Search results for: mitigation techniques

Authors: Haider Javed Uppal, Javed Yunas Uppal

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In today's globalized world, it is necessary to develop a form of music that is able to evoke equal emotional responses among people from diverse cultural backgrounds. Indigenous cultures throughout history have developed their own music cognition, specifically in terms of the connections between music and mood. With the advancements in artificial intelligence technologies, it has become possible to analyze and categorize music features such as timbre, harmony, melody, and rhythm and relate them to the resulting mood effects experienced by listeners. This paper presents a model that utilizes a screenshot translator to convert music from different origins into waveforms, which are then analyzed using machine learning and information retrieval techniques. By connecting these waveforms with Thayer's matrix of moods, a mood classifier has been developed using fuzzy logic algorithms to determine the emotional impact of different types of music on listeners from various cultures.

Keywords: cognition, world music, artificial intelligence, Thayer’s matrix

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Authors: Nam Chol Yu, GyongIl Chu, HoJong Ri

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Using DLTS (Deep-level transient spectroscopy) measurement techniques, we determined the dominant recombination center levels (defects of both A and B) in gold and platinum doped n-type silicon. Also, the injection and temperature dependence of the Shockley-Read-Hall (SRH) carrier lifetime was studied under low-level injection and high-level injection. Here measurements show that the dominant level under low-level injection located at EC-0.25 eV (A) correlated to the Pt+G1 and the dominant level under high-level injection located at EC-0.54 eV (B) correlated to the Au+G4. Finally, A and B are the same dominant levels for controlling the lifetime in gold-platinum doped n-silicon.

Keywords: recombination center level, lifetime, carrier lifetime control, Gold, Platinum, Silicon

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Authors: Blaise Fyama, Elie Museng, Grace Mukoma

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In this article we present a java implementation of video telephony using the SIP protocol (Session Initiation Protocol). After a functional analysis of the SIP protocol, we relied on the work of Italian researchers of University of Parma-Italy to acquire adequate libraries for the development of our own communication tool. In order to optimize the code and improve the prototype, we used, in an incremental approach, test techniques based on a static analysis based on the evaluation of the complexity of the software with the application of metrics and the number cyclomatic of Mccabe. The objective is to promote the emergence of local start-ups producing IP video in a well understood local context. We have arrived at the creation of a video telephony tool whose code is optimized.

Keywords: static analysis, coding complexity metric mccabe, Sip, uml

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Authors: Rattama Rattanawongsa

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As technologies continue to develop and evolve, online learning has become one of the most popular ways of gaining access to learning. Worldwide, many students are engaging in both online and blended courses in growing numbers through e-learning. However, online learning is a form of teaching that has many benefits for learners but still has some limitations. The high attrition rates of students tend to be due to lack of motivation to succeed. Gamification is the use of game design techniques, game thinking and game mechanics in non-game context, such as learning. The gamifying method can motivate students to learn with fun and inspire them to continue learning. This paper aims to describe how the gamification work in the context of learning. The first part of this paper present the concept of gamification. The second part is described the psychological perspectives of gamification, especially motivation and flow theory for gamifying design. The result from this study will be described into the guidelines for effective learning design using a gamification concept.

Keywords: gamification, e-learning, motivation, flow theory

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Authors: Sudha Arlikatti, Laura Siebeneck, Simon A. Andrew

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The objective of this research is to measure organizational resiliency through five attributes namely, rapidity, redundancy, resourcefulness, and robustness and to provide recommendations for resiliency building in flood risk communities. The research was conducted in Thailand following the severe floods of 2011 triggered by Tropical Storm Nock-ten. The floods lasted over eight months starting in June 2011 affecting 65 of the country’s 76 provinces and over 12 million people. Funding from a US National Science Foundation grant was used to collect ephemeral data in rural (Ayutthaya), suburban (Pathum Thani), and urban (Bangkok) provinces of Thailand. Semi-structured face-to-face interviews were conducted in Thai with 44 contacts from public, private, and non-profit organizations including universities, schools, automobile companies, vendors, tourist agencies, monks from temples, faith based organizations, and government agencies. Multiple triangulations were used to analyze the data by identifying selective themes from the qualitative data, validated with quantitative data and news media reports. This helped to obtain a more comprehensive view of how organizations in different geographic settings varied in their understanding of what enhanced or hindered their resilience and consequently their speed and capacities to respond. The findings suggest that the urban province of Bangkok scored highest in resourcefulness, rapidity of response, robustness, and ability to rebound. This is not surprising considering that it is the country’s capital and the seat of government, economic, military and tourism sectors. However, contrary to expectations all 44 respondents noted that the rural province of Ayutthaya was the fastest to recover amongst the three. Its organizations scored high on redundancy and rapidity of response due to the strength of social networks, a flood disaster sub-culture due to annual flooding, and the help provided by monks from and faith based organizations. Organizations in the suburban community of Pathum Thani scored lowest on rapidity of response and resourcefulness due to limited and ambiguous warnings, lack of prior flood experience and controversies that government flood protection works like sandbagging favored the capital city of Bangkok over them. Such a micro-level examination of organizational resilience in rural, suburban and urban areas in a country through mixed methods studies has its merits in getting a nuanced understanding of the importance of disaster subcultures and religious norms for resilience. This can help refocus attention on the strengths of social networks and social capital, for flood mitigation.

Keywords: disaster subculture, flood response, organizational resilience, Thailand floods, religious beliefs and response, social capital and disasters

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Authors: Mehdi Boukri, Mohammed Naboussi Farsi, Mounir Naili, Omar Amellal, Mohamed Belazougui, Ahmed Mebarki, Nabila Guessoum, Brahim Mezazigh, Mounir Ait-Belkacem, Nacim Yousfi, Mohamed Bouaoud, Ikram Boukal, Aboubakr Fettar, Asma Souki

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The seismic risk to which the urban centres are more and more exposed became a world concern. A co-operation on an international scale is necessary for an exchange of information and experiments for the prevention and the installation of action plans in the countries prone to this phenomenon. For that, the 1990s was designated as 'International Decade for Natural Disaster Reduction (IDNDR)' by the United Nations, whose interest was to promote the capacity to resist the various natural, industrial and environmental disasters. Within this framework, it was launched in 1996, the RADIUS project (Risk Assessment Tools for Diagnosis of Urban Areas Against Seismic Disaster), whose the main objective is to mitigate seismic risk in developing countries, through the development of a simple and fast methodological and operational approach, allowing to evaluate the vulnerability as well as the socio-economic losses, by probable earthquake scenarios in the exposed urban areas. In this paper, we will present the adaptation and application of this methodology to the Algerian context for the seismic risk evaluation in urban areas potentially exposed to earthquakes. This application consists to perform an earthquake scenario in the urban centre of Constantine city, located at the North-East of Algeria, which will allow the building seismic damage estimation of this city. For that, an inventory of 30706 building units was carried out by the National Earthquake Engineering Research Centre (CGS). These buildings were digitized in a data base which comprises their technical information by using a Geographical Information system (GIS), and then they were classified according to the RADIUS methodology. The study area was subdivided into 228 meshes of 500m on side and Ten (10) sectors of which each one contains a group of meshes. The results of this earthquake scenario highlights that the ratio of likely damage is about 23%. This severe damage results from the high concentration of old buildings and unfavourable soil conditions. This simulation of the probable seismic damage of the building and the GIS damage maps generated provide a predictive evaluation of the damage which can occur by a potential earthquake near to Constantine city. These theoretical forecasts are important for decision makers in order to take the adequate preventive measures and to develop suitable strategies, prevention and emergency management plans to reduce these losses. They can also help to take the adequate emergency measures in the most impacted areas in the early hours and days after an earthquake occurrence.

Keywords: seismic risk, mitigation, RADIUS, urban areas, Algeria, earthquake scenario, Constantine

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Authors: Debneil Saha Roy

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Weather forecasting is a complex topic and is well suited for analysis by deep learning approaches. With the wide availability of weather observation data nowadays, these approaches can be utilized to identify immediate comparisons between historical weather forecasts and current observations. This work explores the application of deep learning techniques to weather forecasting in order to accurately predict the weather over a given forecast hori­zon. Three deep neural networks are used in this study, namely, Multi-Layer Perceptron (MLP), Long Short Tunn Memory Network (LSTM) and a combination of Convolutional Neural Network (CNN) and LSTM. The predictive performance of these models is compared using two evaluation metrics. The results show that forecasting accuracy increases with an increase in the complexity of deep neural networks.

Keywords: convolutional neural network, deep learning, long short term memory, multi-layer perceptron

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Authors: Xing Feng, Yuanbin Li

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Oil spills at sea can cause severe marine environmental damage, including bringing huge hazards to living resources and human beings. In situ burning or chemical dispersant methods can be used to handle the oil spills sometimes, but these approaches will bring secondary pollution and fail in some situations. Oil recovery techniques have also been developed to recover oil using oil skimmer equipment installed on ships, while the hydrodynamic process of the oil flowing through the oil skimmer is very complicated and important for evaluating the recovery efficiency. Based on this, a two-dimensional numerical simulation platform for simulating the hydrodynamic process of the oil flowing through the oil skimmer is established based on the Navier-Stokes equations for viscous, incompressible fluid. Finally, the influence of the design of the flow channel in the curved plane oil skimmer on the hydrodynamic process of the oil flowing through the oil skimmer is investigated based on the established simulation platform.

Keywords: curved plane oil skimmer, flow channel, CFD, VOF

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Authors: Kalpana Adhikari, Mandip Subedi, Keshab Sharma, Indra P. Acharya

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The Gorkha Nepal earthquake of moment magnitude (Mw) 7.8 struck the central region of Nepal on April 25, 2015 with the epicenter about 77 km northwest of Kathmandu Valley . Peak ground acceleration observed during the earthquake was 0.18g. This motion induced several geotechnical effects such as landslides, foundation failures liquefaction, lateral spreading and settlement, and local amplification. An aftershock of moment magnitude (Mw) 7.3 hit northeast of Kathmandu on May 12 after 17 days of main shock caused additional damages. Kathmandu is the largest city in Nepal, have a population over four million. As the Kathmandu Valley deposits are composed mainly of sand, silt and clay layers with a shallow ground water table, liquefaction is highly anticipated. Extensive liquefaction was also observed in Kathmandu Valley during the 1934 Nepal-Bihar earthquake. Field investigations were carried out in Kathmandu Valley immediately after Mw 7.8, April 25 main shock and Mw 7.3, May 12 aftershock. Geotechnical investigation of both liquefied and non-liquefied sites were conducted after the earthquake. This paper presents observations of liquefaction and liquefaction induced damage, and the liquefaction potential assessment based on Standard Penetration Tests (SPT) for liquefied and non-liquefied sites. SPT based semi-empirical approach has been used for evaluating liquefaction potential of the soil and Liquefaction Potential Index (LPI) has been used to determine liquefaction probability. Recorded ground motions from the event are presented. Geological aspect of Kathmandu Valley and local site effect on the occurrence of liquefaction is described briefly. Observed liquefaction case studies are described briefly. Typically, these are sand boils formed by freshly ejected sand forced out of over-pressurized sub-strata. At most site, sand was ejected to agricultural fields forming deposits that varied from millimetres to a few centimeters thick. Liquefaction-induced damage to structures in these areas was not significant except buildings on some places tilted slightly. Boiled soils at liquefied sites were collected and the particle size distributions of ejected soils were analyzed. SPT blow counts and the soil profiles at ten liquefied and non-liquefied sites were obtained. The factors of safety against liquefaction with depth and liquefaction potential index of the ten sites were estimated and compared with observed liquefaction after 2015 Gorkha earthquake. The liquefaction potential indices obtained from the analysis were found to be consistent with the field observation. The field observations along with results from liquefaction assessment were compared with the existing liquefaction hazard map. It was found that the existing hazard maps are unrepresentative and underestimate the liquefaction susceptibility in Kathmandu Valley. The lessons learned from the liquefaction during this earthquake are also summarized in this paper. Some recommendations are also made to the seismic liquefaction mitigation in the Kathmandu Valley.

Keywords: factor of safety, geotechnical investigation, liquefaction, Nepal earthquake

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Authors: Abder-Rahman Ali, Adélaïde Albouy-Kissi, Manuel Grand-Brochier, Viviane Ladan-Marcus, Christine Hoeffl, Claude Marcus, Antoine Vacavant, Jean-Yves Boire

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In this paper, we present a new segmentation approach for focal liver lesions in contrast enhanced ultrasound imaging. This approach, based on a two-cluster Fuzzy C-Means methodology, considers type-II fuzzy sets to handle uncertainty due to the image modality (presence of speckle noise, low contrast, etc.), and to calculate the optimum inter-cluster threshold. Fine boundaries are detected by a local recursive merging of ambiguous pixels. The method has been tested on a representative database. Compared to both Otsu and type-I Fuzzy C-Means techniques, the proposed method significantly reduces the segmentation errors.

Keywords: defuzzification, fuzzy clustering, image segmentation, type-II fuzzy sets

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Authors: Ahmed A. Elshami, Stephanie Bonnet, Abdelhafid Khelidj

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Corrosion inhibitors are widely used in concrete industry to reduce the corrosion rate of steel rebar which is present in contact with aggressive environments. The present work aims to using Zamzam water from well located within the Masjid al-Haram in Mecca, Saudi Arabia 20 m (66 ft) east of the Kaaba, the holiest place in Islam as corrosion inhibitor for steel in rain water and simulated acid rain. The effect of Zamzam water was investigated by electrochemical impedance spectroscopy (EIS) and Potentiodynamic polarization techniques in Department of Civil Engineering - IUT Saint-Nazaire, Nantes University, France. Zamzam water is considered to be one of the most important steel corrosion inhibitor which is frequently used in different industrial applications. Results showed that zamzam water gave a very good inhibition for steel corrosion in rain water and simulated acid rain.

Keywords: Zamzam water, corrosion inhibitor, rain water, simulated acid rain

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Authors: Geoffrey Gilfillan, Peter Barham, Lisa Smallwood, David Harper

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The ‘Welland for People and Wildlife’ project aimed to improve the River Welland’s ecology and water quality, and to make it more accessible to the community of Market Harborough. A joint monitoring project by the Welland Rivers Trust & University of Leicester was incorporated into the design. The techniques that have been used to measure its success are hydrological, geomorphological, and water quality monitoring, species and habitat surveys, and community engagement. Early results show improvements to flow and habitat diversity, water quality and biodiversity of the river environment. Barrier removal has increased stickleback mating activity, and decreased parasitically infected fish in sample catches. The habitats provided by the berms now boast over 25 native plant species, and the river is clearer, cleaner and with better-oxygenated water.

Keywords: community engagement, ecological monitoring, river restoration, water quality

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Authors: Minoo Tavakoli, Alireza Kiani Rashid, Abbas Afrasiabi

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An aluminum coating deposited on mild steel substrate by electric arc spray and diffused to the base steel material by diffusion treatment at 800 and 900°C for 1 and 3 hours in a static air. Alloy layers formed by diffusion at both temperatures were investigated, and their features were compared with those of pack cementation aluminized steel. High-temperature oxidation tests were carried out in air at 600 °C for 145 hours. Results indicated that the aluminide coatings obtained from this process have significantly improved the high-temperature oxidation resistance in both methods due to the Al2O3 scale formation. Furthermore, it showed that the isothermal oxidation resistance of arc spray technique is better than pack cementation method. This can be attributed to voids that formed at the intermetallic layer /Al layer interface which is increased in the pack cementation method.

Keywords: electric arc spray, pack cementation, oxidation resistance, aluminized steel

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Authors: Rokhmatul Insani, Hira Laksmiwati Soemitro

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Business Intelligence is a methodology that exploits the data to produce information and knowledge systematically, business intelligence can support the decision-making process. Some methods in business intelligence are data warehouse and data mining. A data warehouse can store historical data from transactional data. For data modelling in data warehouse, we apply dimensional modelling by Kimball. While data mining is used to extracting patterns from the data and get insight from the data. Data mining has many techniques, one of which is segmentation. For profiling of telecommunication customer, we use customer segmentation according to customer’s usage of services, customer invoice and customer payment. Customers can be grouped according to their characteristics and can be identified the profitable customers. We apply K-Means Clustering Algorithm for segmentation. The input variable for that algorithm we use RFM (Recency, Frequency and Monetary) model. All process in data mining, we use tools IBM SPSS modeller.

Keywords: business intelligence, customer segmentation, data warehouse, data mining

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Authors: O. P. Yadav

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Nano-size Ag-N co-doped ZnO/CuO composite photo-catalyst has been synthesized by chemical method and characterized using XRD, TEM, FTIR, AAS and UV-Vis spectroscopic techniques. Photo-catalytic activity of as-synthesized nanomaterial has been studied using degradation of methyl orange as a probe under UV as well as visible radiations. Ag-N co-doped ZnO/CuO composite showed higher photo-catalytic activity than Ag- or N-doped ZnO and undoped ZnO-CuO composite photo-catalysts. The observed highest activity of Ag-N co-doped ZnO-CuO among the studied photo-catalysts is attributed to the cumulative effects of lowering of band-gap energy and decrease of recombination rate of photo-generated electrons and holes owing to doped N and Ag, respectively. Effects of photo-catalyst load, pH and substrate initial concentration on degradation of methyl orange have also been studied. Photo-catalytic degradation of methyl orange follows pseudo first order kinetics.

Keywords: degradation, nanocomposite, photocatalyst, spectroscopy, XRD

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Authors: Sujith Rajashekar Swamy, Meghana Rajashekara Swamy

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Although T1-weighted gadolinium-enhanced imaging (T1-Gd) has its established clinical role in diagnosing brain lesions of infectious and metastatic origins, the use of post-contrast susceptibility-weighted imaging (SWI) has been understudied. This observational study aims to explore and compare the prominence of brain parenchymal lesions between T1-Gd and SWI-Gd images. A cross-sectional study design was utilized to analyze 58 patients with brain parenchymal lesions using T1-Gd and SWI-Gd scanning techniques. Our results indicated that SWI-Gd enhanced the conspicuity of metastatic as well as infectious brain lesions when compared to T1-Gd. Consequently, it can be used as an adjunct to T1-Gd for post-contrast imaging, thereby avoiding additional contrast administration. Improved conspicuity of brain lesions translates directly to enhanced patient outcomes, and hence SWI-Gd imaging proves useful to meet that endpoint.

Keywords: susceptibility weighted, T1 weighted, brain lesions, gadolinium contrast

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Authors: Yiea Funk Te, Daniel Mueller, Irena Pletikosa Cvijikj

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Small and medium enterprises (SMEs) play an important role in the economy of many countries. When the overall world economy is considered, SMEs represent 95% of all businesses in the world, accounting for 66% of the total employment. Existing studies show that the current business environment is characterized as highly turbulent and strongly influenced by modern information and communication technologies, thus forcing SMEs to experience more severe challenges in maintaining their existence and expanding their business. To support SMEs at improving their competitiveness, researchers recently turned their focus on applying data mining techniques to build risk and growth prediction models. However, data used to assess risk and growth indicators is primarily obtained via questionnaires, which is very laborious and time-consuming, or is provided by financial institutes, thus highly sensitive to privacy issues. Recently, web mining (WM) has emerged as a new approach towards obtaining valuable insights in the business world. WM enables automatic and large scale collection and analysis of potentially valuable data from various online platforms, including companies’ websites. While WM methods have been frequently studied to anticipate growth of sales volume for e-commerce platforms, their application for assessment of SME risk and growth indicators is still scarce. Considering that a vast proportion of SMEs own a website, WM bears a great potential in revealing valuable information hidden in SME websites, which can further be used to understand SME risk and growth indicators, as well as to enhance current SME risk and growth prediction models. This study aims at developing an automated system to collect business-relevant data from the Web and predict future growth trends of SMEs by means of WM and data mining techniques. The envisioned system should serve as an 'early recognition system' for future growth opportunities. In an initial step, we examine how structured and semi-structured Web data in governmental or SME websites can be used to explain the success of SMEs. WM methods are applied to extract Web data in a form of additional input features for the growth prediction model. The data on SMEs provided by a large Swiss insurance company is used as ground truth data (i.e. growth-labeled data) to train the growth prediction model. Different machine learning classification algorithms such as the Support Vector Machine, Random Forest and Artificial Neural Network are applied and compared, with the goal to optimize the prediction performance. The results are compared to those from previous studies, in order to assess the contribution of growth indicators retrieved from the Web for increasing the predictive power of the model.

Keywords: data mining, SME growth, success factors, web mining

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Authors: Hanna Zietara

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Gastronomy is one of the oldest forms of commercial activity. It is currently one of the most popular and still dynamically developing branches of business. Socio-economic changes, its widespread occurrence, new techniques, or culinary styles affect the almost unlimited possibilities of its development. Importantly, regardless of the form of business adopted, food service is strongly related to logistics processes, and areas of food service that are closely linked to logistics are of strategic importance. Any inefficiency in logistics processes results in reduced chances for success and achieving competitive advantage by companies belonging to the catering industry. The aim of the paper is to identify the areas of logistic support occurring in the catering business, affecting the scope of the logistic processes implemented. The aim of the paper is realized through a plural homogeneous approach, based on: direct observation, text analysis of current documents, in-depth free targeted interviews.

Keywords: gastronomy, competitive advantage, logistics, logistics support

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Authors: Igor Bilenko, Artem Shitikov, Michael Gorodetsky

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Optical whispering gallery mode (WGM) resonators combine very high optical quality factor (Q) with small size. Resonators made from low loss crystalline fluorites (CaF2, MgF2) may have Q as high as 1010 that make them unique devices for modern applications including ultrasensitive sensors, frequency control, and precision spectroscopy. While silicon is a promising material transparent from near infrared to terahertz frequencies, fundamental limit for Si WGM quality factor was not reached yet. In our paper, we presented experimental results on the preparation and testing of resonators at 1550 nm wavelength made from crystalline silicon grown and treated by different techniques. Q as high as 3x107 was demonstrated. Future steps need to reach a higher value and possible applications are discussed.

Keywords: optical quality factor, silicon optical losses, silicon optical resonator, whispering gallery modes

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Authors: Zahid Ahmad, Nauman Ali

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This study has estimated the trade between USA and individual members of European Union using Gravity Model of Trade as The USA has a complex trade relationship with the European countries consist of a large number of consumers, which make USA dependent on EU for major of its total world trade. However, among the member of EU, the trade potential of USA with individual members of EU is not known. Panel data techniques e.g. Random Effect, Fixed Effect and Pooled Panel have been applied to secondary quantitative data to analyze the Trade between USA and EU. Trade Potential of USA with individual members of EU has been obtained using the ratio of Actual trade of USA with EU members and the trade as predicted by Gravity Model. The Study concluded that the USA has greater trade potential with 16 members of EU, including Croatia, Portugal and United Kingdom on top. On the other hand, Finland, Ireland, and France are the top countries with which the USA has exhaustive trade potential.

Keywords: analytical technique, economic, gravity, international trade, significant

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Authors: Seyed-Ali Sadegh-Zadeh, Kaveh Kavianpour, Hamed Atashbar, Elham Heidari, Saeed Shiry Ghidary, Amir M. Hajiyavand

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Evaluation metrics play a critical role in assessing the performance of machine learning models. In this review paper, we provide a comprehensive overview of performance measurement approaches for machine learning models. For each category, we discuss the most widely used metrics, including their mathematical formulations and interpretation. Additionally, we provide a comparative analysis of performance measurement approaches for metric combinations. Our review paper aims to provide researchers and practitioners with a better understanding of performance measurement approaches and to aid in the selection of appropriate evaluation metrics for their specific applications.

Keywords: evaluation metrics, performance measurement, supervised learning, unsupervised learning, reinforcement learning, model robustness and stability, comparative analysis

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Authors: Adeiza Matthew, Oluwadamilola Abubakar

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Wood energy, also known as wood fuel, is a renewable energy source that is derived from woody biomass, which is organic matter that is harvested from forests, woodlands, and other lands. Woody biomass includes trees, branches, twigs, and other woody debris that can be used as fuel. Wood energy can be classified based on its sources, such as trees outside forests, residues from wood harvesting and conversion, and energy plantations. There are several policy frameworks that support the use of wood energy, including participatory forest management and agroforestry. These policies aim to promote the sustainable use of woody biomass as a source of energy while also protecting forests and wildlife habitats. There are several options for using wood as a fuel, including central heating systems, pellet-based systems, wood chip-based systems, log boilers, fireplaces, and stoves. Each of these options has its own benefits and drawbacks, and the most appropriate option will depend on factors such as the availability of woody biomass, the heating needs of the household or facility, and the local climate. In order to use wood as a fuel, it must be harvested and stored properly. Hardwood or softwood can be used as fuel, and the heating value of firewood depends on the species of tree and the degree of moisture content. Proper harvesting and storage of wood can help to minimize environmental impacts and improve wildlife habitats. The use of wood energy has several environmental impacts, including the release of greenhouse gases during combustion and the potential for air pollution from combustion by-products. However, wood energy can also have positive environmental impacts, such as the sequestration of carbon in trees and the reduction of reliance on fossil fuels. The regulation and legislation of wood energy vary by country and region, and there is an ongoing debate about the potential use of wood energy in renewable energy technologies. Wood energy is a renewable energy source that can be used to generate electricity, heat, and transportation fuels. Woody biomass is abundant and widely available, making it a potentially significant source of energy for many countries. The use of wood energy can create local economic and employment opportunities, particularly in rural areas. Wood energy can be used to reduce reliance on fossil fuels and reduce greenhouse gas emissions. Properly managed forests can provide a sustained supply of woody biomass for energy, helping to reduce the risk of deforestation and habitat loss. Wood energy can be produced using a variety of technologies, including direct combustion, co-firing with fossil fuels, and the production of biofuels. The environmental impacts of wood energy can be minimized through the use of best practices in harvesting, transportation, and processing. Wood energy is regulated and legislated at the national and international levels, and there are various standards and certification systems in place to promote sustainable practices. Wood energy has the potential to play a significant role in the transition to a low-carbon economy and the achievement of climate change mitigation goals.

Keywords: biomass, timber, charcoal, firewood

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Authors: Maciej Szeląg, Stanisław Fic

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The impact of elevated temperatures on the construction materials manifests in change of their physical and mechanical characteristics. Stresses and thermal deformations that occur inside the volume of the material cause its progressive degradation as temperature increase. Finally, the reactions and transformations of multiphase structure of cementitious composite cause its complete destruction. A particularly dangerous phenomenon is the impact of thermal shock – a sudden high temperature load. The thermal shock leads to a high value of the temperature gradient between the outer surface and the interior of the element in a relatively short time. The result of mentioned above process is the formation of the cracks and scratches on the material’s surface and inside the material. The article describes the use of computer image analysis techniques to identify and assess the structure of the cluster cracks on the surfaces of modified cement pastes, caused by thermal shock. Four series of specimens were tested. Two Portland cements were used (CEM I 42.5R and CEM I 52,5R). In addition, two of the series contained metakaolinite as a replacement for 10% of the cement content. Samples in each series were made in combination of three w/b (water/binder) indicators of respectively 0.4; 0.5; 0.6. Surface cracks of the samples were created by a sudden temperature load at 200°C for 4 hours. Images of the cracked surfaces were obtained via scanning at 1200 DPI; digital processing and measurements were performed using ImageJ v. 1.46r software. In order to examine the cracked surface of the cement paste as a system of closed clusters – the dispersal systems theory was used to describe the structure of cement paste. Water is used as the dispersing phase, and the binder is used as the dispersed phase – which is the initial stage of cement paste structure creation. A cluster itself is considered to be the area on the specimen surface that is limited by cracks (created by sudden temperature loading) or by the edge of the sample. To describe the structure of cracks two stereological parameters were proposed: A ̅ – the cluster average area, L ̅ – the cluster average perimeter. The goal of this study was to compare the investigated stereological parameters with the mechanical properties of the tested specimens. Compressive and tensile strength testes were carried out according to EN standards. The method used in the study allowed the quantitative determination of defects occurring in the examined modified cement pastes surfaces. Based on the results, it was found that the nature of the cracks depends mainly on the physical parameters of the cement and the intermolecular interactions on the dispersal environment. Additionally, it was noted that the A ̅/L ̅ relation of created clusters can be described as one function for all tested samples. This fact testifies about the constant geometry of the thermal cracks regardless of the presence of metakaolinite, the type of cement and the w/b ratio.

Keywords: cement paste, cluster cracks, elevated temperature, image analysis, metakaolinite, stereological parameters

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Authors: Martina Manenova, Lukas Cirus

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This article introduces research focused on elementary school teachers’ approach to innovations in ICT. The diffusion of innovations theory, which was written by E. M. Rogers, captures the processes of innovation adoption. The research method derived from this theory and the Rogers’ questionnaire focused on the diffusion of innovations was used as the basic research method. The research sample consisted of elementary school teachers. The comparison of results with the Rogers’ results shows that among the teachers in the research sample the so-called early majority, as well as the overall division of the data, was rather central (early adopter, early majority, and later majority). The teachers very rarely appeared on the edge positions (innovator, laggard). The obtained results can be applied to teaching practice and used especially in the implementation of new technologies and techniques into the educational process.

Keywords: innovation, diffusion of innovation, information and communication technology, teachers

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Authors: Gui Yewei, Du Yanxia, Xiao Guangming, Liu Lei, Wei Dong, Yang Xiaofeng

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A phase change material (PCM) is a substance which absorbs a large amount of energy when undergoing a change of solid-liquid phase. The good physical and chemical properties of C or SiC foam reveal the possibility of using them as a thermal conductivity enhancer for the PCM. C or SiC foam composite PCM has a high effective conductivity and becomes one of the most interesting thermal storage techniques due to its advantage of simplicity and reliability. The paper developed a numerical method to simulate the heat transfer of SiC and C foam composite PCM, a finite volume technique was used to discretize the heat diffusion equation while the phase change process was modeled using the equivalent specific heat method. The effects of the porosity were investigated based on the numerical method, and the effects of the geometric model of the microstructure on the equivalent thermal conductivity was studies.

Keywords: SiC foam, composite, phase change material, heat transfer

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Authors: Magdi Mohamed Eltayeb Zumrawi

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It is quite essential to investigate the causes of pavement deterioration in order to select the proper maintenance technique. The objective of this study was to identify factors cause deterioration of recently constructed roads in Khartoum state. A comprehensive literature concerning the factors of road deterioration, common road defects and their causes were reviewed. Three major road projects with different deterioration reasons were selected for this study. The investigation involved field survey and laboratory testing on those projects to examine the existing pavement conditions. The results revealed that the roads investigated experienced severe failures in the forms of cracks, potholes and rutting in the wheel path. The causes of those failures were found mainly linked to poor drainage, traffic overloading, expansive subgrade soils and the use of low quality materials in construction. Based on the results, recommendations were provided to help highway engineers in selecting the most effective repair techniques for specific kinds of distresses.

Keywords: pavement, deterioration, causes, failures

Procedia PDF Downloads 357

Authors: M. Taha, Hala H. Zayed, T. Nazmy, M. Khalifa

Abstract:

Recently, traffic monitoring has attracted the attention of computer vision researchers. Many algorithms have been developed to detect and track moving vehicles. In fact, vehicle tracking in daytime and in nighttime cannot be approached with the same techniques, due to the extreme different illumination conditions. Consequently, traffic-monitoring systems are in need of having a component to differentiate between daytime and nighttime scenes. In this paper, a HSV-based day/night detector is proposed for traffic monitoring scenes. The detector employs the hue-histogram and the value-histogram on the top half of the image frame. Experimental results show that the extraction of the brightness features along with the color features within the top region of the image is effective for classifying traffic scenes. In addition, the detector achieves high precision and recall rates along with it is feasible for real time applications.

Keywords: day/night detector, daytime/nighttime classification, image classification, vehicle tracking, traffic monitoring

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Authors: Fida Isam Abdulhafiz

Abstract:

Traditional vernacular architecture in the United Arab Emirates constituted namely of adobe houses with a limited number of openings in their facades. The thick mud and rubble walls and wooden window screens protected its inhabitants from the harsh desert climate and provided them with privacy and fulfilled their comfort zone needs to an extent. However, with the rise of the immediate post petroleum era reinforced concrete villas with glass and steel technology has replaced traditional vernacular dwellings. And more load was put on the mechanical cooling systems to ensure the satisfaction of today’s more demanding doweling inhabitants. However, In the early 21at century professionals started to pay more attention to the carbon footprint caused by the built constructions. In addition, many studies and innovative approaches are now dedicated to lower the impact of the existing operating buildings on their surrounding environments. The UAE government agencies started to regulate that aim to revive sustainable and environmental design through Local and international building codes and urban design policies such as Estidama and LEED. The focus in this paper is on the reduction of the emissions resulting from the use of energy sources in the cooling and heating systems, and that would be through using innovative screen designs and façade solutions to provide a green footprint and aesthetic architectural icons. Screens are one of the popular innovative techniques that can be added in the design process or used in existing building as a renovation techniques to develop a passive green buildings. Preparing future architects to understand the importance of environmental design was attempted through physical modelling of window screens as an educational means to combine theory with a hands on teaching approach. Designing screens proved to be a popular technique that helped them understand the importance of sustainable design and passive cooling. After creating models of prototype screens, several tests were conducted to calculate the amount of Sun, light and wind that goes through the screens affecting the heat load and light entering the building. Theory further explored concepts of green buildings and material that produce low carbon emissions. This paper highlights the importance of hands on experience for student architects and how physical modelling helped rise eco awareness in Design studio. The paper will study different types of façade screens and shading devices developed by Architecture students and explains the production of diverse patterns for traditional screens by student architects based on sustainable design concept that works properly with the climate requirements in the Middle East region.

Keywords: building’s screens modeling, façade design, sustainable architecture, sustainable dwellings, sustainable education

Procedia PDF Downloads 304

Authors: Diego Santibañez Oyarce, Fernanda Bravo Cornejo, Camilo Cerda Sarabia, Belén Díaz Díaz, Esteban Gómez Terán, Hugo Osses Prado, Raúl Caulier-Cisterna, Jorge Vergara-Quezada, Ana Moya-Beltrán

Abstract:

The advent of high-throughput sequencing technologies has revolutionized genomics, generating vast amounts of genetic data that challenge traditional bioinformatics methods. Machine learning addresses these challenges by leveraging computational power to identify patterns and extract information from large datasets. However, biological sequence data, being symbolic and non-numeric, must be converted into numerical formats for machine learning algorithms to process effectively. So far, some encoding methods, such as one-hot encoding or k-mers, have been explored. This work proposes additional approaches for encoding DNA sequences in order to compare them with existing techniques and determine if they can provide improvements or if current methods offer superior results. Data from the 16S rRNA gene, a universal marker, was used to analyze eight bacterial groups that are significant in the pulmonary environment and have clinical implications. The bacterial genes included in this analysis are Prevotella, Abiotrophia, Acidovorax, Streptococcus, Neisseria, Veillonella, Mycobacterium, and Megasphaera. These data were downloaded from the NCBI database in Genbank file format, followed by a syntactic analysis to selectively extract relevant information from each file. For data encoding, a sequence normalization process was carried out as the first step. From approximately 22,000 initial data points, a subset was generated for testing purposes. Specifically, 55 sequences from each bacterial group met the length criteria, resulting in an initial sample of approximately 440 sequences. The sequences were encoded using different methods, including one-hot encoding, k-mers, Fourier transform, and Wavelet transform. Various machine learning algorithms, such as support vector machines, random forests, and neural networks, were trained to evaluate these encoding methods. The performance of these models was assessed using multiple metrics, including the confusion matrix, ROC curve, and F1 Score, providing a comprehensive evaluation of their classification capabilities. The results show that accuracies between encoding methods vary by up to approximately 15%, with the Fourier transform obtaining the best results for the evaluated machine learning algorithms. These findings, supported by the detailed analysis using the confusion matrix, ROC curve, and F1 Score, provide valuable insights into the effectiveness of different encoding methods and machine learning algorithms for genomic data analysis, potentially improving the accuracy and efficiency of bacterial classification and related genomic studies.

Keywords: DNA encoding, machine learning, Fourier transform, Fourier transformation

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Authors: Mohammed Al Awadh

Abstract:

In order for businesses to take advantage of the opportunities for expanded production and trade that have arisen as a result of globalization and increased levels of competition, productivity growth is required. The number of available sources is decreasing with each passing day, which results in an ever-increasing demand. In response to this, there will be an increased demand placed on firms to improve the efficiency with which they utilise their resources. As a scientific method, work and time research techniques have been employed in all manufacturing and service industries to raise the efficiency of use of the factors of production. These approaches focus on work and time. The goal of this research is to improve the productivity of a manufacturing industry's production system by looking at ways to measure work. The work cycles were broken down into more manageable and quantifiable components. On the observation sheet, these aspects were noted down. The operation has been properly analysed in order to identify value-added and non-value-added components, and observations have been recorded for each of the different trails.

Keywords: time study, work measurement, work study, efficiency

Procedia PDF Downloads 74