Search results for: time series data mining

Authors: Mohammed Farag, Mina Attari, S. Andrew Gadsden, Saeid R. Habibi

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Battery state of charge (SOC) estimation is an important parameter as it measures the total amount of electrical energy stored at a current time. The SOC percentage acts as a fuel gauge if it is compared with a conventional vehicle. Estimating the SOC is, therefore, essential for monitoring the amount of useful life remaining in the battery system. This paper looks at the implementation of three nonlinear estimation strategies for Li-Ion battery SOC estimation. One of the most common behavioral battery models is the one state hysteresis (OSH) model. The extended Kalman filter (EKF), the smooth variable structure filter (SVSF), and the time-varying smoothing boundary layer SVSF are applied on this model, and the results are compared.

Keywords: state of charge estimation, battery modeling, one-state hysteresis, filtering and estimation

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Authors: Anil P. Dewani, Alok S. Tripathi, Anil V. Chandewar

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Present manuscript reports the development and validation of a quantitative high performance liquid chromatography method for the pharmacokinetic evaluation of Glimepiride (GLM) and Ilaprazole (ILA) in rat plasma. The plasma samples were involved with Solid phase extraction process (SPE). The analytes were resolved on a Phenomenex C18 column (4.6 mm× 250 mm; 5 µm particle size) using a isocratic elution mode comprising methanol:water (80:20 % v/v) with pH of water modified to 3 using Formic acid, the total run time was 10 min at 225 nm as common wavelength, the flow rate throughout was 1ml/min. The method was validated over the concentration range from 10 to 600 ng/mL for GLM and ILA, in rat plasma. Metformin (MET) was used as Internal Standard. Validation data demonstrated the method to be selective, sensitive, accurate and precise. The limit of detection was 1.54 and 4.08 and limit of quantification was 5.15 and 13.62 for GLM and ILA respectively, the method demonstrated excellent linearity with correlation coefficients (r2) 0.999. The intra and inter-day precision (RSD%) values were < 2.0% for both ILA and GLM. The method was successfully applied in pharmacokinetic studies followed by oral administration in rats.

Keywords: pharmacokinetics, glimepiride, ilaprazole, HPLC, SPE

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Authors: Yusuf U. Datti

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It is becoming increasingly clear that the consumption of resources now enjoyed in the developed nations will be impossible to be sustained worldwide. While developing countries still have the advantage of low consumption and a smaller ecological footprint per person, they cannot simply develop in the same way as other western cities have developed in the past. The severe reality of population and consumption inequalities makes it contentious whether studies done in developed countries can be translated and applied to developing countries. Additional to this disparities, there are few or no metabolism of energy studies in Nigeria. Rather more contentious majority of energy metabolism studies have been done only in developed countries. While researches in Nigeria concentrate on other aspects/principles of sustainability such as water supply, sewage disposal, energy supply, energy efficiency, waste disposal, etc., which will not accurately capture the environmental impact of energy flow in Nigeria, this research will set itself apart by examining the flow of energy in Nigeria and the impact that the flow will have on the environment. The aim of the study is to examine and quantify the metabolic flows of energy in Nigeria and its corresponding environmental impact. The study will quantify the level and pattern of energy inflow and the outflow of greenhouse emissions in Nigeria. This study will describe measures to address the impact of existing energy sources and suggest alternative renewable energy sources in Nigeria that will lower the emission of greenhouse gas emissions. This study will investigate the metabolism of energy in Nigeria through a three-part methodology. The first step involved selecting and defining the study area and some variables that would affect the output of the energy (time of the year, stability of the country, income level, literacy rate and population). The second step involves analyzing, categorizing and quantifying the amount of energy generated by the various energy sources in the country. The third step involves analyzing what effect the variables would have on the environment. To ensure a representative sample of the study area, Africa’s most populous country, with economy that is the second biggest and that is among the top largest oil producing countries in the world is selected. This is due to the understanding that countries with large economy and dense populations are ideal places to examine sustainability strategies; hence, the choice of Nigeria for the study. National data will be utilized unless where such data cannot be found, then local data will be employed which will be aggregated to reflect the national situation. The outcome of the study will help policy-makers better target energy conservation and efficiency programs and enables early identification and mitigation of any negative effects in the environment.

Keywords: built environment, energy metabolism, environmental impact, greenhouse gas emissions and sustainability

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Authors: Slimane Ouhmad, Abdellah Halimi

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In this work, we have applied neural networks method MLP type to a database from an array of six sensors for the detection of three toxic gases. As the choice of the number of hidden layers and the weight values has a great influence on the convergence of the learning algorithm, we proposed, in this article, a mathematical formulation to determine the optimal number of hidden layers and good weight values based on the method of back propagation of errors. The results of this modeling have improved discrimination of these gases on the one hand, and optimize the computation time on the other hand, the comparison to other results achieved in this case.

Keywords: MLP Neural Network, back-propagation, number of neurons in the hidden layer, identification, computing time

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Authors: Atena Naeimi, Mehri-Sadat Ekrami-Kakhki

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Fe3O4 is one of the important magnetic oxides with spinel structure; it has exhibited unique electric and magnetic properties based on the electron transfer between Fe2+ and Fe3+ in the octahedral sites. Fe3O4 have received considerable attention in various areas such as cancer therapy, drug targeting, enzyme immobilization catalysis, magnetic cell separation, magnetic refrigeration systems and super-paramagnetic materials. Fe3O4–ZnO nanostructures were synthesized via a surfactant-free ultrasonic reaction at room temperatures. The effect of various parameters such as temperature, time, and power on the size and morphology of the product was investigated. Alternating gradient force magnetometer shows that Fe3O4 nanoparticles exhibit super-paramagnetic behaviour at room temperature. For preparation of nanocomposite 1 g of Fe3O4 nanostructures were dispersed in 100 mL of distilled water. 0.25 g of Zn (NO3)2 and 20 mL of NH3 solution 1 M were then slowly added to the solution under ultrasonic irradiation. The product was centrifuged, washed with distilled water and dried in the air. The photocatalytic behaviour of Fe3O4–ZnO nanoparticles was evaluated using the degradation of a methyl orange aqueous solution under ultraviolet light irradiation. As time increased, more and more methyl orange was adsorbed on the nanoparticles catalyst, until the absorption peak vanish. The methyl orange concentration decreased rapidly with increasing UV-irradiation time.

Keywords: nanocomposite, ultrasonic, paramagnetic, photocatalytic

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Authors: Ayliana Dharmawan, Heng Yong Sheng, Zhang Xiaojin, Tan Thai Lian

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To facilitate discharge planning, doctors are presently required to assign an Estimated Discharge Date (EDD) for each patient admitted to the hospital. This assignment of the EDD is largely based on the doctor’s judgment. This can be difficult for cases which are complex or relatively new to the doctor. It is hypothesized that a data-driven approach would be able to facilitate the doctors to make accurate estimations of the discharge date. Making use of routinely collected data on inpatient discharges between January 2013 and May 2016, a predictive model was developed using machine learning techniques to predict the Length of Stay (and hence the EDD) of inpatients, at the point of admission. The predictive performance of the model was compared to that of the clinicians using accuracy measures. Overall, the best performing model was found to be able to predict EDD with an accuracy improvement in Average Squared Error (ASE) by -38% as compared to the first EDD determined by the present method. It was found that important predictors of the EDD include the provisional diagnosis code, patient’s age, attending doctor at admission, medical specialty at admission, accommodation type, and the mean length of stay of the patient in the past year. The predictive model can be used as a tool to accurately predict the EDD.

Keywords: inpatient, estimated discharge date, EDD, prediction, data-driven

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Authors: Idris Lawal

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Electronic payment system is simply a payment or monetary transaction made over the internet or a network of computers. This study was carried out in order to assess how electronic payment system has impacted on banks service delivery, to examine the efficiency of electronic payment system in Nigeria and to determine the level of customer's satisfaction as a direct result of the deployment of electronic payment systems. It is an empirical study conducted using structured questionnaire distributed to officials and customers of Access Bank plc. Chi-square(x2) was adopted for the purpose of data analysis. The result of the study showed that the development of electronic payment system offer great benefit to bank customers including improved services, reduced turn-around time, ease of banking transaction, significant cost saving etc. The study recommends that customer protection laws should be properly put in place to safeguard the interest of end users of e-payment instruments.

Keywords: bank, electronic payment systems, service delivery, customer's satisfaction

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Authors: Misha Mirza

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In recent years, the definition of journalism in Pakistan has changed, so has the mindset of people and their approach towards a news story. For the audience, news has become more interesting than a drama or a film. This research thus provides an insight into Pakistan’s evolving media landscape. It tries not only to bring forth the outcomes of cross-platform cooperation among print and broadcast journalism but also gives an insight into the interactive data visualization techniques being used. The storytelling in journalism in Pakistan has evolved from depicting merely the truth to tweaking, fabricating and producing docu-dramas. It aims to look into how news is translated to a visual. Pakistan acquires a diverse cultural heritage and by engaging audience through media, this history translates into the storytelling platform today. The paper explains how journalists are thriving in a converging media environment and provides an analysis of the narratives in television talk shows today.’ Jack of all, master of none’ is being challenged by the journalists today. One has to be a quality information gatherer and an effective storyteller at the same time. Are journalists really looking more into what sells rather than what matters? Express Tribune is a very popular news platform among the youth. Not only is their newspaper more attractive than the competitors but also their style of narrative and interactive web stories lead to well-rounded news. Interviews are used as the basic methodology to get an insight into how data visualization is compassed. The quest for finding out the difference between visualization of information versus the visualization of knowledge has led the author to delve into the work of David McCandless in his book ‘Knowledge is beautiful’. Journalism in Pakistan has evolved from information to combining knowledge, infotainment and comedy. What is being criticized the most by the society most often becomes the breaking news. Circulation in today’s world is carried out in cultural and social networks. In recent times, we have come across many examples where people have gained overnight popularity by releasing songs with substandard lyrics or senseless videos perhaps because creativity has taken over information. This paper thus discusses the various platforms of convergence journalism from Pakistan’s perspective. The study concludes with proving how Pakistani pop culture Truck art is coexisting with all the platforms in convergent journalism. The changing media landscape thus challenges the basic rules of journalism. The slapstick humor and ‘jhatka’ in Pakistani talk shows has evolved from the Pakistani truck art poetry. Mobile journalism has taken over all the other mediums of journalism; however, the Pakistani culture coexists with the converging landscape.

Keywords: convergence journalism in Pakistan, data visualization, interactive narrative in Pakistani news, mobile journalism, Pakistan's truck art culture

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Authors: Kasun P. Wijayaratna, Lauren Gardner, Taha Hossein Rashidi

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Undergraduate students entering university across the last 2 to 3 years tend to be born during the middle years of the 1990s. This generation of students has been exposed to the internet and the desire and dependency on technology since childhood. Brains develop based on environmental influences and technology has wired this generation of student to be attuned to sophisticated complex visual imagery, indicating visual forms of learning may be more effective than the traditional lecture or discussion formats. Furthermore, post-millennials perspectives on career are not focused solely on stability and income but are strongly driven by interest, entrepreneurship and innovation. Accordingly, it is important for educators to acknowledge the generational shift and tailor the delivery of learning material to meet the expectations of the students and the needs of industry. In the context of transport engineering, effectively teaching undergraduate students the basic principles of transport planning, traffic engineering and highway design is fundamental to the progression of the profession from a practice and research perspective. Recent developments in technology have transformed the discipline as practitioners and researchers move away from the traditional “pen and paper” approach to methods involving the use of computer programs and simulation. Further, enhanced accessibility of technology for students has changed the way they understand and learn material being delivered at tertiary education institutions. As a consequence, blended learning approaches, which aim to integrate face to face teaching with flexible self-paced learning resources, have become prevalent to provide scalable education that satisfies the expectations of students. This research study involved the development of a series of ‘Blended Learning’ initiatives implemented within an introductory transport planning and geometric design course, CVEN2401: Sustainable Transport and Highway Engineering, taught at the University of New South Wales, Australia. CVEN2401 was modified by conducting interactive polling exercises during lectures, including weekly online quizzes, offering a series of supplementary learning videos, and implementing a realistic design project that students needed to complete using modelling software that is widely used in practice. These activities and resources were aimed to improve the learning environment for a large class size in excess of 450 students and to ensure that practical industry valued skills were introduced. The case study compared the 2016 and 2017 student cohorts based on their performance across assessment tasks as well as their reception to the material revealed through student feedback surveys. The initiatives were well received with a number of students commenting on the ability to complete self-paced learning and an appreciation of the exposure to a realistic design project. From an educator’s perspective, blending the course made it feasible to interact and engage with students. Personalised learning opportunities were made available whilst delivering a considerable volume of complex content essential for all undergraduate Civil and Environmental Engineering students. Overall, this case study highlights the value of blended learning initiatives, especially in the context of large class size university courses.

Keywords: blended learning, highway design, teaching, transport planning

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Authors: M. A. At-Tasneem, N. T. Rao, T. M. Y. S. Tuan Ya, M. S. Idris, M. Ammar

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River flow over micro hydro power (MHP) turbines of multiple arrays arrangement is simulated with computational fluid dynamics (CFD) software to obtain the flow characteristics. In this paper, CFD software is used to simulate the water flow over MHP turbines as they are placed in a river. Multiple arrays arrangement of MHP turbines lead to generate large amount of power. In this study, a river model is created and simulated in CFD software to obtain the water flow characteristic. The process then continued by simulating different types of arrays arrangement in the river model. A MHP turbine model consists of a turbine outer body and static propeller blade in it. Five types of arrangements are used which are parallel, series, triangular, square and rhombus with different spacing sizes. The velocity profiles on each MHP turbines are identified at the mouth of each turbine bodies. This study is required to obtain the arrangement with increasing spacing sizes that can produce highest power density through the water flow variation.

Keywords: micro hydro power, CFD, arrays arrangement, spacing sizes, velocity profile, power

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Authors: Varsha Puri, Sharon Hudson, Ian Kim

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Background: Incest-related childhood sexual abuse (IRCSA) is challenging to study due to the shame and secrecy experienced by its survivors. Ramifications of IRCSA worsen when it is unidentified, and interventions are not made. IRCSA perspectives are essential for future prevention and intervention strategies. However, there is limited understanding of this population’s experiences, perspectives, and long-term struggles. To date, research for IRCSA has utilized data from treatment programs and qualitative research with cohorts of 10-20 people, much of the data is from 10-40 years prior. Methods. In June 2018, an anonymous online survey was posted to multiple social media sites (e.g., Facebook IRCSA groups) and sexual abuse resource sites. Survey responses were collected for a year. The survey collected non-identifying demographics, IRCSA experiences, and outcomes data. Results: We obtained 1310 completed surveys. Demographics of all ages, racial backgrounds, financial backgrounds, and genders were obtained; the majority identified as white (81%) and female (76%). Childhood sexual abuse (CSA) started before the age of 6 in 49% and was endured for more than one year in 84% of respondents, and 39% reported ten or more years of abuse. CSA by multiple perpetrators occurred in 58%, while 8% had ten or more perpetrators. CSA by perpetrators under 21 years old was reported by 46%. Female perpetrators were reported by 28% of respondents. Fathers were the highest reported sexual abusers at 60%, and mothers were reported at 17%. Only 16% reported that at least one of their perpetrators was prosecuted for sexual abuse of a minor. Respondents confirmed that 54% of the time, they informed an adult of the abuse; only 2% agreed that “an intervention was made by the family that protected me.” A majority reported that IRCSA has negatively impacted their intimate/sexual relationships (96%) and mental health (96%). A majority reported negative impacts on biological family relationships (88%), physical health (73%), finances (59%), educational achievement (57%), and employment (56%). When asked about suffering from addiction, 85% of respondents answered yes. Prevention strategies selected most by respondents include early school education around CSA prevention (67%), removing the statute of limitations for reporting CSA (69%), and improved laws protecting IRCSA survivors (63%). Conclusion: The data document that IRCSA can be pervasive, and the dearth of intervention and support for survivors have major lasting impacts. Survivors have a unique and valuable perspective on what interventions are needed to prevent IRCSA and support survivors; their voice has long been unheard in crafting prevention and intervention policies and services. These results thus provide an important call to action from these critical stakeholders. Pediatricians should recognize that perpetrators can be pediatric patients, women, and parents. Pediatricians can advocate for more early CSA prevention education and policy changes that remove the statute of limitations for reporting CSA.

Keywords: incest, childhood sexual abuse, incest-related childhood sexual abuse, incest survivor

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Authors: N. Hoosain, S. Nene, B. Pearce, C. Jacobs, M. Du Plessis, M. Benjeddou

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Organic Cation Transporters play a vital role in the absorption, tissue distribution and elimination of various substrates. Numerous studies have suggested that variations in non-synonymous single nucleotide polymorphisms (SNPs) of SLC22A2 could influence an individual’s response to various treatments, including clinically important drugs. This study is the first to determine the baseline frequency distribution for twenty SNPs of SLC22A2in the Zulu population. DNA was collected from 101 unrelated “healthy” Zulu participants. Genotypes of all samples were determined using a multiplex PCR and SNaPshot assay followed by the generation of the haplotype structure. This is the first time that the baseline frequency distribution of SNPs is reported for the Zulu population. Data from this study could be used in in vitro and in vivo pharmacogenetic and pharmacokinetic studies to evaluate the potential role the studied SNPs play in the therapeutic efficacy of clinically important drugs.

Keywords: SLC22A2 gene, SNaPshot assay, PCR, Zulu population

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Authors: Živa Ravnikar, Alfonso Bahillo Martinez, Barbara Goličnik Marušić

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Climate change mitigation has been formally adopted and announced by countries over the globe, where cities are targeting carbon neutrality through various more or less successful, systematic, and fragmentary actions. The article is based on the fact that environmental conditions affect human comfort and the usage of space. Urban planning can, with its sustainable solutions, not only support climate mitigation in terms of a planet reduction of global warming but as well enabling natural processes that in the immediate vicinity produce environmental conditions that encourage people to walk or cycle. However, the article draws attention to the importance of integrating climate consideration into urban planning, where detailed environmental data play a key role, enabling urban planners to improve or monitor environmental conditions on cycle paths. In a practical aspect, this paper tests a particular ICT tool, a prototype used for environmental data. Data gathering was performed along the cycling lanes in Ljubljana (Slovenia), where the main objective was to assess the tool's data applicable value within the planning of comfortable cycling lanes. The results suggest that such transportable devices for in-situ measurements can help a researcher interpret detailed environmental information, characterized by fine granularity and precise data spatial and temporal resolution. Data can be interpreted within human comfort zones, where graphical representation is in the form of a map, enabling the link of the environmental conditions with a spatial context. The paper also provides preliminary results in terms of the potential of such tools for identifying the correlations between environmental conditions and different spatial settings, which can help urban planners to prioritize interventions in places. The paper contributes to multidisciplinary approaches as it demonstrates the usefulness of such fine-grained data for better consideration of microclimatology in urban planning, which is a prerequisite for creating climate-comfortable cycling lanes promoting active mobility.

Keywords: information and communication technology tools, urban planning, human comfort, microclimate, cycling lanes

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Authors: Marjila Burhanzoi, Kenta Onohara, Tomoaki Ikegami

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Faults in photovoltaic (PV) modules should be detected to the greatest extent as early as possible. For that conventional fault detection methods such as electrical characterization, visual inspection, infrared (IR) imaging, ultraviolet fluorescence and electroluminescence (EL) imaging are used, but they either fail to detect the location or category of fault, or they require expensive equipment and are not convenient for onsite application. Hence, these methods are not convenient to use for monitoring small-scale PV systems. Therefore, low cost and efficient inspection techniques with the ability of onsite application are indispensable for PV modules. In this study in order to establish efficient inspection technique, correlation between faults and magnetic flux density on the surface is of crystalline PV modules are investigated. Magnetic flux on the surface of normal and faulted PV modules is measured under the short circuit and illuminated conditions using two different sensor devices. One device is made of small integrated sensors namely 9-axis motion tracking sensor with a 3-axis electronic compass embedded, an IR temperature sensor, an optical laser position sensor and a microcontroller. This device measures the X, Y and Z components of the magnetic flux density (Bx, By and Bz) few mm above the surface of a PV module and outputs the data as line graphs in LabVIEW program. The second device is made of a laser optical sensor and two magnetic line sensor modules consisting 16 pieces of magnetic sensors. This device scans the magnetic field on the surface of PV module and outputs the data as a 3D surface plot of the magnetic flux intensity in a LabVIEW program. A PC equipped with LabVIEW software is used for data acquisition and analysis for both devices. To show the effectiveness of this method, measured results are compared to those of a normal reference module and their EL images. Through the experiments it was confirmed that the magnetic field in the faulted areas have different profiles which can be clearly identified in the measured plots. Measurement results showed a perfect correlation with the EL images and using position sensors it identified the exact location of faults. This method was applied on different modules and various faults were detected using it. The proposed method owns the ability of on-site measurement and real-time diagnosis. Since simple sensors are used to make the device, it is low cost and convenient to be sued by small-scale or residential PV system owners.

Keywords: fault diagnosis, fault location, integrated sensors, PV modules

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Authors: Tonislav Ivanov, Oleksii Nedashkivskyi, Denis Babeshko, Vadim Pinskiy, Matthew Putman

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Training a machine learning model for object detection that generalizes well is known to benefit from a training dataset with diverse examples. However, training datasets usually contain many repeats of common examples of a class and lack rarely seen examples. This is due to the process commonly used during human annotation where a person would proceed sequentially through a list of images labeling a sufficiently high total number of examples. Instead, the method presented involves an active process where, after the initial labeling of several images is completed, the next subset of images for labeling is selected by an algorithm. This process of algorithmic image selection and manual labeling continues in an iterative fashion. The algorithm used for the image selection is a deep learning algorithm, based on the U-shaped architecture, which quantifies the presence of unseen data in each image in order to find images that contain the most novel examples. Moreover, the location of the unseen data in each image is highlighted, aiding the labeler in spotting these examples. Experiments performed using semiconductor wafer data show that labeling a subset of the data, curated by this algorithm, resulted in a model with a better performance than a model produced from sequentially labeling the same amount of data. Also, similar performance is achieved compared to a model trained on exhaustive labeling of the whole dataset. Overall, the proposed approach results in a dataset that has a diverse set of examples per class as well as more balanced classes, which proves beneficial when training a deep learning model.

Keywords: computer vision, deep learning, object detection, semiconductor

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Authors: A. Chegenizadeh, M. Keramatikerman, H. Nikraz

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Bitumen is one of the most applicable materials in pavement engineering. It is a binding material with unique viscoelastic properties, especially when it mixes with polymer. In this study, to figure out the viscoelastic behaviour of the polymer modified with bitumen (PMB), a series of dynamic shearing rheological (DSR) tests were conducted. Four percentages of lime (i.e. 1%, 2%, 4% and 5%) were mixed with PMB and tested under four different temperatures including 64ºC, 70ºC, 76ºC and 82ºC. The results indicated that complex shearing modulus (G*) increased by increasing the frequency due to raised resistance against deformation. The phase angle (δ) showed a decreasing trend by incrementing the frequency. The addition of lime percentages increased the complex modulus value and declined phase angle parameter. Increasing the temperature decreased the complex modulus and increased the phase angle until 70ºC. The decreasing trend of rutting factor with increasing temperature revealed that rutting factor improved by the addition of the lime to the PMB.

Keywords: rheological properties, DSR test, polymer mixed with bitumen (PMB), complex modulus, lime

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Authors: Zhang Jiafeng

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Stone houses, represented by Shitang town, Wenling town, Taizhou city, are very precious cultural relics in Zhejiang province and even in the whole country. The coastal residences in eastern Zhejiang with distinctive regional characteristics are completely different from the traditional residential styles in the inland areas of Zhejiang. However, with the aggravation of the conflict between the use function of traditional stone houses and the modern lifestyle, and the lack of effective protection, stone houses are disappearing in large numbers. Therefore, it is very important to protect and inherit the stone house building, and make effective and feasible development strategies. This paper will analyze the formation background, location selection, plane layout, architectural form, spatial organization, material application, and construction technology of the stone houses through literature research and field investigation. In addition, a series of feasibility studies are carried out on the protection and renovation of stone houses. The ultimate purpose is to attract people's attention and provide some reference for the protection, inheritance, development, and utilization of traditional houses in coastal areas.

Keywords: regional, stone house building, traditional houses, Wenling Shitang

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Authors: Guillaume Craveur

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The evaluation of the passenger exchange time is necessary for railway operators in order to optimize and dimension rail traffic. Several influential parameters are identified and studied. Each parameter leads to a modeling completed with the buildingEXODUS software. The objective is the modelling of passenger exchanges measured by passenger counting. Population size is dimensioned using passenger counting files which are a report of the train service and contain following useful informations: number of passengers who get on and leave the train, exchange time. These information are collected by sensors placed at the top of each train door. With passenger counting files it is possible to know how many people are engaged in the exchange and how long is the exchange, but it is not possible to know passenger flow of the door. All the information about observed exchanges are thus not available. For this reason and in order to minimize inaccuracies, only short exchanges (less than 30 seconds) with a maximum of people are performed.

Keywords: passengers exchange, numerical tools, rolling stock, platforms

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Authors: Anders S. Kristensen, Dewan Ahsan, Saqib Mehmood, Shakeel Ahmed

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Traffic accidents are a result of the convergence of hazards, malfunctioning of vehicles and human negligence that have adverse economic and health impacts and effects. Unfortunately, avoiding them completely is very difficult, but with quick response to rescue and first aid, the mortality rate of inflicted persons can be reduced significantly. Smart and innovative technologies can play a pivotal role to respond faster to traffic crash emergencies comparing conventional means of transportation. For instance, Rescue Emergency Drone (RED) can provide faster and real-time crash site risk assessment to emergency medical services, thereby helping them to quickly and accurately assess a situation, dispatch the right equipment and assist bystanders to treat inflicted person properly. To conduct a research in this regard, the case of a traffic roundabout that is prone to frequent traffic accidents on the outskirts of Esbjerg, a town located on western coast of Denmark is hypothetically considered. Along with manual calculations, Emergency Disaster Management Simulation (EDMSIM) has been used to verify the response time of RED from a fire station of the town to the presumed crash site. The results of the study demonstrate the robustness of RED into emergency services to help save lives. 

Keywords: automated external defibrillator, medical emergency, response time, unmanned aerial system

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Authors: Chiung-Hui Chen

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Traditional service channel is losing its edge due to emerging service technology. To establish interaction with the clients, the service industry is using effective mechanism to give clients direct access to services with emerging technologies. Thus, as service science receives attention, special and unique consumption pattern evolves; henceforth, leading to new market mechanism and influencing attitudes toward life and consumption patterns. The market demand for customized services is thus valued due to the emphasis of personal value, and is gradually changing the demand and supply relationship in the traditional industry. In respect of interior design service, in the process of traditional interior design, a designer converts to a concrete form the concept generated from the ideas and needs dictated by a user (client), by using his/her professional knowledge and drawing tool. The final product is generated through iterations of communication and modification, which is a very time-consuming process. Although this process has been accelerated with the help of computer graphics software today, repeated discussions and confirmations with users are still required to complete the task. In consideration of what is addressed above a space user’s life model is analyzed with visualization technique to create an interaction system modeled after interior design knowledge. The space user document intuitively personal life experience in a model requirement chart, allowing a researcher to analyze interrelation between analysis documents, identify the logic and the substance of data conversion. The repeated data which is documented are then transformed into design information for reuse and sharing. A professional interior designer may sort out the correlation among user’s preference, life pattern and design specification, thus deciding the critical design elements in the process of service design.

Keywords: information design, life model-based, aesthetic computing, communication

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Authors: Chih-Chia Lin, Ching-Ying Huang, Cheng-Hong Liu, Wen-Lin Wang

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A complete fuel cell stack comprises several single cells with end plates, bipolar plates, gaskets and membrane electrode assembly (MEA) components. Electrons generated from cells are conducted through bipolar plates. The amount of cells' components increases as the stack voltage increases, complicating the fuel cell assembly process and mass production. Stack assembly error influence cell performance. PEM fuel cell stack importing laser welding technique could eliminate transverse deformation between bipolar plates to promote stress uniformity of cell components as bipolar plates and MEA. Simultaneously, bipolar plates were melted together using laser welding to decrease interface resistance. A series of experiments as through-plan and in-plan resistance measurement test was conducted to observe the laser welding effect. The result showed that the through-plane resistance with laser welding was a drop of 97.5-97.6% when the contact pressure was about 1MPa to 3 MPa, and the in-plane resistance was not significantly different for laser welding.

Keywords: PEM fuel cell, laser welding, through-plan, in-plan, resistance

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Authors: Kibreab Alene Fenite

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The purpose of this study is to investigate the implementation and challenges of different assessment methods for physical education class in some selected preparatory schools of kirkos sub city. The participants in this study are teachers, students, department heads and school principals from 4 selected schools. Of the total 8 schools offering in kirkos sub city 4 schools (Dandi Boru, Abiyot Kirse, Assay, and Adey Ababa) are selected by using simple random sampling techniques and from these schools all (100%) of teachers, 100% of department heads and school principals are taken as a sample as their number is manageable. From the total 2520 students, 252 (10%) of students are selected using simple random sampling. Accordingly, 13 teachers, 252 students, 4 department heads and 4 school principals are taken as a sample from the 4 selected schools purposefully. As a method of data gathering tools; questionnaire and interview are employed. To analyze the collected data, both quantitative and qualitative methods are used. The result of the study revealed that assessment in physical education does not implement properly: lack of sufficient materials, inadequate time allotment, large class size, and lack of collaboration and working together of teachers towards assessing the performance of students, absence of guidelines to assess the physical education subject, no different assessment method that is implementing on students with disabilities in line with their special need are found as major challenges in implementing the current assessment method of physical education. To overcome these problems the following recommendations have been forwarded. These are: the necessary facilities and equipment should be available; In order to make reliable, accurate, objective and relevant assessment, teachers of physical education should be familiarized with different assessment techniques; Physical education assessment guidelines should be prepared, and guidelines should include different types of assessment methods; qualified teachers should be employed, and different teaching room must be build.

Keywords: assessment, challenges, equipment, guidelines, implementation, performance

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Authors: Getinet Gezahegn Gebre

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The study examined the impact of gender differences on Crop productivity in Decha woreda of south west Kafa zone, located 140 Km from Jimma Town and 460 km south west of Addis Ababa, between Bonga town and Omo River. The specific objectives were to assess the extent to which the agricultural production system is gender oriented, to examine access and control over productive resources, and to estimate men’s and women’s productivity in agriculture. Cross-sectional data collected from a total of 140 respondents were used in this study, whereby 65 were female headed and 75 were male headed households. The data were analyzed by using Statistical Package for Social Science (SPSS). Descriptive statistics such as frequency, mean, percentage, t-test, and chi-square were used to summarize and compare the information between the two groups. Moreover, Cobb-Douglas(CD) production function was to estimate the productivity difference in agriculture between male and female headed households. Results of the study showed that male headed households (MHH) own more productive resources such as land, livestock, labor, and other agricultural inputs as compared to female headed households (FHH). Moreover, the estimate of CD production function shows that livestock, herbicide use, land size, and male labor were statistically significant for MHH, while livestock, land size, herbicides use and female labor were significant variables for FHH. The crop productivity difference between MHH and FHH was about 68.83% in the study area. However, if FHH had equal access to the inputs as MHH, the gross value of the output would be higher by 23.58% for FHH. This might suggest that FHH would be more productive than MHH if they had equal access to inputs as MHH. Based on the results obtained, the following policy implication can be drawn: accessing FHH to inputs that increase the productivity of agriculture, such as herbicides, livestock, and male labor; increasing the productivity of land; and introducing technologies that reduce the time and energy of women, especially for inset processing.

Keywords: gender difference, crop, productivity, efficiency

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Authors: Kostas Kouvaris, Anastasia Eleftheriou, Georgios A. Sarantitis, Apostolos Chondronasios

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To achieve the objective of almost zero carbon energy solutions by 2050, the EU needs to accelerate the development of integrated, highly efficient and environmentally friendly solutions. In this direction, district heating and cooling (DHC) emerges as a viable and more efficient alternative to conventional, decentralized heating and cooling systems, enabling a combination of more efficient renewable and competitive energy supplies. In this paper, we develop a forecasting tool for near real-time local weather and thermal energy demand predictions for an entire DHC network. In this fashion, we are able to extend the functionality and to improve the energy efficiency of the DHC network by predicting and adjusting the heat load that is distributed from the heat generation plant to the connected buildings by the heat pipe network. Two case-studies are considered; one for Vransko, Slovenia and one for Montpellier, France. The data consists of i) local weather data, such as humidity, temperature, and precipitation, ii) weather forecast data, such as the outdoor temperature and iii) DHC operational parameters, such as the mass flow rate, supply and return temperature. The external temperature is found to be the most important energy-related variable for space conditioning, and thus it is used as an external parameter for the energy demand models. For the development of the forecasting tool, we use state-of-the-art deep neural networks and more specifically, recurrent networks with long-short-term memory cells, which are able to capture complex non-linear relations among temporal variables. Firstly, we develop models to forecast outdoor temperatures for the next 24 hours using local weather data for each case-study. Subsequently, we develop models to forecast thermal demand for the same period, taking under consideration past energy demand values as well as the predicted temperature values from the weather forecasting models. The contributions to the scientific and industrial community are three-fold, and the empirical results are highly encouraging. First, we are able to predict future thermal demand levels for the two locations under consideration with minimal errors. Second, we examine the impact of the outdoor temperature on the predictive ability of the models and how the accuracy of the energy demand forecasts decreases with the forecast horizon. Third, we extend the relevant literature with a new dataset of thermal demand and examine the performance and applicability of machine learning techniques to solve real-world problems. Overall, the solution proposed in this paper is in accordance with EU targets, providing an automated smart energy management system, decreasing human errors and reducing excessive energy production.

Keywords: machine learning, LSTMs, district heating and cooling system, thermal demand

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Authors: Ya Lv

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This article presents the application of the semi-analytic method (SAM) in the thermal management solution (TMS) of the energy storage system (ESS). The TMS studied in this work is fluid cooling. In fluid cooling, both effective heat conduction and heat convection are indispensable due to the heat transfer from solid to fluid. Correspondingly, an efficient TMS requires a design investigation of the following parameters: fluid inlet temperature, ESS initial temperature, fluid flow rate, working c rate, continuous working time, and materials properties. Their variation induces a change of thermal performance in the battery module, which is usually evaluated by numerical simulation. Compared to complicated computation resources and long computation time in simulation, the SAM is developed in this article to predict the thermal influence within a few seconds. In SAM, a fast prediction model is reckoned by combining numerical simulation with theoretical/empirical equations. The SAM can explore the thermal effect of boundary parameters in both steady-state and transient heat transfer scenarios within a short time. Therefore, the SAM developed in this work can simplify the design cycle of TMS and inspire more possibilities in TMS design.

Keywords: semi-analytic method, fast prediction model, thermal influence of boundary parameters, energy storage system

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Authors: Shuenn-Yih Chang, Chiu-LI Huang, Ngoc-Cuong Tran

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A new family of structure-dependent integration methods, whose coefficients of the difference equation for displacement increment are functions of the initial structural properties and the step size for time integration, is proposed in this work. This family method can simultaneously integrate the controllable numerical dissipation, explicit formulation and unconditional stability together. In general, its numerical dissipation can be continuously controlled by a parameter and it is possible to achieve zero damping. In addition, it can have high-frequency damping to suppress or even remove the spurious oscillations high frequency modes. Whereas, the low frequency modes can be very accurately integrated due to the almost zero damping for these low frequency modes. It is shown herein that the proposed family method can have exactly the same numerical properties as those of HHT-α method for linear elastic systems. In addition, it still preserves the most important property of a structure-dependent integration method, which is an explicit formulation for each time step. Consequently, it can save a huge computational efforts in solving inertial problems when compared to the HHT-α method. In fact, it is revealed by numerical experiments that the CPU time consumed by the proposed family method is only about 1.6% of that consumed by the HHT-α method for the 125-DOF system while it reduces to be 0.16% for the 1000-DOF system. Apparently, the saving of computational efforts is very significant.

Keywords: structure-dependent integration method, nonlinear dynamic analysis, unconditional stability, numerical dissipation, accuracy

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Authors: Alejandro Villegas, Cihan Varol

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Voice over Internet Protocol (VoIP) products is an emerging technology that can contain forensically important information for a criminal activity. Without having the user name and passwords, this forensically important information can still be gathered by the investigators. Although there are a few VoIP forensic investigative applications available in the literature, most of them are particularly designed to collect evidence from the Skype product. Therefore, in order to assist law enforcement with collecting forensically important information from variety of Betamax VoIP tools, CVOIP-FRU framework is developed. CVOIP-FRU provides a data gathering solution that retrieves usernames, contact lists, as well as call and SMS logs from Betamax VoIP products. It is a scripting utility that searches for data within the registry, logs and the user roaming profiles in Windows and Mac OSX operating systems. Subsequently, it parses the output into readable text and html formats. One superior way of CVOIP-FRU compared to the other applications that due to intelligent data filtering capabilities and cross platform scripting back end of CVOIP-FRU, it is expandable to include other VoIP solutions as well. Overall, this paper reveals the exploratory analysis performed in order to find the key data paths and locations, the development stages of the framework, and the empirical testing and quality assurance of CVOIP-FRU.

Keywords: betamax, digital forensics, report utility, VoIP, VoIPBuster, VoIPWise

Procedia PDF Downloads 280

Authors: Juan Li, Jiawen Qiu, Yuchuan Chu, Tianping Zhang, Wei Meng, Yanhui Jia, Xiaohui Liu

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This article developed an ion thruster optic system sputter erosion depth numerical 3D model by IFE-PIC (Immersed Finite Element-Particle-in-Cell) and Mont Carlo method, and calculated the downstream surface sputter erosion rate of accelerator grid; Compared with LIPS-200 life test data, the results of the numerical model are in reasonable agreement with the measured data. Finally, we predict the lifetime of the 20cm diameter ion thruster via the erosion data obtained with the model. The ultimate result demonstrates that under normal operating condition, the erosion rate of the grooves wears on the downstream surface of the accelerator grid is 34.6μm⁄1000h, which means the conservative lifetime until structural failure occurring on the accelerator grid is 11500 hours.

Keywords: ion thruster, accelerator gird, sputter erosion, lifetime assessment

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Authors: Lydia Novozhilova, Vladimir Urazhdin

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An optimization problem for reinforced thin-walled vessels under uniform external pressure is considered. The conventional approaches to optimization generally start with pre-defined geometric parameters of the vessels, and then employ analytic or numeric calculations and/or experimental testing to verify functionality, such as stability under the projected conditions. The proposed approach consists of two steps. First, the feasibility domain will be identified in the multidimensional parameter space. Every point in the feasibility domain defines a design satisfying both geometric and functional constraints. Second, an objective function defined in this domain is formulated and optimized. The broader applicability of the suggested methodology is maximized by implementing the Support Vector Machines (SVM) classification algorithm of machine learning for identification of the feasible design region. Training data for SVM classifier is obtained using the Simulation package of SOLIDWORKS®. Based on the data, the SVM algorithm produces a curvilinear boundary separating admissible and not admissible sets of design parameters with maximal margins. Then optimization of the vessel parameters in the feasibility domain is performed using the standard algorithms for the constrained optimization. As an example, optimization of a ring-stiffened closed cylindrical thin-walled vessel with semi-spherical caps under high external pressure is implemented. As a functional constraint, von Mises stress criterion is used but any other stability constraint admitting mathematical formulation can be incorporated into the proposed approach. Suggested methodology has a good potential for reducing design time for finding optimal parameters of thin-walled vessels under uniform external pressure.

Keywords: design parameters, feasibility domain, von Mises stress criterion, Support Vector Machine (SVM) classifier

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Authors: Alexander Marx

Abstract:

Measuring and mitigating market risk is essential for the stability of enterprises, especially for major banking corporations and investment bank firms. To employ these risk measurement and mitigation processes, the Value at Risk (VaR) is the most commonly used risk metric by practitioners. In the past years, we have seen significant weaknesses in the predictive performance of the VaR in times of financial market crisis. To address this issue, the purpose of this study is to investigate the value-at-risk (VaR) estimation models and their predictive performance by applying a series of backtesting methods on the stock market indices of the G7 countries (Canada, France, Germany, Italy, Japan, UK, US, Europe). The study employs parametric, non-parametric, and semi-parametric VaR estimation models and is conducted during three different periods which cover the most recent financial market crisis: the overall period (2006–2022), the global financial crisis period (2008–2009), and COVID-19 period (2020–2022). Since the regulatory authorities have introduced and mandated the Conditional Value at Risk (Expected Shortfall) as an additional regulatory risk management metric, the study will analyze and compare both risk metrics on their predictive performance.

Keywords: value at risk, financial market risk, banking, quantitative risk management

Procedia PDF Downloads 82