Search results for: smart beta

Authors: Joy Ghosh, Debasmita Biswas

Abstract:

The road network of any area is the most important indicator of regional planning. For proper utilization of urban road networks, the structural parameters such as connectivity and accessibility should be analyzed and evaluated. This paper aims to explain the application of GIS on urban road network connectivity and accessibility analysis with a case study of Chandannagar City. This paper has been made to analyze the road network connectivity through various connectivity measurements like the total number of nodes and links, Cyclomatic Number, Alpha Index, Beta Index, Gamma index, Eta index, Pi index, Theta Index, and Aggregated Transport Score, Road Density based on existing road network in Chandannagar city in India. Accessibility is measured through the shortest Path Matrix, associate Number, and Shimbel Index. Various urban services, such as schools, banks, Hospitals, petrol pumps, ATMs, police stations, theatres, parks, etc., are considered for the accessibility analysis for each ward. This paper also highlights the relationship between urban land use/ land cover (LULC) and urban road network and population density using various spatial and statistical measurements. The datasets were collected through a field survey of 33 wards of the Chandannagar Municipal Corporation area, and the secondary data were collected through an open street map and satellite image of LANDSAT8 OLI & TIRS from USGS. Chandannagar was actually once a French colony, and at that time, various sort of planning was applied, but now Chandannagar city continues to grow haphazardly because that city is facing some problems; the knowledge gained from this paper helps to create a more efficient and accessible road network. Therefore, it would be suggested that some wards need to improve their connectivity and accessibility for the future growth and development of Chandannagar.

Keywords: accessibility, connectivity, transport, road network

Procedia PDF Downloads 67

Authors: Joanna Dauner, Jan Friedrich, Linda Elsner, Kora Kimpel

Abstract:

Active materials such as Electroactive Polymers (EAPs) are promising for the development of novel shape-changing interfaces. This paper explores the potential of EAPs in a multilayer unimorph structure from a design perspective to investigate the visual qualities of the material for dynamic data visualization and data physicalization. We discuss various concepts of how the material can be used for this purpose. Multilayer unimorph EAPs are of particular interest to designers because they can be easily prototyped using everyday materials and tools. By changing the structure and geometry of the EAPs, their movement and behavior can be modified. We present the results of our preliminary user testing, where we evaluated different movement patterns. As a result, we introduce a prototype display built with EAPs for dynamic data physicalization. Finally, we discuss the potentials and drawbacks and identify further open research questions for the design discipline.

Keywords: electroactive polymer, shape-changing interfaces, smart material interfaces, data physicalization

Procedia PDF Downloads 95

Authors: Saurabh Shukla, G. N. Pandey

Abstract:

The fires have become the most serious disasters to forest resources and the human environment. In recent years, due to climate change, human activities and other factors the frequency of forest fires has increased considerably. The monitoring and prevention of forest fires have now become a global concern for forest fire prevention organizations. Currently, the methods for forest fire prevention largely consist of patrols, observation from watch towers. Thus, software like deployment of the wireless sensor network to prevent forest fire is being developed to get a better estimate of the temperature and humidity prospects. Now days, wireless sensor networks are beginning to be deployed at an accelerated pace. It is not unrealistic to expect that in coming years the world will be covered with wireless sensor networks. This new technology has lots of unlimited potentials and can be used for numerous application areas including environmental, medical, military, transportation, entertainment, crisis management, homeland defense, and smart spaces.

Keywords: deployment, sensors, wireless sensor networks, forest fires

Procedia PDF Downloads 432

Authors: Julia Terlet, Thomas H. Beach, Yacine Rezgui

Abstract:

Urbanization, population growth, climate change and the current increase in water demand have made the adoption of innovative demand management strategies crucial to the water industry. Water conservation in urban areas has to be improved by encouraging consumers to adopt more sustainable habits and behaviours. This includes informing and educating them about their households’ water consumption and advising them about ways to achieve significant savings on a daily basis. This paper presents a study conducted in the context of the European FP7 WISDOM Project. By integrating innovative Information and Communication Technologies (ICT) frameworks, this project aims at achieving a change in water savings. More specifically, behavioural change will be attempted by implementing smart meters and in-home displays in a trial group of selected households within Cardiff (UK). Using this device, consumers will be able to receive feedback and information about their consumption but will also have the opportunity to compare their consumption to the consumption of other consumers and similar households. Following an initial survey, it appeared necessary to implement these in-home displays in a way that matches consumer's motivations to save water. The results demonstrated the importance of various factors influencing people’s daily water consumption. Both the relevant literature on the subject and the results of our survey therefore led us to include within the in-home device a variety of elements. It first appeared crucial to make consumers aware of the economic aspect of water conservation and especially of the significant financial savings that can be achieved by reducing their household’s water consumption on the long term. Likewise, reminding participants of the impact of their consumption on the environment by making them more aware of water scarcity issues around the world will help increasing their motivation to save water. Additionally, peer pressure and social comparisons with neighbours and other consumers, accentuated by the use of online social networks such as Facebook or Twitter, will likely encourage consumers to reduce their consumption. Participants will also be able to compare their current consumption to their past consumption and to observe the consequences of their efforts to save water through diverse graphs and charts. Finally, including a virtual water game within the display will help the whole household, children and adults, to achieve significant reductions by providing them with simple tips and advice to save water on a daily basis. Moreover, by setting daily and weekly goals for them to reach, the game will expectantly generate cooperation between family members. Members of each household will indeed be encouraged to work together to reduce their water consumption within different rooms of the house, such as the bathroom, the kitchen, or the toilets. Overall, this study will allow us to understand the elements that attract consumers the most and the features that are most commonly used by the participants. In this way, we intend to determine the main factors influencing water consumption in order to identify the measures that will most encourage water conservation in both the long and short term.

Keywords: behavioural change, ICT technologies, water consumption, water conservation

Procedia PDF Downloads 333

Authors: Hailyie Tekleselase

Abstract:

Deep learning is increasingly used as a building block of security systems. However, neural networks are hard to interpret and typically solid to the practitioner. This paper presents a detail survey of computing methods in cyber security, and analyzes the prospects of enhancing the cyber security capabilities by suggests that of accelerating the intelligence of the security systems. There are many AI-based applications used in industrial scenarios such as Internet of Things (IoT), smart grids, and edge computing. Machine learning technologies require a training process which introduces the protection problems in the training data and algorithms. We present machine learning techniques currently applied to the detection of intrusion, malware, and spam. Our conclusions are based on an extensive review of the literature as well as on experiments performed on real enterprise systems and network traffic. We conclude that problems can be solved successfully only when methods of artificial intelligence are being used besides human experts or operators.

Keywords: artificial intelligence, machine learning, deep learning, cyber security, big data

Procedia PDF Downloads 122

Authors: Amirmozafar Benshams, Khatere Kashmari, Farzad Hatami, Mesbah Saybani

Abstract:

Shape memory alloys with high capability of energy dissipation and large deformation bearing with return ability to their original shape without too much hysteresis strain have opened their place among the other damping systems as smart materials. Ninitol which is the most well-known and most used alloy material from the shape memory alloys family, has high resistance and fatigue and is coverage for large deformations. Shape memory effect and super-elasticity by shape alloys like Nitinol, are the reasons of the high power of these materials in energy depreciation. Thus, these materials are suitable for use in reciprocating dynamic loading conditions. The experiments results showed that Nitinol wires with small diameter have greater energy dissipation capability and by increase of diameter and thickness the damping capability and energy dissipation increase.

Keywords: shape memory alloys, shape memory effect, super elastic effect, nitinol, energy dissipation

Procedia PDF Downloads 507

Authors: Syed Mahbubuz Zaman, A. B. M. Abrar Haque, Mehedi Hassan Nayeem, Misbah Uddin Sagor

Abstract:

Everyday e-mails are being used by millions of people as an effective form of communication over the Internet. Although e-mails allow high-speed communication, there is a constant threat known as spam. Spam e-mail is often called junk e-mails which are unsolicited and sent in bulk. These unsolicited emails cause security concerns among internet users because they are being exposed to inappropriate content. There is no guaranteed way to stop spammers who use static filters as they are bypassed very easily. In this paper, a smart system is proposed that will be using neural networks to approach spam in a different way, and meanwhile, this will also detect the most relevant features that will help to design the spam filter. Also, a comparison of different parameters for different neural network models has been shown to determine which model works best within suitable parameters.

Keywords: long short-term memory, bidirectional long short-term memory, gated recurrent unit, natural language processing, natural language processing

Procedia PDF Downloads 201

Authors: Kuei-Chun Liu, Yu-Yu Lai, Ching-Hong Wu, Hsiao-Han Huang

Abstract:

The number of Android applications (Apps) has increased rapidly in recent years. In order to get better programmatic control over Apps, we designed a record-and-replay mechanism to record Android input events and accessibility service events then make shortcuts. The shortcut is useful for complicated routine works and to Android beginners. We also generated graphical user interface (GUI) API by these shortcuts. GUI API helps developers make integrated Apps which can control other third-party Apps even if the official API is not offered by their providers. We demonstrated the usage of GUI API with two integrated Apps: Universal Bank App and Universal Communication App. Universal Bank App integrates three accounts from different banks and Universal Communication App integrates Line with WhatsApp. Both of them show the advantage of extendable GUI API. Furthermore, using our mechanism, shortcuts could replay almost all of the Top-100 Apps on Google Play correctly. In sum, the approach we present can help both Android developers and general users.

Keywords: graphical user interface, GUI API, record-and-replay, third-party apps

Procedia PDF Downloads 405

Authors: B. Sadepovich Maikanov, Z. Shabanbayevich Adilbekov, R. Husainovna Mustafina, L. Tyulegenovna Auteleyeva

Abstract:

This study involves detailed information about contaminants of honey in the Republic of Kazakhstan. The requirements of the technical regulation ‘Requirements to safety of honey and bee products’ and GOST 19792-2001 were taken into account in this research. Contamination of honey by antibiotics wqs determined by the IEA (immune-enzyme analysis), Ridder analyzer and Tecna produced test systems. Voltammetry (TaLab device) was used to define contamination by salts of heavy metals and gamma-beta spectrometry, ‘Progress BG’ system, with preliminary ashing of the sample of honey was used to define radioactive contamination. This article pointed out that residues of chloramphenicol were detected in 24% of investigated products, in 22% of them –streptomycin, in 7.3% - sulfanilamide, in 2.4% - tylosin, and in 12% - combined contamination was noted. Geographically, the greatest degree of contamination of honey with antibiotics occurs in the Northern Kazakhstan – 54.4%, and Southern Kazakhstan - 50%, and the lowest in Central and Eastern Kazakhstan with 30% and 25%, respectively. Generally, pollution by heavy metals is within acceptable limits, but the contamination from lead is highest in the Akmola region. The level of radioactive cesium and strontium is also within acceptable concentrations. The highest radioactivity in terms of cesium was observed in the East Kazakhstan region - 49.00±10 Bq/kg, in Akmola, North Kazakhstan and Almaty - 12.00±5, 11.05±3 and 19.0±8 Bq/kg, respectively, while the norm is 100 Bq/kg. In terms of strontium, the radioactivity in the East Kazakhstan region is 25.03±15 Bq/kg, while in Akmola, North Kazakhstan and Almaty regions it is 12.00±3, 10.2±4 and 1.0±2 Bq/kg, respectively, with the norm of 80 Bq/kg. This accumulation is mainly associated with the environmental degradation, feeding and treating of bees. Moreover, in the process of collecting nectar, external substances can penetrate honey. Overall, this research determines factors and reasons of honey contamination.

Keywords: antibiotics, contamination of honey, honey, radionuclides

Procedia PDF Downloads 222

Authors: Chinlun Lai, Lunjyh Jiang

Abstract:

Due to the heavy burden and pressure of caring for infants, an integrated automatic baby watching system based on IoT smart sensing and deep learning machine vision techniques is proposed in this paper. By monitoring infant body conditions such as heartbeat, breathing, body temperature, sleeping posture, as well as the surrounding conditions such as dangerous/sharp objects, light, noise, humidity and temperature, the proposed system can analyze and predict the obvious/potential dangerous conditions according to observed data and then adopt suitable actions in real time to protect the infant from harm. Thus, reducing the burden of the caregiver and improving safety efficiency of the caring work. The experimental results show that the proposed system works successfully for the infant care work and thus can be implemented in various life fields practically.

Keywords: baby care system, Internet of Things, deep learning, machine vision

Procedia PDF Downloads 223

Authors: G. Santamato, M. Solazzi, A. Frisoli

Abstract:

Systems for detection of damages in railway pantographs effectively reduce the cost of maintenance and improve time scheduling. In this paper, we present an approach to design a monitoring tool fitting strong customer requirements such as portability and ease of use. Pantograph has been modeled to estimate its dynamical properties, since no data are available. With the aim to focus on suspensions health, a two Degrees of Freedom (DOF) scheme has been adopted. Parameters have been calculated by means of analytical dynamics. A Finite Element Method (FEM) modal analysis verified the former model with an acceptable error. The detection strategy seeks phase-plots topology alteration, induced by defects. In order to test the suitability of the method, leakage in the dashpot was simulated on the lumped model. Results are interesting because changes in phase plots are more appreciable than frequency-shift. Further calculations as well as experimental tests will support future developments of this smart strategy.

Keywords: pantograph models, phase plots, structural health monitoring, damage detection

Procedia PDF Downloads 360

Authors: Hosuk Shin, Young-Hyun Seo, Eunhak Lee, Seung-Young Kho

Abstract:

Currently, in Seoul, users have the privilege to avoid riding crowded buses with the installation of Bus Information System (BIS). BIS has three levels of on-board bus ridership level information (spacious, normal, and crowded). However, there are flaws in the system due to it being real time which could provide incomplete information to the user. For example, a bus comes to the station, and on the BIS it shows that the bus is crowded, but on the stop that the user is waiting many people get off, which would mean that this station the information should show as normal or spacious. To fix this problem, this study predicts the bus ridership level using smart card data to provide more accurate information about the passenger ridership level on the bus. An Artificial Neural Network (ANN) is an interconnected group of nodes, that was created based on the human brain. Forecasting has been one of the major applications of ANN due to the data-driven self-adaptive methods of the algorithm itself. According to the results, the ANN algorithm was stable and robust with somewhat small error ratio, so the results were rational and reasonable.

Keywords: smartcard data, ANN, bus, ridership

Procedia PDF Downloads 162

Authors: Donghee Noh, Seonhyeong Kim, Junhwan Choi, Heegon Kim, Sooho Jung, Keunho Park

Abstract:

In this paper, we describe an image post-processing method to enhance the performance of the parcel segmentation method using deep learning-based aerial images conducted in previous studies. The study results were evaluated using a confusion matrix, IoU, Precision, Recall, and F1-Score. In the case of the confusion matrix, it was observed that the false positive value, which is the result of misclassification, was greatly reduced as a result of image post-processing. The average IoU was 0.9688 in the image post-processing, which is higher than the deep learning result of 0.8362, and the F1-Score was also 0.9822 in the image post-processing, which was higher than the deep learning result of 0.8850. As a result of the experiment, it was found that the proposed technique positively complements the deep learning results in segmenting the parcel of interest.

Keywords: aerial image, image process, machine vision, open field smart farm, segmentation

Procedia PDF Downloads 77

Authors: Arezou Javadi

Abstract:

The use of algorithmic models dependent on software calculations and simulation of new government management assays with the help of specialized software had increased the productivity and efficiency of the government management system recently. This has caused the management approach to change from the old bitch & fix model, which has low efficiency and less usefulness, to the capable management model with higher efficiency called the partnership with resident model. By using Govpilot TM software, the relationship between people in a system and the government was examined. The method of two tailed interaction was the outsourcing of a goal in a system, which is formed in the order of goals, qualified executive people, optimal executive model, and finally, summarizing additional activities at the different statistical levels. The results showed that the participation of people in a financial implementation system with a statistical potential of P≥5% caused a significant increase in investment and initial capital in the government system with maximum implement project in a smart government.

Keywords: machine learning, financial income, statistical potential, govpilot

Procedia PDF Downloads 85

Authors: Arezou Javadi

Abstract:

The use of algorithmic models dependent on software calculations and simulation of new government management assays with the help of specialized software had increased the productivity and efficiency of the government management system recently. This has caused the management approach to change from the old bitch & fix model, which has low efficiency and less usefulness, to the capable management model with higher efficiency called the partnership with resident model. By using Govpilot TM software, the relationship between people in a system and the government was examined. The method of two tailed interaction was the outsourcing of a goal in a system, which is formed in the order of goals, qualified executive people, optimal executive model, and finally, summarizing additional activities at the different statistical levels. The results showed that the participation of people in a financial implementation system with a statistical potential of P≥5% caused a significant increase in investment and initial capital in the government system with maximum implement project in a smart government.

Keywords: machine learning, financial income, statistical potential, govpilot

Procedia PDF Downloads 67

Authors: Vahab Behmanesh

Abstract:

Metabolic syndrome is defined as having at least three of the five metabolic risk factors, including abdominal obesity, high blood pressure, high triglycerides, low HDL, and insulin resistance. Lifestyle changes towards reducing physical activity, unhealthy eating habits Especially the high-fat and high-carbohydrate diet is directly related to metabolic syndrome, and due to the epidemic of overweight and sedentary life, metabolic syndrome is a serious problem worldwide. On the other hand, vitamin D deficiency is considered as one of the most common problems in the world, which is related to the dysfunction of beta cells and insulin resistance, and therefore, vitamin D deficiency is considered as a factor in the occurrence of metabolic syndrome. 40 subjects (age: 16.12 ± 4.4 years and body mass index 25.61 ± 4.4 kg/m2) were randomly assigned to groups of aerobic exercise and placebo, aerobic exercise and vitamin D and placebo (no exercise) were divided. Vitamin D was taken at a dose of 50,000 units per week in a double-blind format for eight weeks, and the daily aerobic exercise program was performed for 50 to 60 minutes, three doses per week, with an intensity of 50-60% of the maximum heart rate. From one-way analysis of variance, Factorial variance analysis (2x2) repeated measurement and correlated t-test were used for data analysis. Aerobic exercise and vitamin D intake reduced all metabolic risk indicators and blood insulin (P < 0.05). However, the subjective feeling of hunger did not change significantly (P < 0.05). Regarding waist circumference and blood glucose, the effect of exercise combined with vitamin D consumption was greater than the corresponding effect in the vitamin D group (P < 0.05). Aerobic exercises and vitamin D intake are safe and effective for improving cardiometabolic health, Imam adds vitamin D to the exercise program has more benefits for weight and blood sugar control, which suggests prescribing it for patients with metabolic syndrome.

Keywords: vitamin D, aerobic exercise, metabolic control, adolescents

Procedia PDF Downloads 99

Authors: C. Trapp, A. Vijay, M. Khorasani

Abstract:

Decentralised micro-grids with sector coupling can combat the spatial and temporal intermittence of renewable energy by combining power, transportation and infrastructure sectors. Intelligent energy conversion concepts such as electrolysers, hydrogen engines and fuel cells combined with energy storage using intelligent batteries and hydrogen storage form the back-bone of such a system. This paper describes a micro-grid based on Photo-Voltaic cells, battery storage, innovative modular and scalable Anion Exchange Membrane (AEM) electrolyzer with an efficiency of up to 73%, high-pressure hydrogen storage as well as cutting-edge combustion-engine based Combined Heat and Power (CHP) plant with more than 85% efficiency at the university campus to address the challenges of decarbonization whilst eliminating the necessity for expensive high-voltage infrastructure.

Keywords: sector coupling, micro-grids, energy self-sufficiency, decarbonization, AEM electrolysis, hydrogen CHP

Procedia PDF Downloads 179

Authors: Ashish Kumar, Kaptan Singh, Amit Saxena

Abstract:

Today, it is believed that crimes have the greatest impact on a person's ability to progress financially and personally. Identifying places where individuals shouldn't go is crucial for preventing crimes and is one of the key considerations. As society and technologies have advanced significantly, so have crimes and the harm they wreak. When there is a concentration of people in one place and changes happen quickly, it is even harder to prevent. Because of this, many crime prevention strategies have been embraced as a component of the development of smart cities in numerous cities. However, crimes can occur anywhere; all that is required is to identify the pattern of their occurrences, which will help to lower the crime rate. In this paper, an analysis related to crime has been done; information related to crimes is collected from all over India that can be accessed from anywhere. The purpose of this paper is to investigate the relationship between several factors and India's crime rate. The review has covered information related to every state of India and their associated regions of the period going in between 2001- 2014. However various classes of violations have a marginally unique scope over the years.

Keywords: K-nearest neighbor, random forest, decision tree, pre-processing

Procedia PDF Downloads 85

Authors: Sahar Iqrar, Malik Adeel Anwar, Zain Akram, Maria Noor

Abstract:

Introduction: Oral lichen planus is a chronic inflammatory condition of unknown etiology. Oral lichen planus may be related with several other diseases. Grinspan's Syndrome is characterized by a triad of oral lichen planus, hypertension, and diabetes mellitus. Other associations reported in the literature are with chronic liver disease and, with dyslipidemia. The nature of these associations is still not fully understood. Material and methods: Study was conducted in Department of Oral Medicine, Fatima Memorial Hospital College of Medicine and Dentistry, Lahore, Pakistan. A total of n=89 clinically diagnosed patients of oral lichen planus of both gender and all age groups were recruited and detailed history were recorded in the designed performs. Results: A total of n=89 patients were taken with male to female ratio of 3:8 in which 24 were male and 65 females. Mean age was 48.8 ± 13.8 years. Age range of 10-74 years was seen. Among these patients suffering from oral lichen planus, 41.6% (n=37) had a positive history for hypertension with 59.5% (n=22) of these patients were taking different medication for their condition. Whereas Diabetes Mellitus was found in 24.7% (n=22) patients with 72.7% (n=16) of these patients using the hypoglycemic drug (oral or injectable) to control their blood glucose levels. Out of these n=89 lichen planus patients 21.3% had both hypertension and diabetes mellitus (fulfilling the criteria for Grinspan's Syndrome). Out of this Grinspan's Syndrome pool 94.7% (n=19) were taking drug atleast for one of the two conditions. Conclusion: As noticed form the medical history of the patients, most of them were using hypoglycemic drugs for diabetes mellitus and beta blockers, diuretics and calcium channel blockers for hypertension. These drugs are known for lichenoid reaction. Therefore, it should be ruled out at histopathological/ immunological and molecular level whether these patients are suffering from lichen planus or lichenoid drug reaction to truly declare them as patients with Grinspan’s Syndrome.

Keywords: diabetes mellitus, grinspan's syndrome, lichenoid drug reaction, oral lichen planus

Procedia PDF Downloads 239

Authors: Tamar Trop

Abstract:

Bike sharing systems can be important elements of smart cities as they have the potential for impact on multiple levels. These systems can add a significant alternative to other modes of mass transit in cities that are continuously looking for measures to become more livable and maintain their attractiveness for citizens, businesses and tourism. Bike-sharing began in Europe in 1965, and a viable format emerged in the mid-2000s thanks to the introduction of information technology. The rate of growth in bike-sharing schemes and fleets has been very rapid since 2008 and has probably outstripped growth in every other form of urban transport. Today, public bike-sharing systems are available on five continents, including over 700 cities, operating more than 800,000 bicycles at approximately 40,000 docking stations. Since modern bike sharing systems have become prevalent only in the last decade, the existing literature analyzing these systems and their sustainability is relatively new. The purpose of the presented study is to assess the sustainability of these newly emerging transportation systems, by using the Envision™ rating system as a methodological framework and the Israeli 'Tel -O-Fun' – bike sharing project as a case study. The assessment was conducted by project team members. Envision™ is a new guidance and rating system used to assess and improve the sustainability of all types and sizes of infrastructure projects. This tool provides a holistic framework for evaluating and rating the community, environmental, and economic benefits of infrastructure projects over the course of their life cycle. This evaluation method has 60 sustainability criteria divided into five categories: Quality of life, leadership, resource allocation, natural world, and climate and risk. 'Tel -O-Fun' project was launched in Tel Aviv-Yafo on 2011 and today provides about 1,800 bikes for rent, at 180 rental stations across the city. The system is based on a complex computer terminal that is located in the docking stations. The highest-rated sustainable features that the project scored include: (a) Improving quality of life by: offering a low cost and efficient form of public transit, improving community mobility and access, enabling the flexibility of travel within a multimodal transportation system, saving commuters time and money, enhancing public health and reducing air and noise pollution; (b) improving resource allocation by: offering inexpensive and flexible last-mile connectivity, reducing space, materials and energy consumption, reducing wear and tear on public roads, and maximizing the utility of existing infrastructure, and (c) reducing of greenhouse gas emissions from transportation. Overall, 'Tel -O-Fun' project was highly scored as an environmentally sustainable and socially equitable infrastructure. The use of this practical framework for evaluation also yielded various interesting insights on the shortcoming of the system and the characteristics of good solutions. This can contribute to the improvement of the project and may assist planners and operators of bike sharing systems to develop a sustainable, efficient and reliable transportation infrastructure within smart cities.

Keywords: bike sharing, Envision™, sustainability rating system, sustainable infrastructure

Procedia PDF Downloads 334

Authors: Xiaohui Zhao, Shahan Mafuz

Abstract:

Context-aware technologies provide system applications with the awareness of environmental conditions, customer behaviour, object movements, etc. Further, with such capability system applications can be smart to adapt intelligently their responses to the changing conditions. Concerning business operations, this promises businesses that their business processes can run more intelligently, adaptively and flexibly, and thereby either improve customer experience, enhance reliability of service delivery, or lower operational cost, to make the business more competitive and sustainable. Aiming at realizing such context-aware business process management, this paper firstly explores its potential benefit and then identifies some gaps between the current business process management support and the expected. In addition, some preliminary solutions are also discussed with context definition, rule-based process execution, run-time process evolution, etc. A framework is also presented to give a conceptual architecture of context-aware business process management system to guide system implementation.

Keywords: business process adaptation, business process evolution, business process modelling, and context awareness

Procedia PDF Downloads 407

Authors: Wania Mohammad Akram, Swetha Kannan, Urooj Shahid, Aisha Sajjad

Abstract:

Ovarian ectopic pregnancy, a rare manifestation of ectopic gestation, involves the implantation of a fertilized egg on the ovarian surface. This condition poses diagnostic challenges and is associated with significant maternal morbidity if not promptly managed. This report presents the case of a 33-year-old nulliparous woman with a history of polycystic ovary syndrome (PCOS) undergoing ovulation induction therapy. Following her first conception in October 2021, she presented with symptoms of per vaginal spotting and low back pain, prompting a diagnosis of left adnexal ectopic pregnancy confirmed by transvaginal ultrasound and serum beta-human chorionic gonadotropin (B-HCG) levels. Medical management with methotrexate was initiated successfully. In August 2022, the patient conceived again, with subsequent ultrasound revealing a large pelvic collection suggestive of a complex ectopic pregnancy involving both ovaries. Despite initial stability, she developed abdominal pain necessitating emergency laparoscopy, which revealed an ovarian ectopic pregnancy with hemoperitoneum. Laparotomy was performed due to the complexity of the presentation, and histopathology confirmed viable chorionic villi within ovarian tissue. This case underscores the clinical management challenges posed by ovarian ectopic pregnancies, particularly in patients with previous ectopic pregnancies. The discussion reviews current literature on diagnostic modalities, treatment strategies, and outcomes associated with ovarian ectopic pregnancies, emphasizing the role of surgical intervention in cases refractory to conservative management. Tailored approaches considering individual patient factors are crucial to optimize outcomes and preserve fertility in such complex scenarios.

Keywords: obgyn, ovarian ectopic pregnancy, laproscopy, pcos

Procedia PDF Downloads 26

Authors: Fatemeh Karimi

Abstract:

The fashion and textile industry is undergoing a profound transformation, with polymers playing an increasingly pivotal role in driving innovation and sustainability. This paper explores the application of polymers in fashion and textile engineering, focusing on their impact on material properties, sustainability, and the future of garment production. Polymers, both synthetic and bio-based, offer unique opportunities to enhance the performance, durability, and environmental footprint of textiles. By examining recent advancements in polymer science and their integration into fashion design and production, we provide insights into how these materials are reshaping the industry. This paper also discusses the challenges and opportunities associated with the use of polymers, particularly in the context of sustainable fashion and circular economy practices. Through case studies and industry examples, we highlight the innovative ways in which polymers are being utilized to meet the evolving demands of consumers and the industry's sustainability goals.

Keywords: polymer textiles, sustainable fashion, bio-based polymers, smart textiles, fashion innovation, circular economy, textile engineering

Procedia PDF Downloads 13

Authors: George Kurian, Hongmei Chi

Abstract:

Digital evidence plays a critical role in most legal investigations. In many cases, thumbnail databases show important information in that investigation. The probability of having digital evidence retrieved from a computer or smart device has increased, even though the previous user removed data and deleted apps on those devices. Due to the increase in digital forensics, the ability to store residual information from various thumbnail applications has improved. This paper will focus on investigating thumbnail information from Windows 10. Thumbnail images of interest in forensic investigations may be intact even when the original pictures have been deleted. It is our research goal to recover useful information from thumbnails. In this research project, we use various forensics tools to collect left thumbnail information from deleted videos or pictures. We examine and describe the various thumbnail sources in Windows and propose a methodology for thumbnail collection and analysis from laptops or desktops. A machine learning algorithm is adopted to help speed up content from thumbnail pictures.

Keywords: digital forensic, forensic tools, soundness, thumbnail, machine learning, OCR

Procedia PDF Downloads 128

Authors: Thanasis K. Barlas, Helge A. Madsen

Abstract:

A novel Active Flap System (AFS) has been developed at DTU Wind Energy, as a result of a 3-year R\&D project following almost 10 years of innovative research in this field. The full-scale AFS comprises an active deformable trailing edge has been tested at the unique rotating test facility at the Risoe Campus of DTU Wind Energy in Denmark. The design and instrumentation of the wing section and the active flap system (AFS) are described. The general description and objectives of the rotating test rig at the Risoe campus of DTU are presented, as used for the aeroelastic testing of the AFS in the recently finalized INDUFLAP project. The general description and objectives are presented, along with an overview of sensors on the setup and the test cases. The post-processing of data is discussed and results of steady flap step and azimuth control flap cases are presented.

Keywords: morphing, adaptive, flap, smart blade, wind turbine

Procedia PDF Downloads 395

Authors: Ju-young Hwang, Hyo-Gyoung Kwak, Hong Jae Yim

Abstract:

This paper introduces a numerical analysis method for reinforced-concrete (RC) structures exposed to fire and compares the result with experimental results. The proposed analysis method for RC structure under the high temperature consists of two procedures. First step is to decide the temperature distribution across the section through the heat transfer analysis by using the time-temperature curve. After determination of the temperature distribution, the nonlinear analysis is followed. By considering material and geometrical non-linearity with the temperature distribution, nonlinear analysis predicts the behavior of RC structure under the fire by the exposed time. The proposed method is validated by the comparison with the experimental results. Finally, Prediction model to describe the status of after-cooling concrete can also be introduced based on the results of additional experiment. The product of this study is expected to be embedded for smart structure monitoring system against fire in u-City.

Keywords: RC structures, heat transfer analysis, nonlinear analysis, after-cooling concrete model

Procedia PDF Downloads 363

Authors: Faraji Sepideh

Abstract:

Nowadays, purchase rate of the smart device is increasing and user authentication is one of the important issues in information security. Alphanumeric strong passwords are difficult to memorize and also owners write them down on papers or save them in a computer file. In addition, text password has its own flaws and is vulnerable to attacks. Graphical password can be used as an alternative to alphanumeric password that users choose images as a password. This type of password is easier to use and memorize and also more secure from pervious password types. In this paper we have designed a more secure graphical password system to prevent shoulder surfing, smudge and brute force attack. This scheme is a combination of two types of graphical passwords recognition based and Cued recall based. Evaluation the usability and security of our proposed scheme have been explained in conclusion part.

Keywords: brute force attack, graphical password, shoulder surfing attack, smudge attack

Procedia PDF Downloads 157

Authors: Andrey A. Tyuftin, David Clarke, Malco C. Cruz-Romero, Declan Bolton, Seamus Fanning, Shashi K. Pankaj, Carmen Bueno-Ferrer, Patrick J. Cullen, Joe P. Kerry

Abstract:

Prolonging of shelf-life is essential in order to address issues such as; supplier demands across continents, economical profit, customer satisfaction, and reduction of food wastage. Smart packaging solutions presented in the form of naturally occurred antimicrobially-active packaging may be a solution to these and other issues. Gelatin film forming solution with adding of natural sourced antimicrobials is a promising tool for the active smart packaging. The objective of this study was to coat conventional plastic hydrophobic packaging material with hydrophilic antimicrobial active beef gelatin coating and conduct shelf life trials on beef sub-primal cuts. Minimal inhibition concentration (MIC) of Caprylic acid sodium salt (SO) and commercially available Auranta FV (AFV) (bitter oranges extract with mixture of nutritive organic acids) were found of 1 and 1.5 % respectively against bacterial strains Bacillus cereus, Pseudomonas fluorescens, Escherichia coli, Staphylococcus aureus and aerobic and anaerobic beef microflora. Therefore SO or AFV were incorporated in beef gelatin film forming solution in concentration of two times of MIC which was coated on a conventional plastic LDPE/PA film on the inner cold plasma treated polyethylene surface. Beef samples were vacuum packed in this material and stored under chilling conditions, sampled at weekly intervals during 42 days shelf life study. No significant differences (p < 0.05) in the cook loss was observed among the different treatments compared to control samples until the day 29. Only for AFV coated beef sample it was 3% higher (37.3%) than the control (34.4 %) on the day 36. It was found antimicrobial films did not protect beef against discoloration. SO containing packages significantly (p < 0.05) reduced Total viable bacterial counts (TVC) compared to the control and AFV samples until the day 35. No significant reduction in TVC was observed between SO and AFV films on the day 42 but a significant difference was observed compared to control samples with a 1.40 log of bacteria reduction on the day 42. AFV films significantly (p < 0.05) reduced TVC compared to control samples from the day 14 until the day 42. Control samples reached the set value of 7 log CFU/g on day 27 of testing, AFV films did not reach this set limit until day 35 and SO films until day 42 of testing. The antimicrobial AFV and SO coated films significantly prolonged the shelf-life of beef steaks by 33 or 55% (on 7 and 14 days respectively) compared to control film samples. It is concluded antimicrobial coated films were successfully developed by coating the inner polyethylene layer of conventional LDPE/PA laminated films after plasma surface treatment. The results indicated that the use of antimicrobial active packaging coated with SO or AFV increased significantly (p < 0.05) the shelf life of the beef sub-primal. Overall, AFV or SO containing gelatin coatings have the potential of being used as effective antimicrobials for active packaging applications for muscle-based food products.

Keywords: active packaging, antimicrobials, edible coatings, food packaging, gelatin films, meat science

Procedia PDF Downloads 299

Authors: Ayşe Defne Öz, Özlem Bozkurt

Abstract:

Alzheimer's Disease (AD) is counted as one of the most important global health problems and the main cause of dementia. The term dementia refers to a wide spectrum of disorders characterized by global, chronic, and generally irreversible cognitive deterioration. It is estimated that %60 % to 80 of the cases of dementia are because of AD. Alzheimer's is a slowly progressive brain disease. The reason for AD is unknown to the author's best knowledge, yet it is one of the topics that is most researched. AD shows the histopathologically abnormal accumulation of the protein beta-amyloid (plague) outside neurons and twisted strands of the protein tau (tangles) inside neurons in the brain. These changes are accompanied by damage to the brain tissue and the death of neurons. AD causes people to have difficulty remembering names or conversations. Some of the later symptoms are difficulty in talking and walking. Alzheimer's Disease is elevated by the illness and mortality of COVID-19. COVID-19 has affected many lives globally and had profound effects on human lives. COVID-19 is caused by SARS-CoV-2, which is a virus that attacks the respiratory and central nervous system and has neuroinvasive potential. More than %80 of COVID-19 patients have ageusia or anosmia, representing the pathognomic features of the disease. Patients with dementia are frail, and with the COVID-19 pandemic, including isolation, cognitive decline may exacerbate. Furthermore, patients with AD can be unable to follow the directions, such as covering their mouth and nose while coughing and can live in nursing homes which makes them more open to being infected. As COVID-19 is highly infectious and its management requires isolation and quarantine, the need for caregivers for AD management conflicts with that of COVID-19 and adds an extra burden on AD patients, caregivers, families, society, and the economy. Due to the entry of SARS-CoV-2 into the central nervous system, inflammation caused by COVID-19, prolonged hospitalization, and delirium, it has been reported that COVID-19 causes many neurological disorders and predisposition to AD.

Keywords: Alzheimer's disease, COVID-19, dementia, SARS-CoV-2

Procedia PDF Downloads 73

Authors: Surya R. Niraula, Devendra B Chhetry, Girish K. Singh, S. Nagesh, Frederick A. Connell

Abstract:

Background: Although random sampling is generally considered to be the gold standard for population-based research, the majority of drug abuse research is based on non-random sampling despite the well-known limitations of this kind of sampling. Method: We compared the statistical properties of two surveys of drug abuse in the same community: one using snowball sampling of drug users who then identified “friend controls” and the other using a random sample of non-drug users (controls) who then identified “friend cases.” Models to predict drug abuse based on risk factors were developed for each data set using conditional logistic regression. We compared the precision of each model using bootstrapping method and the predictive properties of each model using receiver operating characteristics (ROC) curves. Results: Analysis of 100 random bootstrap samples drawn from the snowball-sample data set showed a wide variation in the standard errors of the beta coefficients of the predictive model, none of which achieved statistical significance. One the other hand, bootstrap analysis of the random-sample data set showed less variation, and did not change the significance of the predictors at the 5% level when compared to the non-bootstrap analysis. Comparison of the area under the ROC curves using the model derived from the random-sample data set was similar when fitted to either data set (0.93, for random-sample data vs. 0.91 for snowball-sample data, p=0.35); however, when the model derived from the snowball-sample data set was fitted to each of the data sets, the areas under the curve were significantly different (0.98 vs. 0.83, p < .001). Conclusion: The proposed method of random sampling of controls appears to be superior from a statistical perspective to snowball sampling and may represent a viable alternative to snowball sampling.

Keywords: drug abuse, matched case-control study, non-probability sampling, probability sampling

Procedia PDF Downloads 488