Search results for: bobsleigh/skeleton ice track

Authors: Thabiso Sthembiso Msomi

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SMEs are the main engine of growth in most developing economies. One of the main factors that hinder the development of SME is access to finance. In this study, we explored the factors that hinder the growth and survival of SMEs in South Africa. The capital structure theory formed the theoretical underpinning for the study. The quantitative research design was adopted and data was collected from retail, construction, manufacturing and agriculture sectors of SMEs within the KwaZulu-Natal province of South Africa. The modified version of the Cochran formula was used to determine the sample size as 321 SMEs and analysed using the five-point Likert scale. The purposive sampling technique was used to select owners of SME. Statistical Package for the Social Sciences (SPSS) was used for the data analysis through Exploratory Factor Analysis (EFA) to determine the factor structures of items employed to measure each of the constructs in this study. Then, the Cronbach’s alpha test was conducted to determine the reliability of each construct. Kaiser-Meyer-Olkin (KMO) was used to determine the adequacy of the sample size. Linear regression was done to determine the effect of the independent variables on the dependent variable. The findings suggest that the main constraints facing South African SMEs were the lack of experienced management. Furthermore, the SMEs would fail to raise customer awareness of their products and services, which in turn affects their market access and monthly turnover. The study recommends that SMEs keep up-to-date records of business transactions to enable the business to keep track of its operations. The study recommends that South African banks adopt an SME accounting and bookkeeping program. The finding of this study benefits policymakers in both the private and public sectors.

Keywords: small businesses, access to finances, COVID-19, SMEs survival

Procedia PDF Downloads 151

Authors: Dassou Nagassou

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Recent increase in frequency and severity of climatic impacts throughout the world has put a particular emphasis on the urgency to address the anthropogenic greenhouse gas emissions. The latter, mainly composed of carbon dioxide are responsible for the global warming of planet earth. Despite efforts to transition towards a zero-emission economy, manufacturing industries, electricity generation power plants, and transportation sectors continue to encounter challenges which hinder their progress towards a full decarbonization. The growing energy demand from both developed and under-developed economies exacerbates the situation and as a result, more carbon dioxide is discharged into the atmosphere. This situation imposes a lot of constraints on industries which are involved i.e., manufacturing industries, transportation, and electricity generation which must navigate the stringent environmental regulations in order to remain profitable. Existing solutions such as energy efficiencies, green materials (life cycle analysis), and many more have fallen short to address the problem due to their inadaptation to existing infrastructures, low efficiencies, and prohibitive costs. The proposed technology exploits the synergistic interaction between solar radiation and plasma to boost a direct decomposition of the molecules of carbon dioxide while producing alternative fuels which can be used to sustain on-site high-temperature processes via 100% solar energy harvesting in the form of photons and electricity. The advantages of this technology and its ability to be easily integrated into existing systems make it appealing for the industry which can now afford to fast track on the path towards full decarbonization, thanks to the solar plasma reactor. Despite the promising experimental results which proved the viability of this concept, solar-plasma reactors require further investigations to understand the synergistic interactions between plasma and solar radiation for a potential technology scale-up.

Keywords: solar, non-equilibrium, plasma, reactor, greenhouse-gases, solar-fuels

Procedia PDF Downloads 38

Authors: Marah El-Beeli, Abdullah Balkhair, Zakaryia Al Muharmi, Samir Al Adawi, Mansoor Al-Jabri, Abdullah Al Rawahi, Hazaa Al Yahyae, Eman Al Balushi, Yahya M. Al-Farsi

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The health care service and the anticancer chemotherapeutics has changed the natural history of cancer into manageable chronic disease and improve the cancer patient’s lifestyle and increase the survival time. Despite that, still, infection is the major dilemma opposing the cancer patient either because of the clinical presentation of the cancer type and impaired immune system or as a consequence of anticancer therapy. This study has been conducted to1) track changes in the epidemiology of hospital-acquired bloodstream infections among patients with malignancies in the last five years. 2) To explore the causative pathogens and 3) the outcome of HA-BSIs in patients with a different types of malignancies. An ampi-directional study (retrospective and prospective follow up) of patients with malignancies admitted at Sultan Qaboos University hospital (570-bed tertiary hospital) during the study period (from January 2015 to December 2019). The cumulative frequency and prevalence rates of HA-BSIs by patients and isolates were calculated. In addition, the cumulative frequency of participants with single versus mixed infections and types of causative micro-organisms of HA-BSIs were obtained. A total of 1246 event of HA-BSIs has occurred during the study period. Nearly the third (30.25%) of the HA-BSI events was identified among 288 patients with malignancies. About 20% of cases were mixed infections (more than one isolate). Staphylococcus spp were the predominant isolated pathogen (24.7%), followed by Klebsiella spp (15.8%), Escherichia spp (13%), and Pseudomonas spp (9.3%). About half (51%) of cases died in the same year, and (64%) of the deaths occur within two weeks after the infection. According to the observations, no changes in the trends of epidemiology, causative pathogens, morbidity, and mortality rates in the last five years.

Keywords: epidemiology, haematological malignancies, hospital acquired bloodstream infections, solid malignancies

Procedia PDF Downloads 121

Authors: Nadine Wiesmann, Melanie Viel, Christoph Buhr, Rachel Tanner, Wolfgang Tremel, Juergen Brieger

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Recidivation of tumors and the development of resistances against the classical anti-tumor approaches represent a major challenge we face when treating cancer. In order to master this challenge, we are in desperate need of new treatment options beyond the beaten tracks. Zinc oxide nanoparticles (ZnO NPs) represent such an innovative approach. Zinc oxide is characterized by a high level of biocompatibility, concurrently ZnO NPs are able to exert anti-tumor effects. By concentration of the nanoparticles at the tumor site, tumor cells can specifically be exposed to the nanoparticles while low zinc concentrations at off-target sites are tolerated well and can be excreted easily. We evaluated the toxicity of ZnO NPs in vitro with the help of immortalized tumor cell lines and primary cells stemming from healthy tissue. Additionally, the Chorioallantoic Membrane Assay (CAM Assay) was employed to gain insights into the in vivo behavior of the nanoparticles. We could show that ZnO NPs interact with tumor cells as nanoparticulate matter. Furthermore, the extensive release of zinc ions from the nanoparticles nearby and within the tumor cells results in overload with zinc. Beyond that, ZnO NPs were found to further the generation of reactive oxygen species (ROS). We were able to show that tumor cells were more prone to the toxic effects of ZnO NPs at intermediate concentrations compared to fibroblasts. With the help of ZnO NPs covered by a silica shell in which FITC dye was incorporated, we were able to track ZnO NPs within tumor cells as well as within a whole organism in the CAM assay after injection into the bloodstream. Depending on the applied concentrations, selective tumor cell killing seems feasible. Furthermore, the combinational treatment of tumor cells with radiotherapy and ZnO NPs shows promising results. Still, further investigations are needed to gain a better understanding of the interaction between ZnO NPs and the human body to be able to pave the way for their application as an innovative anti-tumor agent in the clinics.

Keywords: metal oxide nanoparticles, nanomedicine, overcome resistances against classical treatment options, zinc oxide nanoparticles

Procedia PDF Downloads 105

Authors: Catarina Isabel Ramos Pereira, Jorge Machado, Begona Alonso Criado, Maria João Santos

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Introduction: Gait disorders are one of the symptoms that have severe implications on the quality of life in Parkinson's disease (PD). Currently, there is no therapy to reverse or treat this condition. None of the drugs used in conventional medical treatment is entirely efficient, and all have a high incidence of side effects. Acupuncture treatment is believed to improve motor ability, but there is still little scientific evidence in individuals with PD. Aim: The aim of the study is to investigate the acute effect of acupuncture on gait parameters in Parkinson's disease. Methods: This is a randomized and controlled crossover study. The same individual patient was part of both the experimental (real acupuncture) and control group (false acupuncture/sham), and the sequence was randomized. Gait parameters were measured at two different moments, before and after treatment, using four force platforms as well as the collection of 3D markers positions taken by 11 cameras. Images were quantitatively analyzed using Qualisys Track Manager software that let us extract data related to the quality of gait and balance. Seven patients with the diagnosis of Parkinson's disease were included in the study. Results: Statistically significant differences were found in gait speed (p = 0.016), gait cadence (p = 0.006), support base width (p = 0.0001), medio-lateral oscillation (p = 0.017), left-right step length (p = 0.0002), and stride length: right-right (p = 0.0000) and left-left (p = 0.0018), time of left support phase (p = 0.029), right support phase (p = 0.025) and double support phase (p = 0.015), between the initial and final moments for the experimental group. Differences in right-left stride length were found for both groups. Conclusion: Our results show that acupuncture could enhance gait in Parkinson's disease patients. Deep research involving a larger number of volunteers should be accomplished to validate these encouraging findings.

Keywords: acupuncture, traditional Chinese medicine, Parkinson's disease, gait

Procedia PDF Downloads 149

Authors: Mualla McManus, Jenna Luche Thaye

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World Health Organisation International Classification of Disease codes were created to define disease including infections in order to guide and educate diagnosticians. Most infectious diseases such as syphilis are clearly defined by their ICD 10 codes and aid/help to educate the clinicians in syphilis diagnosis and treatment globally. However, current ICD 10 codes for relapsing fever Borreliosis and Lyme disease are less clearly defined and can impede appropriate diagnosis especially if the clinician is not familiar with the symptoms of these infectious diseases. This is despite substantial number of scientific articles published in peer-reviewed journals about relapsing fever and Lyme disease. In the USA there are estimated 380,000 people annually contacting Lyme disease, more cases than breast cancer and 6x HIV/AIDS cases. This represents estimated 0.09% of the USA population. If extrapolated to the global population (7billion), 0.09% equates to 63 million people contracting relapsing fever or Lyme disease. In many regions, the rate of contracting some form of infection from tick bite may be even higher. Without accurate and appropriate diagnostic codes, physicians are impeded in their ability to properly care for their patients, leaving those patients invisible and marginalized within the medical system and to those guiding public policy. This results in great personal hardship, pain, disability, and expense. This unnecessarily burdens health care systems, governments, families, and society as a whole. With accurate diagnostic codes in place, robust data can guide medical and public health research, health policy, track mortality and save health care dollars. Better defined ICD codes are the way forward in educating the diagnosticians about relapsing fever and Lyme diseases.

Keywords: WHO ICD codes, relapsing fever, Lyme diseases, World Health Organisation

Procedia PDF Downloads 167

Authors: Tanka Nath Dahal

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Community-based forestry is seen as a promising instrument for sustainable forest management (SFM) through the purposeful involvement of local communities. Globally, forest area managed by local communities is on the rise. However, transferring management responsibilities to forest users alone cannot guarantee the sustainability of forest management. A monitoring tool, that allows the local communities to track the progress of forest management towards the goal of sustainability, is essential. A case study, including six forest user groups (FUGs), two from each three community-based forestry models—community forestry (CF), buffer zone community forestry (BZCF), and collaborative forest management (CFM) representing three different physiographic regions, was conducted in Nepal. The study explores which community-based forest management model (CF, BZCF or CFM) is doing well in terms of sustainable forest management. The study assesses the overall performance of the three models towards SFM using locally developed criteria (four), indicators (26) and verifiers (60). This paper attempts to quantify the sustainability of the models using sustainability index for individual criteria (SIIC), and overall sustainability index (OSI). In addition, rating to the criteria and scoring of the verifiers by the FUGs were done. Among the four criteria, the FUGs ascribed the highest weightage to institutional framework and governance criterion; followed by economic and social benefits, forest management practices, and extent of forest resources. Similarly, the SIIC was found to be the highest for the institutional framework and governance criterion. The average values of OSI for CFM, CF, and BZCF were 0.48, 0.51 and 0.60 respectively; suggesting that buffer zone community forestry is the more sustainable model among the three. The study also suggested that the SIIC and OSI help local communities to quantify the overall progress of their forestry practices towards sustainability. The indices provided a clear picture of forest management practices to indicate the direction where they are heading in terms of sustainability; and informed the users on issues to pay attention to enhancing the sustainability of their forests.

Keywords: community forestry, collaborative management, overall sustainability, sustainability index for individual criteria

Procedia PDF Downloads 227

Authors: Huang Wei-Chi, Li Wei, Yu Tien-Chieh

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Medication adherence is crucial for treatment success. Adherence problem is common in patients with polypharmacy, especially in the geriatric population who are vulnerable to multiple chronic conditions but averagely less knowledgeable about diseases and medications. In order to help patients take medications appropriately and enhance the understanding of diseases or medications, a Line official account named e-Pharmacist was designed. The line is a popular freeware app with the highest penetration rate (95.7%) in Taiwan. The interface of e-Pharmacist is user-friendly for easy-to-read and convenient operating. Differ from other medication adherence apps, users just added e-Pharmacist as a LINE friend without installing any more apps and the drug lists were automatically downloaded from the personal electronic medical records with security permission. Over and above medication reminder, several additional capabilities were set up and engaged in the platform of e-Pharmacist including prescription refill reservation, laboratory examination consultation, medical appointment registration, and “Daily Health Log” where patients can record and track data of blood pressure/blood sugar and daily meals for self-health management as well as can share the important information to clinical professionals when seeking medical help. Additionally, a Line chatbot was utilized to provide tailored medicine information for the individual user. From July 2020 to March 2022, around 3000 patients added e-pharmacist as Line friends. Every day more than 1500 patients receive messages from e-pharmacist to notify them to take medicine. Thanks to the e-pharmacist alert system and Chatbot, the low-compliance patients (defined by Program on Adherence to Medication, PAM) significantly dropped from 36% to 6%, whereas the high-compliance patients dramatically increased from 13% to 77%. The user satisfaction is 98%. In brief, an e-pharmacist is not only a medication reminder but also a tailored personal assistant with value-added service for health management.

Keywords: e-pharmacist, self-health management, medication reminder, value-added service

Procedia PDF Downloads 129

Authors: Gihan Thilakarathna, Fernando Ishara, Rathnayake Yasith, Bandara A. M. R. Y.

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E-learning is a crucial component of intelligent education. Even in the midst of a pandemic, E-learning is becoming increasingly important in the educational system. Several e-learning programs are accessible for students. Here, we decided to create an e-learning framework for children. We've found a few issues that teachers are having with their online classes. When there are numerous students in an online classroom, how does a teacher recognize a student's focus on academics and below-the-surface behaviors? Some kids are not paying attention in class, and others are napping. The teacher is unable to keep track of each and every student. Key challenge in e-learning is online exams. Because students can cheat easily during online exams. Hence there is need of exam proctoring is occurred. In here we propose an automated online exam cheating detection method using a web camera. The purpose of this project is to present an E-learning platform for math education and include games for kids as an alternative teaching method for math students. The game will be accessible via a web browser. The imagery in the game is drawn in a cartoonish style. This will help students learn math through games. Everything in this day and age is moving towards automation. However, automatic answer evaluation is only available for MCQ-based questions. As a result, the checker has a difficult time evaluating the theory solution. The current system requires more manpower and takes a long time to evaluate responses. It's also possible to mark two identical responses differently and receive two different grades. As a result, this application employs machine learning techniques to provide an automatic evaluation of subjective responses based on the keyword provided to the computer as student input, resulting in a fair distribution of marks. In addition, it will save time and manpower. We used deep learning, machine learning, image processing and natural language technologies to develop these research components.

Keywords: math, education games, e-learning platform, artificial intelligence

Procedia PDF Downloads 129

Authors: Balakrishna Shetty

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Introduction: Stem Cell Imaging is a challenging field since the advent of Stem Cell treatment in humans. Series of research on tagging and tracking the stem cells has not been very effective. The present study is an effort by the authors to track the stem cells injected into calf muscles by Magnetic Resonance Diffusion Weighted Imaging. Materials and methods: Stem Cell injection deep into the calf muscles of patients with peripheral vascular disease is one of the recent treatment modalities followed in our institution. 5 patients who underwent deep intramuscular injection of stem cells as treatment were included for this study. Pre and two hours Post injection MRI of bilateral calf regions was done using 1.5 T Philips Achieva, 16 channel system using 16 channel torso coils. Axial STIR, Axial Diffusion weighted images with b=0 and b=1000 values with back ground suppression (DWIBS sequence of Philips MR Imaging Systems) were obtained at 5 mm interval covering the entire calf. The invert images were obtained for better visualization. 120ml of autologous bone marrow derived stem cells were processed and enriched under c-GMP conditions and reduced to 40ml solution containing mixture of above stem cells. Approximately 40 to 50 injections, each containing 0.75ml of processed stem cells, was injected with marked grids over the calf region. Around 40 injections, each of 1ml normal saline, is injected into contralateral leg as control. Results: Significant Diffusion hyper intensity is noted at the site of injected stem cells. No hyper intensity noted before the injection and also in the control side where saline was injected conclusion: This is one of the earliest studies in literature showing diffusion hyper intensity in intramuscularly injected stem cells. The advantages and deficiencies in this study will be discussed during the presentation.

Keywords: stem cells, imaging, DWI, peripheral vascular disease

Procedia PDF Downloads 46

Authors: Junfeng Yan, Wenkui Hou

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Prognostics and Health Management (PHM) is a technology to monitor the equipment status and predict impending faults. It is used to predict the potential fault and provide fault information and track trends of system degradation by capturing characteristics signals. So how to detect characteristics signals is very important. The select of test point plays a very important role in detecting characteristics signal. Traditionally, we use dependency model to select the test point containing the most detecting information. But, facing the large complicated system, the dependency model is not built so easily sometimes and the greater trouble is how to calculate the matrix. Rely on this premise, the paper provide a highly effective method to select test point without dependency model. Because signal flow model is a diagnosis model based on failure mode, which focuses on system’s failure mode and the dependency relationship between the test points and faults. In the signal flow model, a fault information can flow from the beginning to the end. According to the signal flow model, we can find out location and structure information of every test point and module. We break the signal flow model up into serial and parallel parts to obtain the final relationship function between the system’s testability or prediction metrics and test points. Further, through the partial derivatives operation, we can obtain every test point’s importance degree in determining the testability metrics, such as undetected rate, false alarm rate, untrusted rate. This contributes to installing the test point according to the real requirement and also provides a solid foundation for the Prognostics and Health Management. According to the real effect of the practical engineering application, the method is very efficient.

Keywords: false alarm rate, importance degree, signal flow model, undetected rate, untrusted rate

Procedia PDF Downloads 357

Authors: Abdolrasoul Daneshjoo

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The purpose of this research was to study the effect of aerobic exercises with 75% heart beats on the amount of urea, uric acid and creatine in blood of Iranian soccer national U-23 players. 27 players were selected according to the following demographic specifications: age: 21.4±1.60 years old; weight: 68±9.4 kg; height: 174.2±8.6 cm. Urea, uric acid and creatine in blood are considered as dependent variations where as 40 minutes running on a track with maximum 75% heart beats are independent variations. Heart beat and blood pressure in rest time, age, height, and weight are considered as the controlled variations. Maximum heart beats are recorded under maximum exercises (8 minutes and 150-250 watt energy) on ergo meter. Then, in order to determine independent variations, 75% maximum heart beats are considered for each player. Blood is taken twice (before and after determining independence variation). Moreover, the players are given a few instructions to be fulfilled 24 hours before the main exercises. Laboratory analysis method for blood urea sample is deacetyl ammoniom, for uric acid Karvy test and for creatine pyric acid. 'T' formula is applied for analyzing statistical data in dependent groups with degree of freedom 7 (d.f=7) urea and uric acid contain P>0.01 and P>0.05 for creatine. 1. Aerobic exercise can effect on the concentration of urea of blood as well as uric acid and creatine in blood serum and increase the amount of them. 2. Urea of blood serum increases from 26.75±2.59 to 28.9±2.67 (25%) with 40 minutes running and 75% heart beat. 3. Aerobic exercise causes uric acid increase 12.5% from 5.7±0.52 (before exercise) to 6.1±0.71 (after exercise). Creatine of blood serum increases from 1.36±0.27 (before exercise) to 1.85±0.49 (after exercise). We came to this result that during aerobic exercise catabolism of protein substrate increases. Moreover, augmentation of urea, uric acid and creatine in blood serum as metabolic poisons causes disorder in kidney. Also, tendons and joints are affected by these poisons. Appropriate diet and exercise can prevent production of these poisons resulted from heavy exercise.

Keywords: aerobic exercise, urea, uric acid, creatine, blood, soccer national players

Procedia PDF Downloads 509

Authors: Shilpa Balan

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Radio Frequency Identification, also popularly known as RFID is used to automatically identify and track tags attached to items. This study focuses on the application of RFID in healthcare. The adoption of RFID in healthcare is a crucial technology to patient safety and inventory management. Data from RFID tags are used to identify the locations of patients and inventory in real time. Medical errors are thought to be a prominent cause of loss of life and injury. The major advantage of RFID application in healthcare industry is the reduction of medical errors. The healthcare industry has generated huge amounts of data. By discovering patterns and trends within the data, big data analytics can help improve patient care and lower healthcare costs. The number of increasing research publications leading to innovations in RFID applications shows the importance of this technology. This study explores the current state of research of RFID in healthcare using a text mining approach. No study has been performed yet on examining the current state of RFID research in healthcare using a data mining approach. In this study, related articles were collected on RFID from healthcare journal and news articles. Articles collected were from the year 2000 to 2015. Significant keywords on the topic of focus are identified and analyzed using open source data analytics software such as Rapid Miner. These analytical tools help extract pertinent information from massive volumes of data. It is seen that the main benefits of adopting RFID technology in healthcare include tracking medicines and equipment, upholding patient safety, and security improvement. The real-time tracking features of RFID allows for enhanced supply chain management. By productively using big data, healthcare organizations can gain significant benefits. Big data analytics in healthcare enables improved decisions by extracting insights from large volumes of data.

Keywords: RFID, data mining, data analysis, healthcare

Procedia PDF Downloads 202

Authors: Guillaume Richard, Sarra Zaied

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Marine waste quantities increase more and more, 5 million tons of plastic waste enter the ocean every year. Their spatiotemporal distribution is never homogeneous and depends mainly on the hydrodynamic characteristics of the environment, as well as the size and location of the waste. As part of optimizing collect of marine plastic wastes, it is important to measure and monitor their evolution over time. In this context, diverse studies have been dedicated to describing waste behavior in order to identify its accumulation in ocean areas. None of the existing tools which track objects at sea had the objective of tracking down a slick of waste. Moreover, the applications related to marine waste are in the minority compared to rescue applications or oil slicks tracking applications. These approaches are able to accurately simulate an object's behavior over time but not during the collection mission of a waste sheet. This paper presents numerical modeling of a boat’s wake impact on the floating marine waste behavior during a collection mission. The aim is to predict the trajectory of a marine waste slick to optimize its collection using meteorological data of ocean currents, wind, and possibly waves. We have made the choice to use Ocean Parcels which is a Python library suitable for trajectoring particles in the ocean. The modeling results showed the important role of advection and diffusion processes in the spatiotemporal distribution of floating plastic litter. The performance of the proposed method was evaluated on real data collected from the Copernicus Marine Environment Monitoring Service (CMEMS). The results of the evaluation in Cape of Good Hope (South Africa) prove that the proposed approach can effectively predict the position and velocity of marine litter during collection, which allowed for optimizing time and more than $90\%$ of the amount of collected waste.

Keywords: marine litter, advection-diffusion equation, sea current, numerical model

Procedia PDF Downloads 62

Authors: Rose A. Yemson, Ping Jiang, Oyedeji L. Inumoh

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The deployment of wireless sensor network has rapidly increased, however with the increased capacity and diversity of sensors, and applications ranging from biological, environmental, military etc. generates tremendous volume of data’s where more attention is placed on the distributed sensing and little on how to manage, analyze, retrieve and understand the data generated. This makes it more quite difficult to process live sensor data, run concurrent control and update because sensor data are either heavyweight, complex, and slow. This work will focus on developing a web service platform for automatic detection of sensors, acquisition of sensor data, storage of sensor data into a database, processing of sensor data using reconfigurable software components. This work will also create a web service based sensor data management system to monitor physical movement of an individual wearing wireless network sensor technology (SunSPOT). The sensor will detect movement of that individual by sensing the acceleration in the direction of X, Y and Z axes accordingly and then send the sensed reading to a database that will be interfaced with an internet platform. The collected sensed data will determine the posture of the person such as standing, sitting and lying down. The system is designed using the Unified Modeling Language (UML) and implemented using Java, JavaScript, html and MySQL. This system allows real time monitoring an individual closely and obtain their physical activity details without been physically presence for in-situ measurement which enables you to work remotely instead of the time consuming check of an individual. These details can help in evaluating an individual’s physical activity and generate feedback on medication. It can also help in keeping track of any mandatory physical activities required to be done by the individuals. These evaluations and feedback can help in maintaining a better health status of the individual and providing improved health care.

Keywords: HTML, java, javascript, MySQL, sunspot, UML, web-based, wireless network sensor

Procedia PDF Downloads 191

Authors: Feifei Wu, Pius Babuna, Xiaohua Yang

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The suitability evaluation of human settlements over time and space is essential to track potential challenges towards suitable human settlements and provide references for policy-makers. This study established a theoretical framework of human settlements based on the nature, human, economy, society and residence subsystems. Evaluation indicators were determined with the consideration of the coupling effect among subsystems. Based on the extended Fourier amplitude sensitivity test algorithm, the global sensitivity analysis that considered the coupling effect among indicators was used to determine the weights of indicators. The human settlement suitability was evaluated at both subsystems and comprehensive system levels in 30 provinces of China between 2000 and 2016. The findings were as follows: (1) human settlements suitability index (HSSI) values increased significantly in all 30 provinces from 2000 to 2016. Among the five subsystems, the suitability index of the residence subsystem in China exhibited the fastest growinggrowth, fol-lowed by the society and economy subsystems. (2) HSSI in eastern provinces with a developed economy was higher than that in western provinces with an underdeveloped economy. In con-trast, the growing rate of HSSI in eastern provinces was significantly higher than that in western provinces. (3) The inter-provincial difference of in HSSI decreased from 2000 to 2016. For sub-systems, it decreased for the residence system, whereas it increased for the economy system. (4) The suitability of the natural subsystem has become a limiting factor for the improvement of human settlements suitability, especially in economically developed provinces such as Beijing, Shanghai, and Guangdong. The results can be helpful to support decision-making and policy for improving the quality of human settlements in a broad nature, human, economy, society and residence context.

Keywords: human settlements, suitability evaluation, extended fourier amplitude, human settlement suitability

Procedia PDF Downloads 51

Authors: Tzen-Ying Ling

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Recently, the resilience of dwellings in urban areas has been deliberated, as to accommodate the growing demand for changing the demography and rapid urbanization. The need to incorporate sustainability and cleaner production thinking have intensified to mitigate climate risks and satisfy the demand for housing. The modular thinking satisfies both the pressing call for fast-tracked housing stocks; while meeting the goal of more sustainable production. In the other side, the importance of the dwelling as a podium for well-being and social connectedness are sought to explore the key human/environment design thinking for the modular system in dwelling. We argue the best practice incorporates the concept of systemic components thinking. The fieldwork reported in this paper illustrates the process of the case study in a modular dwelling unit prototype development; focusing on the systemic frame system design process and adjustment recommendation hereafter. Using a case study method, the study identified that: (1) inclusive human dimensional factoring through systemic design thinking results in affordable implementations possibilities. (2) The environmental dimension encourages the place-based solution suited for the locality and the increasing demand for dwelling in the urban system. (3) Prototype design consideration avails module system component as dwelling construction alternative. (4) Building code often acts as an inhibitor for such dwelling units by the restriction in lot sizes and units placement. The demand for fast-track dwelling construction and cleaner production decisively outweighs the code inhibition; we further underscored the sustainability implication of the alternative prototype as the core of this study. The research suggests that modular thinking results in a resilient solution suited for the locality and the increasing demand for dwelling in the urban system.

Keywords: system prototype, urban resilience, human/environment dimension, modular thinking, dwelling alternative

Procedia PDF Downloads 149

Authors: A. Barratt, M. H. Granat, S. Buttress, B. Roy

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Introduction: Physiotherapy is an essential part of the treatment of patients with shoulder problems. The focus of treatment is usually centred on addressing specific physiotherapy goals, ultimately resulting in the improvement in pain and function. This study investigates if computerised physiotherapy using gamification principles are as effective as standard physiotherapy. Methods: Physiotherapy exergames were created using a combination of commercially available hardware, the Microsoft Kinect, and bespoke software. The exergames used were validated by mapping physiotherapy goals of physiotherapy which included; strength, range of movement, control, speed, and activation of the kinetic chain. A multicenter, randomised prospective controlled trial investigated the use of exergames on patients with Shoulder Impingement Syndrome who had undergone Arthroscopic Subacromial Decompression surgery. The intervention group was provided with the automated sensor-based technology, allowing them to perform exergames and track their rehabilitation progress. The control group was treated with standard physiotherapy protocols. Outcomes from different domains were used to compare the groups. An important metric was the assessment of shoulder range of movement pre- and post-operatively. The range of movement data included abduction, forward flexion and external rotation which were measured by the software, pre-operatively, 6 weeks and 12 weeks post-operatively. Results: Both groups show significant improvement from pre-operative to 12 weeks in elevation in forward flexion and abduction planes. Results for abduction showed an improvement for the interventional group (p < 0.015) as well as the test group (p < 0.003). Forward flexion improvement was interventional group (p < 0.0201) with the control group (p < 0.004). There was however no significant difference between the groups at 12 weeks for abduction (p < 0.118067) , forward flexion (p < 0.189755) or external rotation (p < 0.346967). Conclusion: Exergames may be used as an alternative to standard physiotherapy regimes; however, further analysis is required focusing on patient engagement.

Keywords: shoulder, physiotherapy, exergames, gamification

Procedia PDF Downloads 156

Authors: Altilio Rosa, Chirico Francesco, Foglia Goffredo

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In recent years, the number of Unmanned Aerial Vehicles (UAVs) has significantly increased. The rapid development of commercial and recreational drones makes them an important part of our society. Despite the growing list of their applications, these vehicles pose a huge threat to civil and military installations: detection, classification and neutralization of such flying objects become an urgent need. Radar is an effective remote sensing tool for detecting and tracking flying objects, but scenarios characterized by the presence of a high number of tracks related to flying birds make especially challenging the drone detection task: operator PPI is cluttered with a huge number of potential threats and his reaction time can be severely affected. Flying birds compared to UAVs show similar velocity, RADAR cross-section and, in general, similar characteristics. Building from the absence of a single feature that is able to distinguish UAVs and birds, this paper uses a multiple features approach where an original feature selection technique is developed to feed binary classifiers trained to distinguish birds and UAVs. RADAR tracks acquired on the field and related to different UAVs and birds performing various trajectories were used to extract specifically designed target movement-related features based on velocity, trajectory and signal strength. An optimization strategy based on a genetic algorithm is also introduced to select the optimal subset of features and to estimate the performance of several classification algorithms (Neural network, SVM, Logistic regression…) both in terms of the number of selected features and misclassification error. Results show that the proposed methods are able to reduce the dimension of the data space and to remove almost all non-drone false targets with a suitable classification accuracy (higher than 95%).

Keywords: birds, classification, machine learning, UAVs

Procedia PDF Downloads 188

Authors: Aniketh Ravukutam, Rajath Rao M., Pradyumna S. A.

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In the past few decades there has been great advancement in use of aerodynamics in cars. Now its use has been evident from commercial cars to race cars for achieving higher speeds, stability and efficiency. This paper focusses on studying the effects of aerodynamics in Formula Student car. These cars weigh around 200kgs with an average speed of 60kmph. With increasing competition every year, developing a competitive car is a herculean task. The race track comprises mostly of tight corners and little or no straights thus testing the car’s cornering capabilities. Higher cornering speeds can be achieved by increasing traction at the tires. Studying the aerodynamics helps in achieving higher traction without much addition in overall weight of car. The main focus is to develop an aerodynamic package involving front wing, under tray and body to obtain an optimum value of down force. The initial process involves the detail study of geometrical constraints mentioned in the rule book and calculating the limiting value of drag as per the engine specifications. The successive steps involve conduction of various iterations in ANSYS for selection of airfoils, deciding the number of elements, designing the nose for low drag, channelizing the flow under the body and obtain an optimum value of down force within the limits defined in the initial process. The final step involves design of model using these results in Virtual environment called OptimumLap® for detailed study of performance with and without the presence of aerodynamics. The CFD analysis results showed an overall down force of 377.44N with a drag of 164.08N. The corresponding parameters of the last model were applied in OptimumLap® and an improvement of 3.5 seconds in lap times was observed.

Keywords: aerodynamics, formula student, traction, front wing, undertray, body, rule book, drag, down force, virtual environment, computational fluid dynamics (CFD)

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Authors: Komal Vig

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Cardiovascular disease (CVD)-related deaths occur in 17.3 million people globally each year, accounting for 30% of all deaths worldwide, with a predicted annual incidence of deaths to reach 23.3 million globally by 2030. Autologous bypass grafts remain an important therapeutic option for the treatment of CVD, but the poor quality of the donor patient’s blood vessels, the invasiveness of the resection surgery, and postoperative movement restrictions create issues. The present study is aimed to improve the endothelialization of intimal surface of graft by using low temperature plasma (LTP) to increase the cell attachment and proliferation. Polytetrafluoroethylene (PTFE) was treated with LTP. Air was used as the feed-gas, and the pressure in the plasma chamber was kept at 800 mTorr. Scaffolds were also modified with gelatin and collagen by dipping method. Human umbilical vein endothelial cells (HUVEC) were plated on the developed scaffolds, and cell proliferation was determined by the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT) assay and by microscopy. mRNA expressions levels of different cell markers were investigated using quantitative real-time PCR (qPCR). XPS confirmed the introduction of oxygenated functionalities from LTP. HUVEC cells showed 80% seeding efficiency on the scaffold. Microscopic and MTT assays indicated increase in cell viability in LTP treated scaffolds, especially when treated with gelatin or collagen, compared to untreated scaffolds. Gene expression studies shows enhanced expression of cell adhesion marker Integrin- α 5 gene after LTP treatment. LTP treated scaffolds exhibited better cell proliferation and viability compared to untreated scaffolds. Protein treatment of scaffold increased cell proliferation. Based on our initial results, more scaffolds alternatives will be developed and investigated for cell growth and vascularization studies. Acknowledgments: This work is supported by the NSF EPSCoR RII-Track-1 Cooperative Agreement OIA-2148653.

Keywords: LTP, HUVEC cells, vascular graft, endothelialization

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Authors: Javad Sarvestan, Zdenek Svoboda

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Force-time (F-T) curvature characteristics are globally referenced as the main indicators of athletic jump performance. Nevertheless, to the best of authors’ knowledge, no investigation tried to deeply study the relationship between F-T curve variables and real-game jump performance among elite volleyball players. To this end, this study was designated to investigate the association between F-T curve variables, including movement timings, force, velocity, power, rate of force development (RFD), modified reactive strength index (RSImod), and net impulse with spike jump height during real-game circumstances. Twelve young elite volleyball players performed 3 countermovement jump (CMJ) and 3 spike jump in real-game circumstances with 1-minute rest intervals to prevent fatigue. Shapiro-Wilk statistical test illustrated the normality of data distribution, and Pearson’s product correlation test portrayed a significant correlation between CMJ height and peak RFD (0.85), average RFD (r=0.81), RSImod (r=0.88) and concentric net impulse (r=0.98), and also significant correlation between spike jump height and peak RFD (0.73), average RFD (r=0.80), RSImod (r=0.62) and concentric net impulse (r=0.71). Multiple regression analysis also reported that these factors have a strong contribution in predicting of CMJ (98%) and spike jump (77%) heights. Outcomes of this study confirm that the RFD, concentric net impulse, and RSImod values could precisely monitor and track the volleyball attackers’ explosive strength, muscular stretch-shortening cycle function efficiency, and ultimate spike jump height. To this effect, volleyball coaches and trainers are advised to have an in-depth focus on their athletes’ progression or the impacts of strength trainings by observing and chasing the F-T curve variables such as RFD, net impulse, and RSImod.

Keywords: net impulse, reactive strength index, rate of force development, stretch-shortening cycle

Procedia PDF Downloads 116

Authors: Mustafa Al Sukar, Azzam Sleit, Abdullatif Abu-Dalhoum, Bassam Al-Kasasbeh

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Use and abuse of drugs by teens is very common and can have dangerous consequences. The drugs contribute to physical and sexual aggression such as assault or rape. Some teenagers regularly use drugs to compensate for depression, anxiety or a lack of positive social skills. Teen resort to smoking should not be minimized because it can be "gateway drugs" for other drugs (marijuana, cocaine, hallucinogens, inhalants, and heroin). The combination of teenagers' curiosity, risk taking behavior, and social pressure make it very difficult to say no. This leads most teenagers to the questions: "Will it hurt to try once?" Nowadays, technological advances are changing our lives very rapidly and adding a lot of technologies that help us to track the risk of drug abuse such as smart phones, Wireless Sensor Networks (WSNs), Internet of Things (IoT), etc. This technique may help us to early discovery of drug abuse in order to prevent an aggravation of the influence of drugs on the abuser. In this paper, we have developed a Decision Support System (DSS) for detecting the drug abuse using Artificial Neural Network (ANN); we used a Multilayer Perceptron (MLP) feed-forward neural network in developing the system. The input layer includes 50 variables while the output layer contains one neuron which indicates whether the person is a drug addict. An iterative process is used to determine the number of hidden layers and the number of neurons in each one. We used multiple experiment models that have been completed with Log-Sigmoid transfer function. Particularly, 10-fold cross validation schemes are used to access the generalization of the proposed system. The experiment results have obtained 98.42% classification accuracy for correct diagnosis in our system. The data had been taken from 184 cases in Jordan according to a set of questions compiled from Specialists, and data have been obtained through the families of drug abusers.

Keywords: drug addiction, artificial neural networks, multilayer perceptron (MLP), decision support system

Procedia PDF Downloads 272

Authors: Tamara Jimah, Priscilla Kehoe, Pamela Pimentel, Amir Rahmani, Nikil Dutt, Yuqing Guo

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Ensuring equitable access to maternal health care is critical for public health. Particularly for underserved women, community health workers (CHWs) have been invaluable in providing support through health education and strategies for improved maternal self-care management. Our research aimed to assess the acceptance of technology by CHWs and perinatal women to promote healthy pregnancy and postpartum wellness. This pilot study was conducted at a local community organization in Orange County, California, where CHWs play an important role in supporting low-income women through home visitations. Questionnaires were administered to 14 CHWs and 114 pregnant and postpartum women, literate in English and/or Spanish. CHWs tested two wearable devices (Galaxy watch and Oura ring) and shared their user experience, including potential reception by the perinatal women they served. In addition, perinatal women provided information on access to a smart phone and the internet, as well as their interest in using wearable devices to self-monitor personal health with guidance from a CHW. Over 85% of CHWs agreed that it was useful to track pregnancy with the smart watch and ring. The majority of perinatal women owned a smartphone (97.4%), had access to the internet (80%) and unlimited data plans (78%), expressed interest in using the smart wearable devices to self-monitor health, and were open to receiving guidance from a CHW (87%). Community health workers and perinatal women embraced the use of wearable technology to monitor maternal health. These preliminary findings have formed the basis of an ongoing research study that integrates CHW guidance and technology (i.e., smart watch, smart ring, and a mobile phone app) to promote self-efficacy and self-management among underserved perinatal women.

Keywords: community health workers, health promotion and education, health equity, maternal and child health, technology

Procedia PDF Downloads 125

Authors: Umashankar Morya, Somnath Basu

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Metalloids like arsenic are often present as contaminants in industrial effluents. Removal of the same is essential before the safe discharge of the wastewater into the environment. Otherwise, these pollutants tend to percolate into aquifers over a period of time and contaminate drinking water sources. Several adsorbents, including metal powders, carbon nanotubes and zeolites, are being used for this purpose, with varying degrees of success. However, most of these solutions are not only costly but also not always readily available. This restricts their use, especially among financially weaker communities. Slag generated globally from primary steelmaking operations exceeds 200 billion kg every year. Some of it is utilized for applications like road construction, filler in reinforced concrete, railway track ballast and recycled into iron ore agglomeration processes. However, these usually involve low-value addition, and a significant amount of the slag still ends up in a landfill. However, there is a strong possibility that the constituents in the steelmaking slag may immobilize metalloid contaminants present in wastewater through a combination of adsorption and precipitation of insoluble product(s). Preliminary experiments have already indicated that exposure to basic oxygen steelmaking slag does reduce pollutant concentration in wastewater. In addition, the slag is relatively inexpensive and available in large quantities and in several countries across the world. Investigations on the mechanism of interactions at the water-solid interfaces have been in progress for some time. However, at the same time, there are concerns about the possibility of leaching of metal ions from the slag particles in concentrations greater than what exists in the water bodies where the “treated” wastewater would eventually be discharged. The effect of such leached ions on the aquatic flora and fauna is yet uncertain. This has prompted the present investigation, which focuses on the leaching of metal ions from steelmaking slag particles in contact with wastewater, and the influence of these ions on the removal of contaminant species. Experiments were carried out to quantify the leaching behavior of different ionic species upon exposure of the slag particles to simulated wastewater, both with and without specific metalloid contaminants.

Keywords: slag, water, metalloid, heavy metal, wastewater

Procedia PDF Downloads 46

Authors: Ghufran Ahmed, Muhammad Osama Siddiqui, Shahbaz Siddiqui, Rauf Ahmad Shams Malick, Faisal Khan, Mubashir Khan

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In this paper, a machine learning-based approach for early prediction of diseases in cows is proposed. Different ML algos are applied to extract useful patterns from the available dataset. Technology has changed today’s world in every aspect of life. Similarly, advanced technologies have been developed in livestock and dairy farming to monitor dairy cows in various aspects. Dairy cattle monitoring is crucial as it plays a significant role in milk production around the globe. Moreover, it has become necessary for farmers to adopt the latest early prediction technologies as the food demand is increasing with population growth. This highlight the importance of state-ofthe-art technologies in analyzing how important technology is in analyzing dairy cows’ activities. It is not easy to predict the activities of a large number of cows on the farm, so, the system has made it very convenient for the farmers., as it provides all the solutions under one roof. The cattle industry’s productivity is boosted as the early diagnosis of any disease on a cattle farm is detected and hence it is treated early. It is done on behalf of the machine learning output received. The learning models are already set which interpret the data collected in a centralized system. Basically, we will run different algorithms on behalf of the data set received to analyze milk quality, and track cows’ health, location, and safety. This deep learning algorithm draws patterns from the data, which makes it easier for farmers to study any animal’s behavioral changes. With the emergence of machine learning algorithms and the Internet of Things, accurate tracking of animals is possible as the rate of error is minimized. As a result, milk productivity is increased. IoT with ML capability has given a new phase to the cattle farming industry by increasing the yield in the most cost-effective and time-saving manner.

Keywords: IoT, machine learning, health care, dairy cows

Procedia PDF Downloads 32

Authors: Hajar Zarei, AliAkbar Zarenejadatashgah, Vuk Uskoković, Hiroshi Watabe

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The reactive oxygen species (ROS) generated by radiation in nuclear diagnostic imaging and radiotherapy could damage the structure of the proteins in noncancerous cells surrounding the tumor. The critical factor in many age-related diseases, such as Alzheimer, Parkinson, or Huntington diseases, is the oxidation of proteins by the ROS as molecular triggers of the given pathologies. Our studies by spectroscopic experiments showed doses close to therapeutic ones (1 to 5 Gy) could lead to changes of secondary and tertiary structures in BSA protein macromolecule as a protein model as well as the aggregation of polypeptide chain but without the fragmentation. For this reason, we investigated the radioprotective effects of natural (vitamin C and E) and synthetic materials (CNPs and FIOMPs) on the structural changes in BSA protein induced by gamma irradiation at a therapeutic dose (3Gy). In the presence of both vitamins and synthetic materials, the spectroscopic studies revealed that irradiated BSA was protected from the structural changes caused by ROS, according to in vitro research. The radioprotective property of CNPs and FIOMPs arises from enzyme mimetic activities (catalase, superoxide dismutase, and peroxidase) and their antioxidant capability against hydroxyl radicals. In the case of FIOMPs, a porous structure also leads to increased ROS recombination with each other in the same radiolytic track and subsequently decreased encounters with BSA. The hydrophilicity of vitamin C resulted in the major scavenging of ROS in the solvent, whereas hydrophobic vitamin E localized on the nonpolar patches of the BSA surface, where it did not only neutralize them thanks to the moderate BSA binding constant but also formed a barrier for diffusing ROS. To the best of our knowledge, there has been a persistent lack of studies investigating the radioactive effect of mentioned materials on proteins. Therefore, the results of our studies can open a new widow for application of these common dietary ingredients and new synthetic NPs in improving the safety of radiotherapy.

Keywords: reactive oxygen species, spectroscopy, bovine serum albumin, gamma radiation, radioprotection

Procedia PDF Downloads 60

Authors: Marcel Schneider, Nils Nießen

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Microscopic simulation programs enable the description of the two processes of railway operation and the previous timetabling. Occupation conflicts are often solved based on defined train priorities on both process levels. These conflict resolutions produce knock-on delays for the involved trains. The sum of knock-on delays is commonly used to evaluate the quality of railway operations. It is either compared to an acceptable level-of-service or the delays are evaluated economically by linearly monetary functions. It is impossible to properly evaluate dispatching decisions without a well-founded objective function. This paper presents a new approach for evaluation of dispatching decisions. It uses models of choice of transport and considers the behaviour of the end-costumers. These models evaluate the knock-on delays in more detail than linearly monetary functions and consider other competing modes of transport. The new approach pursues the coupling of a microscopic model of railway operation with the macroscopic model of choice of transport. First it will be implemented for the railway operations process, but it can also be used for timetabling. The evaluation considers the possibility to change over to other transport modes by the end-costumers. The new approach first looks at the rail-mounted and road transport, but it can also be extended to air transport. The split of the end-costumers is described by the modal-split. The reactions by the end-costumers have an effect on the revenues of the railway undertakings. Various travel purposes has different pavement reserves and tolerances towards delays. Longer journey times affect besides revenue changes also additional costs. The costs depend either on time or track and arise from circulation of workers and vehicles. Only the variable values are summarised in the contribution margin, which is the base for the monetary evaluation of the delays. The contribution margin is calculated for different resolution decisions of the same conflict. The conflict resolution is improved until the monetary loss becomes minimised. The iterative process therefore determines an optimum conflict resolution by observing the change of the contribution margin. Furthermore, a monetary value of each dispatching decision can also be determined.

Keywords: choice of transport, knock-on delays, monetary evaluation, railway operations

Procedia PDF Downloads 302

Authors: Xiaowei Zhang, Min Xu, Saeid Habibi, Fengjun Yan, Ryan Ahmed

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Recently, Electric Vehicles (EVs) have received extensive consideration since they offer a more sustainable and greener transportation alternative compared to fossil-fuel propelled vehicles. Lithium-Ion (Li-ion) batteries are increasingly being deployed in EVs because of their high energy density, high cell-level voltage, and low rate of self-discharge. Since Li-ion batteries represent the most expensive component in the EV powertrain, accurate monitoring and control strategies must be executed to ensure their prolonged lifespan. The Battery Management System (BMS) has to accurately estimate parameters such as the battery State-of-Charge (SOC), State-of-Health (SOH), and Remaining Useful Life (RUL). In order for the BMS to estimate these parameters, an accurate and control-oriented battery model has to work collaboratively with a robust state and parameter estimation strategy. Since battery physical parameters, such as the internal resistance and diffusion coefficient change depending on the battery state-of-life (SOL), the BMS has to be adaptive to accommodate for this change. In this paper, an extensive battery aging study has been conducted over 12-months period on 5.4 Ah, 3.7 V Lithium polymer cells. Instead of using fixed charging/discharging aging cycles at fixed C-rate, a set of real-world driving scenarios have been used to age the cells. The test has been interrupted every 5% capacity degradation by a set of reference performance tests to assess the battery degradation and track model parameters. As battery ages, the combined model parameters are optimized and tracked in an offline mode over the entire batteries lifespan. Based on the optimized model, a state and parameter estimation strategy based on the Extended Kalman Filter (EKF) and the relatively new Smooth Variable Structure Filter (SVSF) have been applied to estimate the SOC at various states of life.

Keywords: lithium-ion batteries, genetic algorithm optimization, battery aging test, parameter identification

Procedia PDF Downloads 243

Authors: Said Benaissa, David Plets, Emmeric Tanghe, Jens Trogh, Luc Martens, Leen Vandaele, Annelies Van Nuffel, Frank A. M. Tuyttens, Bart Sonck, Wout Joseph

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The herd monitoring and managing - in particular the detection of ‘attention animals’ that require care, treatment or assistance is crucial for effective reproduction status, health, and overall well-being of dairy cows. In large sized farms, traditional methods based on direct observation or analysis of video recordings become labour-intensive and time-consuming. Thus, automatic monitoring systems using sensors have become increasingly important to continuously and accurately track the health status of dairy cows. Wireless sensor networks (WSNs) and internet-of-things (IoT) can be effectively used in health tracking of dairy cows to facilitate herd management and enhance the cow welfare. Since on-cow measuring devices are energy-constrained, a proper characterization of the off-body wireless channel between the on-cow sensor nodes and the back-end base station is required for a power-optimized deployment of these networks in barns. The aim of this study was to characterize the off-body wireless channel in indoor (barns) environment at 868 MHz using LoRa nodes. LoRa is an emerging wireless technology mainly targeted at WSNs and IoT networks. Both large scale fading (i.e., path loss) and temporal fading were investigated. The obtained path loss values as a function of the transmitter-receiver separation were well fitted by a lognormal path loss model. The path loss showed an additional increase of 4 dB when the wireless node was actually worn by the cow. The temporal fading due to movement of other cows was well described by Rician distributions with a K-factor of 8.5 dB. Based on this characterization, network planning and energy consumption optimization of the on-body wireless nodes could be performed, which enables the deployment of reliable dairy cow monitoring systems.

Keywords: channel, channel modelling, cow monitoring, dairy cows, health monitoring, IoT, LoRa, off-body propagation, PLF, propagation

Procedia PDF Downloads 290