Search results for: action based method

Authors: Ezman Fitriansyah, Lestari Diah Restu, Wawan

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Adaro coal mine in South Kalimantan-Indonesia maintains catchment area of approximately 15,000 Ha for its mine operation. As an open pit surface coal mine with high erosion rate, the mine water in Adaro coal mine contains high TSS that needs to be treated before being released to rivers. For the treatment process, Adaro operates 21 Settling Ponds equipped with combination of physical and chemical system to separate solids and water to ensure the discharged water complied with regional environmental quality standards. However, the sludge created from the sedimentation process reduces the settling ponds capacity gradually. Therefore regular maintenance activities are required to recover and maintain the ponds' capacity. Trucking system and direct dredging had been the most common method to handle sludge in Adaro. But the main problem in applying these two methods is excessive area required for drying pond construction. To solve this problem, Adaro implements an alternative method called Geotube®. The principle of Geotube® method is the sludge contained in the Settling Ponds is pumped into Geotube® containers which have been designed to release water and retain mud flocks. During the pumping process, an amount of flocculants chemicals are injected into the sludge to form bigger mud flocks. Due to the difference in particle size, the mud flocks are settled in the container whilst the water continues to flow out through the container’s pores. Compared to the trucking system and direct dredging method, this method provides three advantages: space required to operate, increasing of overburden waste dump volume, and increasing of water treatment process speed and quality. Based on the evaluation result, Geotube® method only needs 1:8 of space required by the other methods. From the geotechnical assessment result conducted by Adaro, the potential loss of waste dump volume capacity prior to implementation of the Geotube® method was 26.7%. The water treatment process of TSS in well maintained ponds is 16% more optimum.

Keywords: geotube, mine water, settling pond, sludge handling, wastewater treatment

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Authors: Michaela Vašková

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The paper is focused on the application of the security audit method on the selected objects of the critical infrastructure. The emphasis is put on security audit method to find gaps in the critical infrastructure security. The theoretical part describes objects of the critical infrastructure. The practical part describes using the security audit method. The main emphasis was put on the protection of the critical infrastructure in the Czech Republic.

Keywords: crisis management, critical infrastructure, object of critical infrastructure, security audit, extraordinary event

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Authors: Tomas Vincze, Michal Micjan, Milan Pavuk, Martin Weis

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In recent years, alternative materials are gaining attention to replace polycrystalline and amorphous silicon, which are a standard for low requirement devices, where silicon is unnecessarily and high cost. For that reason, metal oxides are envisioned as the new materials for these low-requirement applications such as sensors, solar cells, energy storage devices, or field-effect transistors. Their most common way of layer growth is sputtering; however, this is a high-cost fabrication method, and a more industry-suitable alternative is the sol-gel method. In this group of materials, many oxides exhibit a semiconductor-like behavior with sufficiently high mobility to be applied as transistors. The sol-gel method is a cost-effective deposition technique for semiconductor-based devices. Copper oxides, as p-type semiconductors with free charge mobility up to 1 cm2/Vs., are suitable replacements for poly-Si or a-Si:H devices. However, to reach the potential of silicon devices, a fine-tuning of material properties is needed. Here we focus on the optimization of the electrical parameters of copper oxide-based field-effect transistors by modification of precursor solvent (usually 2-methoxy ethanol). However, to achieve solubility and high-quality films, a better solvent is required. Since almost no solvents have both high dielectric constant and high boiling point, an alternative approach was proposed with blend solvents. By mixing isopropyl alcohol (IPA) and 2-methoxy ethanol (2ME) the precursor reached better solubility. The quality of the layers fabricated using mixed solutions was evaluated in accordance with the surface morphology and electrical properties. The IPA:2ME solution mixture reached optimum results for the weight ratio of 1:3. The cupric oxide layers for optimal mixture had the highest crystallinity and highest effective charge mobility.

Keywords: copper oxide, field-effect transistor, semiconductor, sol-gel method

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Authors: A. Shahsavari, M. Nili-Ahmadabadi

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This paper presents an innovative one-dimensional optimization of a transonic compressor based on the radial equilibrium theory by means of increasing blade loading. Firstly, the rotor blade of the transonic compressor is redesigned based on the constant span-wise deHaller number and diffusion. The code is applied to extract compressor meridional plane and blade to blade geometry containing rotor and stator in order to design blade three-dimensional view. A structured grid is generated for the numerical domain of fluid. Finer grids are used for regions near walls to capture boundary layer effects and behavior. RANS equations are solved by finite volume method for rotating zones (rotor) and stationary zones (stator). The experimental data, available for the performance map of NASA Rotor67, is used to validate the results of simulations. Then, the capability of the design method is validated by CFD that is capable of predicting the performance map. The numerical results of new geometry show about 19% increase in pressure ratio and 11% improvement in overall efficiency of the transonic stage; however, the design point mass flow rate of the new compressor is 5.7% less than that of the original compressor.

Keywords: deHaller number, one dimensional design, radial equilibrium, transonic compressor

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Authors: John Carlo Combista, Jimbert Tan

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The orchid, Vanda tessellata was chosen by the researchers because of the presence of the constituents in the family Orchidaceae such as alkaloids, flavonoids and glycosides that might give an inhibition activity of the carbonic anhydrase enzyme. This study aimed to determine the in vitro inhibition of carbonic anhydrase of Vanda tessellata flower extract. With the use of modified colorimetric Maren T.H. (1960) method, the time in seconds each test solution changed its color after the rate of CO2 hydration were recorded. Two solvents were used: the semi-polar, 95% ethanol and the non-polar, dichloromethane solvents. The percent inhibition activity of carbonic anhydrase of the different concentrations of solvents ethanol (1%, 25% and 50%) and dichloromethane (1% and 10%) test solutions were determined. Results showed that the ethanol-based extract of Vanda tessellata in different concentrations showed an inhibitory effect while the dichloromethane-based extract of Vanda tessellata showed no inhibitory effect of carbonic anhydrase activity. For ethanol extract, the concentration with the highest activity was 50% followed by 25% which changed its color from red to yellow with an average time of 13.11 seconds and 11.57 seconds but 1% with an average time of 7.56 seconds did not exhibit an effect. The researchers recommend the isolation of the specific active constituents of Vanda tessellata that is responsible for the inhibitory effect of carbonic anhydrase enzyme. It is also recommended to utilize different blood types to observe different reactions to the inhibition of the carbonic anhydrase.

Keywords: carbonic anhydrase, inhibition, modified colorimetric Maren TH method, Vanda orchid

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Authors: Claudia Ehrentraut, Osama Ibrahim, Hercules Dalianis

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Policy making situations are real-world problems that exhibit complexity in that they are composed of many interrelated problems and issues. To be effective, policies must holistically address the complexity of the situation rather than propose solutions to single problems. Formulating and understanding the situation and its complex dynamics, therefore, is a key to finding holistic solutions. Analysis of text based information on the policy problem, using Natural Language Processing (NLP) and Text analysis techniques, can support modelling of public policy problem situations in a more objective way based on domain experts knowledge and scientific evidence. The objective behind this study is to support modelling of public policy problem situations, using text analysis of verbal descriptions of the problem. We propose a formal methodology for analysis of qualitative data from multiple information sources on a policy problem to construct a causal diagram of the problem. The analysis process aims at identifying key variables, linking them by cause-effect relationships and mapping that structure into a graphical representation that is adequate for designing action alternatives, i.e., policy options. This study describes the outline of an algorithm used to automate the initial step of a larger methodological approach, which is so far done manually. In this initial step, inferences about key variables and their interrelationships are extracted from textual data to support a better problem structuring. A small prototype for this step is also presented.

Keywords: public policy, problem structuring, qualitative analysis, natural language processing, algorithm, inference extraction

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Authors: Dahi Ghareab Abdelsalam Ibrahim

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Calibration of step heights with high accuracy is needed for many applications in the industry. In general, step height consists of three bands: pass band, transition band (roll-off), and stop band. Abdelsalam used a convolution of the transfer functions of both Chebyshev type 2 and elliptic filters with WFF of the Fresnel transform in the frequency domain for producing a steeper roll-off with the removal of ripples in the pass band- and stop-bands. In this paper, we used a new method based on the Hamming window: band-pass filter for calibration of step heights in terms of perfect adjustment of pass-band, roll-off, and stop-band. The method is applied to calibrate a nominal step height of 40 cm. The step height is measured first by asynchronous dual-wavelength phase-shift interferometry. The measured step height is then calibrated by the simulation of the Hamming window: band-pass filter. The spectrum of the simulated band-pass filter is simulated at N = 881 and f0 = 0.24. We can conclude that the proposed method can calibrate any step height by adjusting only two factors which are N and f0.

Keywords: optical metrology, step heights, hamming window, band-pass filter

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Authors: Prajamitra Bhuyan

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Transport operators have a range of intervention options available to improve or enhance their networks. But often such interventions are made in the absence of sound evidence on what outcomes may result. Cycling superhighways were promoted as a sustainable and healthy travel mode which aims to cut traffic congestion. The estimation of the impacts of the cycle superhighways on congestion is complicated due to the non-random assignment of such intervention over the transport network. In this paper, we analyse the causal effect of cycle superhighways utilising pre-innervation and post-intervention information on traffic and road characteristics along with socio-economic factors. We propose a modeling framework based on the propensity score and outcome regression model. The method is also extended to doubly robust set-up. Simulation results show the superiority of the performance of the proposed method over existing competitors. The method is applied to analyse a real dataset on the London transport network, and the result would help effective decision making to improve network performance.

Keywords: average treatment effect, confounder, difference-in-difference, intelligent transportation system, potential outcome

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Authors: Seyed Amin Vakili, Sahar Sadat Vakili, Seyed Ehsan Vakili, Nader Abdoli Yazdi

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The aim of this paper is to examine the behavior of elastic stability of reinforced and composite concrete struts with axial loads. The objective of this study is to verify the ability of the Modified Newmark Method to include geometric non-linearity in addition to non-linearity due to cracking, and also to show the advantage of the established method to reconsider an ignored minor parameter in mathematical modeling, such as the effect of the cracking by extra geometric bending moment Ny on cross-section properties. The purpose of this investigation is not to present some new results for the instability of reinforced or composite concrete columns. Therefore, no kinds of non-linearity involved in the problem are considered here. Only as mentioned, it is a part of the verification of the new established method to solve two kinds of non-linearity P- δ effect and cracking together simultaneously. However, the Modified Newmark Method can be used to solve non-linearity of materials and time-dependent behavior of concrete. However, since it is out of the scope of this article, it is not considered.

Keywords: stability, buckling, modified newmark method, reinforced

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Authors: Toufik Bensana, Slimane Mekhilef, Kamel Tadjine

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The use of vibration analysis has been established as the most common and reliable method of analysis in the field of condition monitoring and diagnostics of rotating machinery. Rolling bearings cover a broad range of rotary machines and plays a crucial role in the modern manufacturing industry. Unfortunately, the vibration signals collected from a faulty bearing are generally non-stationary, nonlinear and with strong noise interference, so it is essential to obtain the fault features correctly. In this paper, a novel numerical analysis method based on local mean decomposition (LMD) is proposed. LMD decompose the signal into a series of product functions (PFs), each of which is the product of an envelope signal and a purely frequency modulated FM signal. The envelope of a PF is the instantaneous amplitude (IA) and the derivative of the unwrapped phase of a purely flat frequency demodulated (FM) signal is the IF. After that, the fault characteristic frequency of the roller bearing can be extracted by performing spectrum analysis to the instantaneous amplitude of PF component containing dominant fault information. the results show the effectiveness of the proposed technique in fault detection and diagnosis of rolling element bearing.

Keywords: fault diagnosis, local mean decomposition, rolling element bearing, vibration analysis

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Authors: Vikas Sharma, V. K. Dixit

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Anacyclus pyrethrum (A. pyrethrum) has been used as Vajikaran Rasayana (aphrodisiac) in traditional Indian ayurvedic medicine to treat male sexual dysfunction, including infertility. Aphrodisiac activity may be due to an increase in the production or effect of androgens, so this study sought to evaluate the androgenic and spermatogenic potential of the alkylamide-rich ethanol solution extract. Male Wistar strain rats weighing between 150 and 180 g were completely randomized divided into five groups. The ethanol solution extract of A. pyrethrum was administered to groups of rats in 50, 100, and 150 mg/kg doses for a period of 28 days, and the action was compared with control and testosterone-treated rats. Thirteen N-alkylamides were detected in the extract by using HPLC/UV/electrospray ionization mass spectrometry method. Extract administration at all the doses produced significant increase in body weight, sperm count, motility, and viability along with serum testosterone, luteinizing hormone, and follicle-stimulating hormone concentrations. Histoarchitecture of testis revealed increased spermatogenic activities. Seminal fructose content was also significantly increased after 28 days of treatment. Our results suggest that the ethanol solution extract of the roots of A. pyrethrum has androgenic potential and may improve male fertility by enhancing spermatogenesis.

Keywords: N-alkylamides, testosterone, Anacyclus pyrethrum, androgen

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Authors: Manendra Singh Parihar, Sandip Ghosh Chowdhury

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Austenitic stainless steels are widely used and give a good combination of properties. When this steel is plastically deformed, a phase transformation of the metastable Face Centred Cubic Austenite to the stable Body Centred Cubic (α’) or to the Hexagonal close packed (ԑ) martensite may occur, leading to the enhancement in the mechanical properties like strength. The work was based on variant selection and corresponding texture analysis for the strain induced martensitic transformation during deformation of the parent austenite FCC phase to form the product HCP and the BCC martensite phases separately, obeying their respective orientation relationships. The automated method for reconstruction of the parent phase orientation using the EBSD data of the product phase orientation is done using the MATLAB and TSL-OIM software. The method of triplets was used which involves the formation of a triplet of neighboring product grains having a common variant and linking them using a misorientation-based criterion. This led to the proper reconstruction of the pre-transformation phase orientation data and thus to its micro structure and texture. The computational speed of current method is better compared to the previously used methods of reconstruction. The reconstruction of austenite from ԑ and α’ martensite was carried out for multiple samples and their IPF images, pole figures, inverse pole figures and ODFs were compared. Similar type of results was observed for all samples. The comparison gives the idea for estimating the correct sequence of the transformation i.e. γ → ε → α’ or γ → α’, during deformation of AISI 304 austenitic stainless steel.

Keywords: variant selection, reconstruction, EBSD, austenitic stainless steel, martensitic transformation

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Authors: Vahid Bairami Rad, Shapoor Norazar, Moslem Talebi Asl

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The fast growing accessibility and capability of emerging technologies have fashioned enormous possibilities of designing, developing and implementing innovative teaching methods in the classroom. Using teaching methods and technology together have a fantastic results, because the global technological scenario has paved the way to new pedagogies in teaching-learning process. At the other side methods by focusing on students and the ways of learning in them, that can demonstrate logical ways of improving student achievement in English as a foreign language in Iran. The sample of study was 90 students of 10th grade of high school located in Ardebil. A pretest-posttest equivalent group designed to compare the achievement of groups. Students divided to 3 group, Control base, computer base, method and technology base. Pretest and post test contain 30 items each from English textbook were developed and administrated, then obtained data were analyzed. The results showed that there was an important difference. The 3rd group performance was better than other groups. On the basis of this result it was obviously counseled that teaching-learning capabilities.

Keywords: method, technology based environment, computer based environment, english as a foreign language, student achievement

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Authors: Andrey V. Malyshev, Anna B. Petrova, Anatoly P. Surzhikov

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The article presents the results of the influence of diamagnetic additives on the defects level of ferrite ceramics. For this purpose, we use a previously developed method based on the mathematical analysis of experimental temperature dependences of the initial permeability. A phenomenological expression for the description of such dependence was suggested and an interpretation of its main parameters was given. It was shown, that the main criterion of the integral defects level of ferrite ceramics is the relation of two parameters correlating with elastic stress value in a material. Model samples containing a controlled number of intergranular phase inclusions served to prove the validity of the proposed method, as well as to assess its sensitivity in comparison with the traditional XRD (X-ray diffraction) analysis. The broadening data of diffraction reflexes of model samples have served for such comparison. The defects level data obtained by the proposed method are in good agreement with the X-ray data. The method showed high sensitivity. Therefore, the legitimacy of the selection relationship β/α parameters of phenomenological expression as a characteristic of the elastic state of the ferrite ceramics confirmed. In addition, the obtained data can be used in the detection of non-magnetic phases and testing the optimal sintering production technology of soft magnetic ferrites.

Keywords: cure point, initial permeability, integral defects level, homogeneity

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Authors: Siti Noor Farwina Anwar, Hailiza Kamarulhaili

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In this paper, we present the idea of implementing the Integer Sub-Decomposition (ISD) method on elliptic curves with j-invariant 1728. The ISD method was proposed in 2013 to compute scalar multiplication in elliptic curves, which remains to be the most expensive operation in Elliptic Curve Cryptography (ECC). However, the original ISD method only works on integer number field and solve integer scalar multiplication. By extending the method into the complex quadratic field, we are able to solve complex multiplication and implement the ISD method on elliptic curves with j-invariant 1728. The curve with j-invariant 1728 has a unique discriminant of the imaginary quadratic field. This unique discriminant of quadratic field yields a unique efficiently computable endomorphism, which later able to speed up the computations on this curve. However, the ISD method needs three endomorphisms to be accomplished. Hence, we choose all three endomorphisms to be from the same imaginary quadratic field as the curve itself, where the first endomorphism is the unique endomorphism yield from the discriminant of the imaginary quadratic field.

Keywords: efficiently computable endomorphism, elliptic scalar multiplication, j-invariant 1728, quadratic field

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Authors: Mohamad R. Moshtagh, Ahmad Bagheri

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Accurate fault detection in rotating machinery is of utmost importance to ensure optimal performance and prevent costly downtime in industrial applications. This study presents a robust fault detection system based on vibration data collected from rotating gears under various operating conditions. The considered scenarios include: (1) both gears being healthy, (2) one healthy gear and one faulty gear, and (3) introducing an imbalanced condition to a healthy gear. Vibration data was acquired using a Hentek 1008 device and stored in a CSV file. Python code implemented in the Spider environment was used for data preprocessing and analysis. Winner features were extracted using the Wiener feature selection method. These features were then employed in multiple machine learning algorithms, including Convolutional Neural Networks (CNN), Multilayer Perceptron (MLP), K-Nearest Neighbors (KNN), and Random Forest, to evaluate their performance in detecting and classifying faults in both the training and validation datasets. The comparative analysis of the methods revealed the superior performance of the Wiener-CNN approach. The Wiener-CNN method achieved a remarkable accuracy of 100% for both the two-class (healthy gear and faulty gear) and three-class (healthy gear, faulty gear, and imbalanced) scenarios in the training and validation datasets. In contrast, the other methods exhibited varying levels of accuracy. The Wiener-MLP method attained 100% accuracy for the two-class training dataset and 100% for the validation dataset. For the three-class scenario, the Wiener-MLP method demonstrated 100% accuracy in the training dataset and 95.3% accuracy in the validation dataset. The Wiener-KNN method yielded 96.3% accuracy for the two-class training dataset and 94.5% for the validation dataset. In the three-class scenario, it achieved 85.3% accuracy in the training dataset and 77.2% in the validation dataset. The Wiener-Random Forest method achieved 100% accuracy for the two-class training dataset and 85% for the validation dataset, while in the three-class training dataset, it attained 100% accuracy and 90.8% accuracy for the validation dataset. The exceptional accuracy demonstrated by the Wiener-CNN method underscores its effectiveness in accurately identifying and classifying fault conditions in rotating machinery. The proposed fault detection system utilizes vibration data analysis and advanced machine learning techniques to improve operational reliability and productivity. By adopting the Wiener-CNN method, industrial systems can benefit from enhanced fault detection capabilities, facilitating proactive maintenance and reducing equipment downtime.

Keywords: fault detection, gearbox, machine learning, wiener method

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Authors: Pedro H. S. Messetti, Mary L. G. S. Senna, Afonso R. Aquino

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Sustainability is a very important and heavily discussed subject, expanding through tourism as well. The study proposition was to collect data and present it to the competent bodies so they can mold their public politics to improve the conditions of the site. It was hypothesized that the lack of data is currently affecting the quality of life and the sustainable development of the site and the tourism. The research was held in Mateiros, a city in the state of Tocantins (TO)/Brasil, 275km far from the capital city Palmas, being one of the 8 cities that comprises the Jalapão region, an ecotourism and adventure tourism site as well as an environmental protection area (Jalapão State Park). Because of the concentration of tourists during the high season and several tourist attractions being around, the research took place in Mateiros. The methodological procedure had a script of theoretical construction and investigation of the deductive scientific method parameters through a case study in the Jalapão/TO/Brazil region, using it as a tool for a questionnaire given to the competent bodies in an interview system with the UN sustainability indexes as a base. In the three sustainable development scope: environmental, social and economic, the results indicated that the data presented by the interviewed were scarce or nonexistent. It shows that more research is necessary, providing the tools for the ones responsible to propose action plans to improve the site, strengthening the tourism and making it even more sustainable.

Keywords: Jalapão/Brazil state park, sustainable tourism, UN sustainability indexes

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Authors: Enes Furkan Erkan, Özer Uygun, Halil Ibrahim Demir, Zeynep Demir

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Companies require increase in quality perception level of their products due to competitive conditions. As a result, the tendency to quality and researches to develop the quality are increasing day by day. Cost and time constraints are the biggest problems that companies face in their quality improvement efforts. In this study, factors that affect the porosity of ceramic products are determined and analyzed in a factory producing ceramic tiles. Then, Taguchi method is used in the design phase in order to decrease the number of tests to be performed by means of orthogonal sequences. The most important factors affecting the porosity of ceramic tiles are determined using Taguchi and ANOVA analysis. Based on the analyses, the most affecting factors are determined to be used in the fuzzy implementation stage. Then, the fuzzy rules were established with the factors affecting porosity by the experts’ opinion. Thus, porosity result could be obtained not only for the specified factor levels but also for intermediate values. In this way, it has been provided convenience to the factory in terms of cost and quality improvement.

Keywords: fuzzy, porosity, Taguchi Method, Taguchi-Fuzzy

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Authors: Min-Feng Hsieh

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Nowadays, we are facing a highly competitive environment in which the situation for survival has come even more critical than ever before. The challenge we will be confronted with is no longer can be dealt with the single system of knowledge. The abilities we urgently need to acquire is something that can lead us to cross over the boundaries between different disciplines and take us to a neutral ground that gathers and integrates powers and intelligence that surrounds us. This paper aims at discussing how a trans-disciplinary design course organized by the College of Design at Chaoyang University can react to this modern challenge. By orchestrating an experimental course format and by developing a series of coaching strategies, a trans-disciplinary learning environment has been created and practiced in which students selected from five different departments, including Architecture, Interior Design, Visual Design, Industrial Design, Landscape and Urban Design, are encouraged to think outside their familiar knowledge pool and to learn with/from each other. In the course of implementing this program, a parallel research has been conducted alongside by adopting the theory and principles of Action Research which is a research methodology that can provide the course organizer emergent, responsive, action-oriented, participative and critically reflective insights for the immediate changes and amendments in order to improve the effect of teaching and learning experience. In the conclusion, how the learning and teaching experience of this trans-disciplinary design studio can offer us some observation that can help us reflect upon the constraints and division caused by the subject base curriculum will be pointed out. A series of concepts for course design and teaching strategies developed and implemented in this trans-disciplinary course are to be introduced as a way to promote learners’ self-motivated, collaborative, cross-disciplinary and student-centered learning skills. The outcome of this experimental course can exemplify an alternative approach that we could adopt in pursuing a remedy for dealing with the problematic issues of the current educational practice.

Keywords: course design, coaching strategy, subject base curriculum, trans-disciplinary

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Authors: Mohd Said Nurumal, Sarah Sheikh Abdul Karim

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Information regarding out of hospital cardiac arrest incidence include outcome in Malaysia is limited and fragmented. This study aims to identify incidence and adherence to protocol of out of hospital cardiac arrest and also to explore the issues faced by the pre-hospital personnel in regards managing cardiac arrest victim in Kuala Lumpur, Malaysia. A mixed method approach combining the qualitative and quantitative study design was used. The 285 pre-hospital care data sheet of out of hospital cardiac arrest during the year of 2011 were examined by using checklists for identify the incidence and adherence to protocol. Nine semi-structured interviews and two focus group discussions were performed. For the incidence based on the overall out of hospital cardiac arrest cases that occurred in 2011 (n=285), the survival rates were 16.8%. For adherence to protocol, only 89 (41.8%) of the cases adhered to the given protocol and 124 did not adhere to such protocol. The qualitative information provided insight about the issues related to out of hospital cardiac arrest in every aspect. All the relevant qualitative data were merged into few categories relating issues that could affect the management of out of hospital cardiac arrest performed by pre-hospital care team. One of the essential elements in the out of hospital cardiac arrest handling by pre-hospital care is to ensure increase of survival rates and excellent outcomes by adhering to given protocols based on international standard benchmarks. Measures are needed to strengthen the quick activation of the pre-hospital care service, prompt bystander cardiopulmonary resuscitation, early defibrillation and timely advanced cardiac life support and also to tackle all the issues highlighted in qualitative results.

Keywords: pre-hospital care, out of hospital cardiac arrest, incidence, protocol, mixed method research

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Authors: S. Ali, R. Yunus, A. Arif, Y. Ayaz, M. Baber Sial, R. Asif, N. Naseer, M. Jawad Khan

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In this study, we have proposed a gesture to emotion recognition method using flex sensors mounted on metacarpophalangeal joints. The flex sensors are fixed in a wearable glove. The data from the glove are sent to PC using Wi-Fi. Four gestures: finger pointing, thumbs up, fist open and fist close are performed by five subjects. Each gesture is categorized into sad, happy, and excited class based on the velocity and acceleration of the hand gesture. Seventeen inspectors observed the emotions and hand gestures of the five subjects. The emotional state based on the investigators assessment and acquired movement speed data is compared. Overall, we achieved 77% accurate results. Therefore, the proposed design can be used for emotional state detection applications.

Keywords: emotion identification, emotion models, gesture recognition, user perception

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Authors: John M. Ikome, Martha E. Ikome, Therese Van Wyk

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Productivity optimization of a company can significantly increase the company’s output and productivity which can be in the form of corrective actions of ineffective activities, process simplification, and reduction of variations, responsiveness, and reduction of set-up-time which are all under the classification of waste within the manufacturing environment. Deriving a means to eliminate a number of these issues has a key importance for manufacturing organization. This paper focused on a number of industrial engineering techniques which include a cause and effect diagram, to identify and optimize the method or systems being used. Based on our results, it shows that there are a number of variations within the production processes that can significantly disrupt the expected output.

Keywords: optimization, fishbone, diagram, productivity

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Authors: Lanchi Xie, Zhihui Li, Zhigang Li, Guiqiang Wang, Lei Xu, Yuwen Yan

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Image-based facial features can be classified into category recognition features and individual recognition features. Current automated face recognition systems extract a specific feature vector of different dimensions from a facial image according to their pre-trained neural network. However, to improve the efficiency of parameter calculation, an algorithm generally reduces the image details by pooling. The operation will overlook the details concerned much by forensic experts. In our experiment, we adopted a variety of face recognition algorithms based on deep learning, compared a large number of naturally collected face images with the known data of the same person's frontal ID photos. Downscaling and manual handling were performed on the testing images. The results supported that the facial recognition algorithms based on deep learning detected structural and morphological information and rarely focused on specific markers such as stains and moles. Overall performance, distribution of genuine scores and impostor scores, and likelihood ratios were tested to evaluate the accuracy of biometric systems and forensic experts. Experiments showed that the biometric systems were skilled in distinguishing category features, and forensic experts were better at discovering the individual features of human faces. In the proposed approach, a fusion was performed at the score level. At the specified false accept rate, the framework achieved a lower false reject rate. This paper contributes to improving the interpretability of the objective method of facial comparison and provides a novel method for human-machine collaboration in this field.

Keywords: likelihood ratio, automated facial recognition, facial comparison, biometrics

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Authors: Zhaofeng Li, Jun Kang Chow, Yu-Hsing Wang

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This paper attempts to bridge the soil properties and the mechanical response of soil in the discrete element method (DEM) simulation. The artificial neural network (ANN) was therefore adopted, aiming to reproduce the stress-strain-volumetric response when soil properties are given. 31 biaxial shearing tests with varying soil parameters (e.g., initial void ratio and interparticle friction coefficient) were generated using the DEM simulations. Based on these 45 sets of training data, a three-layer neural network was established which can output the entire stress-strain-volumetric curve during the shearing process from the input soil parameters. Beyond the training data, 2 additional sets of data were generated to examine the validity of the network, and the stress-strain-volumetric curves for both cases were well reproduced using this network. Overall, the ANN was found promising in predicting the soil behavior and reducing repetitive simulation work.

Keywords: artificial neural network, discrete element method, soil properties, stress-strain-volumetric response

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Authors: Haitham Qaralleh, Syed Z. Idid, Shahbudin Saad, Deny Susanti, Osama Althunibat

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This study was carried out to isolate the active antimicrobial compounds from Neopetrosia exigua using bio-guided assay isolation against Staphylococcus aureus. N. exigua was extracted using methanol and subjected to liquid-liquid extraction using solvents with different polarity (n-hexane, carbon tetrachloride, dichloromethane, n-butanol and water). Purification of the active components of n-butanol and dichloromethane fractions was done using Sephadex LH-20 and reverse phase chromatography. Based on the biological guided fractionation results, dichloromethane and n-butanol fractions showed the highest antimicrobial activity. Purification of the active components of n-butanol and dichloromethane fractions yielded three compounds. The structure of the isolated compounds were elucidated and found to be 5-hydroxy-1H-indole-3-carboxylic acid methyl ester, cyclo-1`-demethylcystalgerone and avarol derivative. Avarol was showed potent bactericidal effect against S. aureus. N. exigua appears to be rich source of natural antimicrobial agents. Further studies are needed to investigate the mode of action of these compounds.

Keywords: antimicrobial, avarol, Neopetrosia exigua, Staphylococcus aureus

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Authors: Ping Tan, Xiaomeng Su, Yi Shen

Abstract:

The motion intention in the motor imagery braincomputer interface is identified by classifying the event-related desynchronization (ERD) and event-related synchronization ERS characteristics of sensorimotor rhythm (SMR) in EEG signals. When the subject imagines different limbs or different parts moving, the rhythm components and bandwidth will change, which varies from person to person. How to find the effective sensorimotor frequency band of subjects is directly related to the classification accuracy of brain-computer interface. To solve this problem, this paper proposes a Minimum Distance to Riemannian Mean Classification method based on Non-Uniform Filter Banks. During the training phase, the EEG signals are decomposed into multiple different bandwidt signals by using multiple band-pass filters firstly; Then the spatial covariance characteristics of each frequency band signal are computered to be as the feature vectors. these feature vectors will be classified by the MDRM (Minimum Distance to Riemannian Mean) method, and cross validation is employed to obtain the effective sensorimotor frequency bands. During the test phase, the test signals are filtered by the bandpass filter of the effective sensorimotor frequency bands, and the extracted spatial covariance feature vectors will be classified by using the MDRM. Experiments on the BCI competition IV 2a dataset show that the proposed method is superior to other classification methods.

Keywords: non-uniform filter banks, motor imagery, brain-computer interface, minimum distance to Riemannian mean

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Authors: Muhammad Irfan Marwat, Sadaqat Jan, Syed Zafar Ali Shah

Abstract:

Software architecture plays a key role in software development but absence of formal description of software architecture causes different impede in software development. To cope with these difficulties, ontology has been used as artifact. This paper proposes ontology for software architectural design based on IEEE model for architecture description and Kruchten 4+1 model for viewpoints classification. For categorization of style and views, ISO/IEC 42010 has been used. Corpus method has been used to evaluate ontology. The main aim of the proposed ontology is to classify and locate software architectural design information.

Keywords: semantic-based software architecture, software architecture, ontology, software engineering

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Authors: C. S. Wong, K. H. Badri, N. Ataollahi, K. P. Law, M. S. Su’ait, N. I. Hassan

Abstract:

Novel bio-based polymer electrolyte was synthesized with LiClO4 as the main source of charge carrier. Initially, polyurethane-LiClO4 polymer electrolytes were synthesized via polymerization method with different NCO/OH ratios and labelled as PU1, PU2, PU3, and PU4. Subsequently, the chemical, thermal properties and ionic conductivity of the films produced were determined. Fourier transform infrared (FTIR) analysis indicates the co-ordination between Li+ ion and polyurethane in PU1 due to the greatest amount of hard segment of polyurethane in PU1 as proven by soxhlet analysis. The structures of polyurethanes were confirmed by 13 nuclear magnetic resonance spectroscopy (13C NMR) and FTIR spectroscopy. Differential scanning calorimetry (DSC) analysis indicates PU 1 has the highest glass transition temperature (Tg) corresponds to the most abundant urethane group which is the hard segment in PU1. Scanning electron microscopy (SEM) of the PU-LiClO4 shows the good miscibility between lithium salt and the polymer. The study found that PU1 possessed the greatest ionic conductivity (1.19 × 10-7 S.cm-1 at 298 K and 5.01 × 10-5 S.cm-1 at 373 K) and the lowest activation energy, Ea (0.32 eV) due to the greatest amount of hard segment formed in PU 1 induces the coordination between lithium ion and oxygen atom of carbonyl group in polyurethane. All the polyurethanes exhibited linear Arrhenius variations indicating ion transport via simple lithium ion hopping in polyurethane. This research proves the NCO content in polyurethane plays an important role in affecting the ionic conductivity of this polymer electrolyte.

Keywords: ionic conductivity, palm kernel oil-based monoester-OH, polyurethane, solid polymer electrolyte

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Authors: Dong Liu

Abstract:

By sending a high-frequency probe wave and a low-frequency pump wave to a specimen, the vibroacoustic method evaluates the defect’s severity according to the modulation index of the received signal. Many studies experimentally proved the significant sensitivity of the modulation index to the tiny contact type defect. However, it has also been found that the modulation index was highly affected by the frequency of probe or pump waves. Therefore, the chirp signal has been introduced to the VAM method since it can assess multiple frequencies in a relatively short time duration, so the robustness of the VAM method could be enhanced. Consequently, the signal processing method needs to be modified accordingly. Various studies utilized different algorithms or combinations of algorithms for processing the VAM signal method by chirp excitation. These signal process methods were compared and used for processing a VAM signal acquired from the steel samples.

Keywords: vibroacoustic modulation, nonlinear acoustic modulation, nonlinear acoustic NDT&E, signal processing, structural health monitoring

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Authors: Sajid Abas, Jon Pyo Hong, Jung-Ryun Le, Seungryong Cho

Abstract:

Computed tomography and laminography are heavily investigated in a compressive sensing based image reconstruction framework to reduce the dose to the patients as well as to the radiosensitive devices such as multilayer microelectronic circuit boards. Nowadays researchers are actively working on optimizing the compressive sensing based iterative image reconstruction algorithm to obtain better quality images. However, the effects of the sampled data’s properties on reconstructed the image’s quality, particularly in an insufficient sampled data conditions have not been explored in computed laminography. In this paper, we investigated the effects of two data properties i.e. sampling density and data incoherence on the reconstructed image obtained by conventional computed laminography and a recently proposed method called spherical sinusoidal scanning scheme. We have found that in a compressive sensing based image reconstruction framework, the image quality mainly depends upon the data incoherence when the data is uniformly sampled.

Keywords: computed tomography, computed laminography, compressive sending, low-dose

Procedia PDF Downloads 464