Epiphaniou, Carsten Maple

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There is a dramatic surge in the adoption of Machine Learning (ML) techniques in many areas, including the nuclear industry (such as fault diagnosis and fuel management in nuclear power plants), autonomous systems (including self-driving vehicles), space systems (space debris recovery, for example), medical surgery, network intrusion detection, malware detection, to name a few. Artificial Intelligence (AI) has become a part of everyday modern human life. To date, the predominant focus has been developing underpinning ML algorithms that can improve accuracy, while factors such as resiliency and robustness of algorithms have been largely overlooked. If an adversarial attack is able to compromise the learning method or data, the consequences can be fatal, especially but not exclusively in safety-critical applications. In this paper, we present an in-depth analysis of five adversarial attacks and two defence methods on a crack detection ML model. Our analysis shows that it can be dangerous to adopt ML techniques without rigorous testing, since they may be vulnerable to adversarial attacks, especially in security-critical areas such as the nuclear industry. We observed that while the adopted defence methods can effectively defend against different attacks, none of them could protect against all five adversarial attacks entirely.

Keywords: Resilient Machine Learning, attacks, defences, nuclear industry, crack detection.

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Authors: M. Bodner, M. Scampicchio

Abstract:

Fourier Transform Infrared (FT-IR) spectroscopy coupled with chemometrics was used to distinguish between butter samples and non-butter samples. Further, quantification of the content of margarine in adulterated butter samples was investigated. Fingerprinting region (1400-800 cm^–1) was used to develop unsupervised pattern recognition (Principal Component Analysis, PCA), supervised modeling (Soft Independent Modelling by Class Analogy, SIMCA), classification (Partial Least Squares Discriminant Analysis, PLS-DA) and regression (Partial Least Squares Regression, PLS-R) models. PCA of the fingerprinting region shows a clustering of the two sample types. All samples were classified in their rightful class by SIMCA approach; however, nine adulterated samples (between 1% and 30% w/w of margarine) were classified as belonging both at the butter class and at the non-butter one. In the two-class PLS-DA model’s (R² = 0.73, RMSEP, Root Mean Square Error of Prediction = 0.26% w/w) sensitivity was 71.4% and Positive Predictive Value (PPV) 100%. Its threshold was calculated at 7% w/w of margarine in adulterated butter samples. Finally, PLS-R model (R² = 0.84, RMSEP = 16.54%) was developed. PLS-DA was a suitable classification tool and PLS-R a proper quantification approach. Results demonstrate that FT-IR spectroscopy combined with PLS-R can be used as a rapid, simple and safe method to identify pure butter samples from adulterated ones and to determine the grade of adulteration of margarine in butter samples.

Keywords: Adulterated butter, margarine, PCA, PLS-DA, PLS-R, SIMCA.

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Authors: Hina Kausher, Sangita Srivastava

Abstract:

In India, there is a lack of standard, systematic sizing approach for producing readymade garments. Garments manufacturing companies use their own created size tables by modifying international sizing charts of ready-made garments. The purpose of this study is to tabulate the anthropometric data which cover the variety of figure proportions in both height and girth. 3,000 data have been collected by an anthropometric survey undertaken over females between the ages of 16 to 80 years from the some states of India to produce the sizing system suitable for clothing manufacture and retailing. The data are used for the statistical analysis of body measurements, the formulation of sizing systems and body measurements tables. Factor analysis technique is used to filter the control body dimensions from the large number of variables. Decision tree-based data mining is used to cluster the data. The standard and structured sizing system can facilitate pattern grading and garment production. Moreover, it can exceed buying ratios and upgrade size allocations to retail segments.

Keywords: Anthropometric data, data mining, decision tree, garments manufacturing, ready-made garments, sizing systems.

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Authors: G. Ghodrati Amiri, M. Khorasani, Razavian Ameri, M.Mohamadi Dehcheshmeh, S.Fathi

Abstract:

Many studies have been conducted for derivation of attenuation relationships worldwide, however few relationships have been developed to use for the seismic region of Iranian plateau and only few of these studies have been conducted for derivation of attenuation relationships for parameters such as uniform duration. Uniform duration is the total time during which the acceleration is larger than a given threshold value (default is 5% of PGA). In this study, the database was same as that used previously by Ghodrati Amiri et al. (2007) with same correction methods for earthquake records in Iran. However in this study, records from earthquakes with MS< 4.0 were excluded from this database, each record has individually filtered afterward, and therefore the dataset has been expanded. These new set of attenuation relationships for Iran are derived based on tectonic conditions with soil classification into rock and soil. Earthquake parameters were chosen to be hypocentral distance and magnitude in order to make it easier to use the relationships for seismic hazard analysis. Tehran is the capital city of Iran wit ha large number of important structures. In this study, a probabilistic approach has been utilized for seismic hazard assessment of this city. The resulting uniform duration against return period diagrams are suggested to be used in any projects in the area.

Keywords: Attenuation Relationships, Iran, Probabilistic Seismic Hazard Analysis, Tehran, Uniform Duration

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Authors: Hossein Lotfizadeh, André McDonald, Amit Kumar

Abstract:

Renewable energy resources, which can supplement space and water heating for residential buildings, can have a noticeable impact on natural gas consumption and air pollution. This study considers a technical analysis of a combined solar water heating system with evacuated tube solar collectors for different solar coverage, ranging from 20% to 100% of the total roof area of a typical residential building located in Edmonton, Alberta, Canada. The alternative heating systems were conventional (non-condensing) and condensing tankless water heaters and condensing boilers that were coupled to solar water heating systems. The performance of the alternative heating systems was compared to a traditional heating system, consisting of a conventional boiler, applied to houses of various gross floor areas. A comparison among the annual natural gas consumption, carbon dioxide (CO₂) mitigation, and emissions for the various house sizes indicated that the combined solar heating system can reduce the natural gas consumption and CO₂ emissions, and increase CO₂ mitigation for all the systems that were studied. The results suggest that solar water heating systems are potentially beneficial for residential heating system applications in terms of energy savings and CO₂ mitigation.

Keywords: CO2 emissions, CO2 mitigation, natural gas consumption, solar water heating system, tankless water heater.

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Authors: O. J. G. Somsen

Abstract:

One of the tasks of optical surveillance is to detect anomalies in large amounts of image data. However, if the size of the anomaly is very small, limited information is available to distinguish it from the surrounding environment. Spectral detection provides a useful source of additional information and may help to detect anomalies with a size of a few pixels or less. Unfortunately, spectral cameras are expensive because of the difficulty of separating two spatial in addition to one spectral dimension. We investigate the possibility of modifying a simple spectral line detector for outdoor detection. This may be especially useful if the area of interest forms a line, such as the horizon. We use a monochrome CCD that also enables detection into the near infrared. A simple camera is attached to the setup to determine which part of the environment is spectrally imaged. Our preliminary results indicate that sensitive detection of very small targets is indeed possible. Spectra could be taken from the various targets by averaging columns in the line image. By imaging a set of lines of various widths we found narrow lines that could not be seen in the color image but remained visible in the spectral line image. A simultaneous analysis of the entire spectra can produce better results than visual inspection of the line spectral image. We are presently developing calibration targets for spatial and spectral focusing and alignment with the spatial camera. This will present improved results and more use in outdoor application.

Keywords: Anomaly detection, spectroscopic line imaging, image analysis.

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Authors: G. Shanmugasundar, R. Sivaramakrishnan, S. Venugopal

Abstract:

Robots are booming as an essential substituent in the field of inspection. In hazardous environments like nuclear waste disposal, robots are really a necessitate one. In a view to meet such demands, this paper presents the seven degree of freedom articulated inspection robot. To design such a robot the kinematic analysis of seven Degree of freedom robot which can inspect the hazardous nuclear waste storage tanks is done. The effective utilization of universal joints for arms and screw jack mechanisms at the base gives the higher order of degree of freedom to the newly designed robot. The analytical method of deriving the manipulator forward as well as inverse kinematics is explained elaborately using the Denavit-Hartenberg Approach for the purpose of calculating the robot joints, links and end-effector parameters. The comparison of the geometric and the analytical approach is stated. The self-developed kinematic model gives the accurate positions of the end effector. The Graphical User Interface (GUI) is developed in Visual Basic language for the manipulation of kinematic results easily. This software gives the expected position of the end-effector accurately at short time compared to manual manipulations.

Keywords: Robot kinematics, screw jack mechanisms, Denavit-Hartenberg approach, universal joints.

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