Search results for: quality sensor

Authors: Narottam Puri, Gurvinder Kaur

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Background: The National Accreditation Board for Hospitals & Healthcare Providers (NABH) is India’s apex standard setting accrediting body in health care which evaluates and accredits healthcare organizations. NABH requires accredited organizations to become reaccredited every three years. It is often though that once the initial accreditation is complete, the foundation is set and reaccreditation is a much simpler process. Fortis Hospital, Shalimar Bagh, a part of the Fortis Healthcare group is a 262 bed, multi-specialty tertiary care hospital. The hospital was successfully accredited in the year 2012. On completion of its first cycle, the hospital underwent a reaccreditation assessment in the year 2015. This paper aims to gain a better understanding of the challenges that accredited hospitals face when preparing for a renewal of their accreditations. Methods: The study was conducted using a cross-sectional mixed methods approach; semi-structured interviews were conducted with senior leadership team and staff members including doctors and nurses. Documents collated by the QA team while preparing for the re-assessment like the data on quality indicators: the method of collection, analysis, trending, continual incremental improvements made over time, minutes of the meetings, amendments made to the existing policies and new policies drafted was reviewed to understand the challenges. Results: The senior leadership had a concern about the cost of accreditation and its impact on the quality of health care services considering the staff effort and time consumed it. The management was however in favor of continuing with the accreditation since it offered competitive advantage, strengthened community confidence besides better pay rates from the payors. The clinicians regarded it as an increased non-clinical workload. Doctors felt accountable within a professional framework, to themselves, the patient and family, their peers and to their profession; but not to accreditation bodies and raised concerns on how the quality indicators were measured. The departmental leaders had a positive perception of accreditation. They agreed that it ensured high standards of care and improved management of their functional areas. However, they were reluctant in sparing people for the QA activities due to staffing issues. With staff turnover, a lot of work was lost as sticky knowledge and had to be redone. Listing the continual quality improvement initiatives over the last 3 years was a challenge in itself. Conclusion: The success of any quality assurance reaccreditation program depends almost entirely on the commitment and interest of the administrators, nurses, paramedical staff, and clinicians. The leader of the Quality Movement is critical in propelling and building momentum. Leaders need to recognize skepticism and resistance and consider ways in which staff can become positively engaged. Involvement of all the functional owners is the start point towards building ownership and accountability for standards compliance. Creativity plays a very valuable role. Communication by Mail Series, WhatsApp groups, Quizzes, Events, and any and every form helps. Leaders must be able to generate interest and commitment without burdening clinical and administrative staff with an activity they neither understand nor believe in.

Keywords: NABH, reaccreditation, quality assurance, quality indicators

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Authors: Obokhai Kess Asikhia

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This work explores design concept generation by understanding user needs through observation and interview. The aim is to examine several principles and guidelines in obtaining evidence from observing how users interact with the targeted product and interviewing them to acquire deep insights of their needs. With the help of Quality Function Deployment (QFD), the identified needs of the users while interacting with the product were ranked using the normalised weighting approach. Furthermore, a low fidelity prototype of the alarm clock is developed with a view of addressing the identified needs of the users. Finally, the low fidelity prototype design was evaluated with two design prototypes already existing in the market through a study involving 30 participants. Preliminary results reveal higher performance ratings by the majority of the participants of the new prototype compared to the other existing alarm clocks in the market used in the study.

Keywords: design concept, low fidelity prototype, normalised weighting approach, quality function deployment, user needs

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Authors: Chaouch Souad, Abdou Latifa, Larbi Chrifi Alaoui

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This paper deals with sensorless backstepping control of induction motor using MRAS technique associated to sliding mode approach. A high order genetic algorithm structure is used to approximate a control law designed by the Backstepping technique, and to find the best parameters globally optimized. However, the Backstepping control approach is unsuitable for high performance applications because the need of a speed sensor for increased accuracy and the absence of any error decay mechanism. In this paper a nonlinear observer, obtained by combining sliding mode structure and model reference adaptive system (MRAS), is designed for the rotor flux and rotor speed estimations. To validate the proposed method, the results are presented for showing the improved drive characteristics and performances.

Keywords: Backstepping Control, Induction Motor, Genetic Algorithm, Sliding Mode observer

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Authors: Aliya Hisam, Zia Ul Haq, Sohail Aziz, Patrick Doherty, Jill Pell

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Objective: To determine the effectiveness of Mobile health augmented Cardiac rehabilitation (MCard) on health-related quality of life (HRQoL) among post-acute coronary syndrome(post-ACS) patients. Methodology: In a randomized controlled trial, post-ACS patients were randomly allocated (1:1) to an intervention group (received MCard; counseling, empowering with self-monitoring devices, short text messages, in addition to standard post-ACS care) or control group (standard post-ACS care). HRQoL was assessed by generic Short Form-12 and MacNew quality of life myocardial infarction (QLMI) tools. Participants were followed for 24 weeks with data collection and analysis at three-time points (baseline, 12 weeks and 24 weeks). Result: At baseline, 160 patients (80 in each group; mean age 52.66+8.46 years; 126 males, 78.75%) were recruited, of which 121(75.62%) continued and were analyzed at 12-weeks and 119(74.37%) at 24-weeks. The mean SF-12 physical component score significantly improved in the MCard group at 12 weeks follow-up (48.93 vs. control 43.87, p<.001) and 24 weeks (53.52 vs. 46.82 p<.001). The mean SF-12 mental component scores also improved significantly in the MCard group at 12 weeks follow-up (44.84 vs. control 41.40, p<.001) and 24 weeks follow-up (48.95 vs 40.12, p<.001). At 12-and 24-week follow-up, all domains of MacNew QLMI (social, emotional, physical and global) were also statistically significant (p<.001) improved in the MCard group, unlike the control group. Conclusion: MCard is feasible and effective at improving all domains of HRQoL. There was an improvement in physical, mental, social, emotional and global domains among the MCard group in comparison to the control group. The addition of MCard programs to post-ACS standard care may improve patient outcomes and reduce the burden on the health care setting.

Keywords: acute coronary syndrome, mobile health augmented cardiac rehabilitation (MCard), cardiovascular diseases, cardiac rehabilitation, health-related quality of life, short form 12, MacNew QLMI

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Authors: Tadele Tesfaw, Ajit Pal Singh, Abebaw Mekonnen Gezahegn

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Welding is a basic manufacturing process for making components or assemblies. Recent welding economics research has focused on developing the reliable machinery database to ensure optimum production. Research on welding of materials like steel is still critical and ongoing. Welding input parameters play a very significant role in determining the quality of a weld joint. The metal active gas (MAG) welding parameters are the most important factors affecting the quality, productivity and cost of welding in many industrial operations. The aim of this study is to investigate the optimization process parameters for metal active gas welding for 60x60x5mm dead mild steel plate work-piece using Taguchi method to formulate the statistical experimental design using semi-automatic welding machine. An experimental study was conducted at Bishoftu Automotive Industry, Bishoftu, Ethiopia. This study presents the influence of four welding parameters (control factors) like welding voltage (volt), welding current (ampere), wire speed (m/min.), and gas (CO2) flow rate (lit./min.) with three different levels for variability in the welding hardness. The objective functions have been chosen in relation to parameters of MAG welding i.e., welding hardness in final products. Nine experimental runs based on an L9 orthogonal array Taguchi method were performed. An orthogonal array, signal-to-noise (S/N) ratio and analysis of variance (ANOVA) are employed to investigate the welding characteristics of dead mild steel plate and used in order to obtain optimum levels for every input parameter at 95% confidence level. The optimal parameters setting was found is welding voltage at 22 volts, welding current at 125 ampere, wire speed at 2.15 m/min and gas flow rate at 19 l/min by using the Taguchi experimental design method within the constraints of the production process. Finally, six conformations welding have been carried out to compare the existing values; the predicated values with the experimental values confirm its effectiveness in the analysis of welding hardness (quality) in final products. It is found that welding current has a major influence on the quality of welded joints. Experimental result for optimum setting gave a better hardness of welding condition than initial setting. This study is valuable for different material and thickness variation of welding plate for Ethiopian industries.

Keywords: Weld quality, metal active gas welding, dead mild steel plate, orthogonal array, analysis of variance, Taguchi method

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Authors: Mohammed Abaoli, Omer Kara

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The current research has investigated the soil quality status under dryland vegetation of Yabello district, Southern Ethiopia in which we should identify the nature and extent of salinity problem of the area for further research bases. About 48 soil samples were taken from 0-30, 31-60, 61-90 and 91-120 cm soil depths by opening 12 representative soil profile pits at 1.5 m depth. Soil color, texture, bulk density, Soil Organic Carbon (SOC), Cation Exchange Capacity (CEC), Na, K, Mg, Ca, CaCO₃, gypsum (CaSO₄), pH, Sodium Adsorption Ratio (SAR), Exchangeable Sodium Percentage (ESP) were analyzed. The dominant soil texture was silty-clay-loam.  Bulk density varied from 1.1 to 1.31 g/cm³. High SOC content was observed in 0-30 cm. The soil pH ranged from 7.1 to 8.6. The electrical conductivity shows indirect relationship with soil depth while CaCO₃ and CaSO₄ concentrations were observed in a direct relationship with depth. About 41% are non-saline, 38.31% saline, 15.23% saline-sodic and 5.46% sodic soils. Na concentration in saline soils was greater than Ca and Mg in all the soil depths. Ca and Mg contents were higher above 60 cm soil depth in non-saline soils. The concentrations of SO₂^-4 and HCO^-3 were observed to be higher at the most lower depth than upper. SAR value tends to be higher at lower depths in saline and saline-sodic soils, but decreases at lower depth of the non-saline soils. The distribution of ESP above 60 cm depth was in an increasing order in saline and saline-sodic soils. The result of the research has shown the direction to which extent of salinity we should consider for the Commiphora plant species we want to grow on the area. 

Keywords: commiphora species, dryland vegetation, ecological significance, soil quality, salinity problem

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Authors: Yose Rizal, Nuraini, Mirnawati, Maria Endo Mahata, Rio Darman, Dendi Kurniawan

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An experiment had been conducted to determine the effects of several levels of Neurospora crassa- fermented palm kernel cake in the diet on the production performance and egg-yolk quality of Arab laying-hens, and to obtain the appropriate level of this fermented palm kernel cake for reducing the utilization of concentrated feed in the diet. Three hundred Arab laying-hens of 72 weeks old were employed in this experiment, and randomly assigned to four treatments (0, 7.25, 10.15, and 13.05% fermented palm kernel cake in diets) in a completely randomized design with five replicates. Measured variables were production performance (feed consumption, egg-mass production, feed conversion, egg weight and hen-day egg production), and egg-yolk quality (ether extract and cholesterol contents, and egg-yolk color index). Results of experiment indicated that feed consumption, egg-mass production, feed conversion, egg weight, hen-day egg production and egg-yolk color index were not influenced (P>0.05) by diets. However, the ether extract and cholesterol contents of egg-yolk were very significantly reduced (P<0.01) by diets. In conclusion, Neurospora crassa-fermented palm kernel cake could be included up to 13.05% to effectively replace 45% concentrated feed in Arab laying-hens diet without adverse effect on the production performance.

Keywords: neurospora crassa-fermented palm kernel cake, Arab laying-hens, production performance, ether extract, cholesterol, egg-yolk color index

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Authors: Etaf Alkhlaifat

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This study drew conceptually on Communication Accommodation Theory to describe and analyze conversations between doctors and patients to examine the extent to which patients’ level of literacy represents one of the linguistic obstacles that may adversely influence the quality of healthcare services in Jordan. A thematic qualitative approach was employed to interpret the phenomena under study, which required direct observation and interviews with doctors (n=6) and patients (n=15) in natural Jordanian medical settings. This generated a comprehensive corpus of audio and videotaped data, which revealed that most doctors expressed dissatisfaction with patients’ ability to express themselves and comprehend them as a result of a lack of medical awareness and limited health education. The significance of this study rests on its detailed investigation of the impact of health literacy on patients’ health outcomes and while providing unique insights into how low health literacy could contribute to misunderstanding and potential ill-health.

Keywords: doctor-patient communication, health literacy, medical knowledge, communication accommodation theory, qualitative research

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Authors: Juneseok You, Chanho Park, Kuehwan Jang, Sungsoo Na

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Sensing of nanotoxic materials is strongly important, as their engineering applications are growing recently and results in that nanotoxic material can harmfully influence human health and environment. In current study we report the quartz crystal microbalance (QCM)-based, in situ and real-time sensing of nanotoxic-material by frequency shift. We propose the in situ detection of nanotoxic material of zinc oxice by using QCM functionalized with a taget-specific DNA. Since the mass of a target material is comparable to that of an atom, the mass change caused by target binding to DNA on the quartz electrode is so small that it is practically difficult to detect the ions at low concentrations. In our study, we have demonstrated the in-situ and fast detection of zinc oxide using the quartz crystal microbalance (QCM). The detection was derived from the DNA hybridization between the DNA on the quartz electrode. The results suggest that QCM-based detection opens a new avenue for the development of a practical water-testing sensor.

Keywords: nanotoxic material, qcm, frequency, in situ sensing

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Authors: Hamed Saremi, Shahla Saremi

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In today's competitive world, organizations are expected to surpass the competitors and benefit from the resources and benefits. Therefore, organizations need to improve the current performance is felt more than ever that this requires to identify organizational optimal strategies, and consider all strategies simultaneously. In this study, to enhance competitive advantage and according to customer requirements, alignment between business, production and marketing strategies, House of Quality (QFD) approach has been used and zero-one linear programming model has been studied. First, the alignment between production and marketing strategies with business strategy, independent weights of these strategies is calculated. Then with using QFD approach the aligned weights of optimal strategies in each production and marketing field will be obtained and finally the aligned marketing strategies selection with the purpose of allocating budget and specialist human resource to marketing functions will be done that lead to increasing competitive advantage and benefit.

Keywords: marketing strategy, business strategy, strategy alignment, house of quality deployment, production strategy

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Authors: Ruedee Niyomrath, Somboon Sarasit, Chaisri Tharaswatpipat

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This research aims to study the potential of local waste material in quantity and quality. The potential for such local forms of waste material used as renewable energy for the production of processed agricultural products. The results of this study are useful to producers of agricultural products to use fuel that in local, reduce production costs, and conservation. The results showed that Samut Songkhram is a small province located in the central Thailand, sea area, and subdivided into 3 districts. This province has a population of 80 percent of farmers and agriculture with 50 percent of the area planted to coconut growing. Productivity of coconut help create value for the primacy of the province. Waste materials from coconut have quantity and quality potentials for processing biomass into charcoal as the renewable energy for the production of processed agricultural products.

Keywords: waste, renewable energy, producing of product, processed agricultural products

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Authors: Mahsa Ghafouri, Guita Farivarsadri

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In urban open spaces, furniture plays a crucial role in meeting various needs of the users over time. Furniture consists of elements that not only can facilitate physical needs individually but also fulfill social, psychological, and cultural demands on an urban scale. Creating adjustable urban spaces and using flexible furniture can provide the possibility of using urban spaces for a wide range of uses and activities and allow the engagement of users with distinct abilities and limitations in these activities. Flexibility in urban furniture can be seen as designing a number of modular components that are movable, expandable, adjustable, and changeable to accommodate various functions. Although there is a great amount of research related to flexibility and its distinct insights into achieving spaces that can cope with changing demands, this fundamental issue is often neglected in the design of urban furniture. However, in the long term, to address changing public needs over time, it can be logical to bring this quality into the design process to make spaces that can be sustained for a long time. This study aims to first introduce diverse kinds of flexible furniture that can be designed for urban public spaces and then to realize how this flexible furniture can improve the quality of public open spaces and social interaction and make them more adaptable over time and, as a result, achieve social sustainability. This research is descriptive and is mainly based on an extensive literature review and the analysis and classification of existing examples around the world. This research tends to illustrate various kinds of approaches that can help designers create flexible furniture to enhance the sustainability and quality of urban open spaces and, in this way, act as a guide for urban designers in this respect.

Keywords: flexible furniture, flexible design, urban open spaces, adaptability, moveability, social sustainability

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Authors: Syed Imran Hussain Shah

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Air pollution rapidly impacts the Earth's climate and environmental quality, causing public health nuisances and cardio-pulmonary illnesses. Air pollution is a global issue, and all population groups in all the regions in the developed and developing parts of the world were affected by it. The promise of a reduction in deaths and diseases as per SDG No. 3 is an international commitment towards sustainable development. In that context, assessing and evaluating the ambient air quality is paramount. This article estimates the air pollution released by the vehicles on roads of Lahore, a mega city having 13.98 million populations. A survey was conducted on different fuel stations to determine the estimated fuel pumped to different types of vehicles from different fuel stations. The number of fuel stations in Lahore is around 350. Another survey was also conducted to interview the drivers to know the per-litre fuel consumption of other vehicles. Therefore, a survey was conducted on 189 fuel stations and 400 drivers using a combination of random sampling and convenience sampling methods. The sampling was done in a manner to cover all areas of the city including central commercial hubs, modern housing societies, industrial zones, main highways, old traditional population centres, etc. Mathematical equations were also used to estimate the emissions from different modes of vehicles. Due to the increase in population, the number of vehicles is increasing, and consequently, traffic emissions were rising at a higher level. Motorcycles, auto rickshaws, motor cars, and vans were the main contributors to Carbon dioxide and vehicular emissions in the air. It has been observed that vehicles that use petrol fuel produce more Carbon dioxide emissions in the air. Buses and trucks were the main contributors to NOx in the air due to the use of diesel fuel. Whereas vans, buses, and trucks produce the maximum amount of SO2. PM10 and PM2.5 were mainly produced by motorcycles and motorcycle two-stroke rickshaws. Auto rickshaws and motor cars mainly produce benzene emissions. This study may act as a major tool for traffic and vehicle policy decisions to promote better fuel quality and more fuel-efficient vehicles to reduce emissions.

Keywords: particulate matter, nitrogen dioxide, climate change, pollution control

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Authors: Lamiek Abraham, Xinli Du, Yohan Noh, Polin Hsu, Tingting Wu, Tom Logan, Ifan Yen

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In the field of minimally invasive, smart medical instruments such as catheters and guidewires are typically used at a remote distance to gain access to the diseased artery, often negotiating tortuous, complex, and diseased vessels in the process. Three optical fiber sensors with a diameter of 1.5mm each that are 120° apart from each other is proposed to be mounted into a catheter-based pump device with a diameter of 10mm. These sensors are configured to solve the challenges surgeons face during insertion through curvy major vessels such as the aortic arch. Moreover, these sensors deal with providing information on rubbing the walls and shape sensing. This study presents an experimental and mathematical models of the optical fiber sensors with 2 degrees of freedom. There are two eight gear-shaped tubes made up of 3D printed thermoplastic Polyurethane (TPU) material that are connected. The optical fiber sensors are mounted inside the first tube for protection from external light and used TPU material as a prototype for a catheter. The second tube is used as a flat reflection for the light intensity modulation-based optical fiber sensors. The first tube is attached to the linear guide for insertion and withdrawal purposes and can manually turn it 45° by manipulating the tube gear. A 3D hard material phantom was developed that mimics the aortic arch anatomy structure in which the test was carried out. During the insertion of the sensors into the 3D phantom, datasets are obtained in terms of voltage, distance, and position of the sensors. These datasets reflect the characteristics of light intensity modulation of the optical fiber sensors with a plane project of the aortic arch structure shape. Mathematical modeling of the light intensity was carried out based on the projection plane and experiment set-up. The performance of the system was evaluated in terms of its accuracy in navigating through the curvature and information on the position of the sensors by investigating 40 single insertions of the sensors into the 3D phantom. The experiment demonstrated that the sensors were effectively steered through the 3D phantom curvature and to desired target references in all 2 degrees of freedom. The performance of the sensors echoes the reflectance of light theory, where the smaller the radius of curvature, the more of the shining LED lights are reflected and received by the photodiode. A mathematical model results are in good agreement with the experiment result and the operation principle of the light intensity modulation of the optical fiber sensors. A prototype of a catheter using TPU material with three optical fiber sensors mounted inside has been developed that is capable of navigating through the different radius of curvature with 2 degrees of freedom. The proposed system supports operators with pre-scan data to make maneuverability and bendability through curvy major vessels easier, accurate, and safe. The mathematical modelling accurately fits the experiment result.

Keywords: Intensity modulated optical fiber sensor, mathematical model, plane projection, shape sensing.

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Authors: Louis Denis Kevin Catherine, Raja Aziz Raja Ma’arof, Azrina Arshad, Sangeeth Suresh

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Machining parameters are very important in determining the surface quality of any material. In the past decade, some new engineering materials were developed for the manufacturing industry which created a need to conduct an investigation on the impact of the said parameters on their surface roughness. The polyurethane (PU) block is widely used in the automotive industry to manufacture parts such as checking fixtures that are used to verify the dimensional accuracy of automotive parts. In this paper, the design of experiment (DOE) was used to investigate the effect of the milling parameters on the PU block. Furthermore, an analysis of the machined surface chemical composition was done using scanning electron microscope (SEM). It was found that the surface roughness of the PU block is severely affected when PU undergoes a flood machining process instead of a dry condition. In addition, the step over and the silicon content were found to be the most significant parameters that influence the surface quality of the PU block.

Keywords: polyurethane (PU), design of experiment (DOE), scanning electron microscope (SEM), surface roughness

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Authors: Rizwan Iqbal

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Introduction: Re-TURBT has been recommended by international guidelines for patients with non-muscle invasive bladder cancer (NMIBC) who are deemed high-risk. Indications for re-TURBTs remain controversial and studies show mixed outcomes. It should be performed when the initial TURBT specimen lacks detrusor muscle, has tumor stage pT1 or G3/high-grade, or where resection is deemed incomplete. This ensures complete resection of tumors that have a high risk of recurrence as well as accurately identifying any tumors which have been upstaged. The aim of this audit was to evaluate the quality of re-TURBTs in a district general hospital. Method: Data were retrospectively collected from 31 patients who had re-TURBTs between April 2021 and September 2022. Data included baseline demographics, time from initial to re-TURBT, quality of operation note, presence of residual tumor, complications, and administration of chemotherapy within 24 hours of the initial TURBT. Data collection remains ongoing at the time of writing. Results: The mean age was 76 years old and 71.0% of patients were male. 32.3% of patients had their re-TURBT within six weeks and 32.3% had intravesical chemotherapy administered within 24 hours of the initial TURBT. 74.2% of initial TURBTs had detrusor muscle present in the specimen. 48.4% of patients had residual disease following re-TURBT. Just one patient had their pathology upstaged at re-TURBT. The use of the TURBT proforma on the operation note was variable, with 51.6% and 38.7% of surgeons using the proforma after the initial and re-TURBT. Conclusion: Re-TURBT improves bladder cancer staging and is necessary in patients who are deemed high-risk in order to identify any upstaging or recurrence of the disease.

Keywords: urology, bladder cancer, turbt, cancer

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Authors: Shih-Ching Wang, Mark Lang

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This paper examines the secondary effects and consequences of special displays on subsequent shopping behavior. Special displays are studied as a prominent form of in-store or shopper marketing activity. Two experiments are performed using special value and special quality-oriented displays in an online simulated store environment. The impact of exposure to special displays on mindsets and resulting product choices are tested in a shopping task. Impact on store image is also tested. The experiments find that special displays do trigger shopping mindsets that affect product choices and shopping basket composition and value. There are intended and unintended positive and negative effects found. Special value displays improve store price image but trigger a price sensitive shopping mindset that causes more lower-priced items to be purchased, lowering total basket dollar value. Special natural food displays improve store quality image and trigger a quality-oriented mindset that causes fewer lower-priced items to be purchased, increasing total basket dollar value. These findings extend the theories of product categorization, mind-sets, and price sensitivity found in communication research into the retail store environment. Findings also warn retailers to consider the total effects and consequences of special displays when designing and executing in-store or shopper marketing activity.

Keywords: special displays, mindset, shopping behavior, price consciousness, product categorization, store image

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Authors: Jeongmin Kim, Eunju Lee, Kwang Ryel Ryu

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This paper addresses the problem of predictive control for energy management of large-scaled exhibition halls, where a lot of energy is consumed to maintain internal atmosphere under certain required conditions. Predictive control achieves better energy efficiency by optimizing the operation of air-conditioning facilities with not only the current but also some future status taken into account. In this paper, we propose to use predictive models learned from past sensor data of hall environment, for use in optimizing the operating plan for the air-conditioning facilities by simulating future environmental change. We have implemented an emulator of an exhibition hall by using EnergyPlus, a widely used building energy emulation tool, to collect data for learning environment-change models. Experimental results show that the learned models predict future change highly accurately on a short-term basis.

Keywords: predictive control, energy management, machine learning, optimization

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Authors: Jonathan Sahu, Jill Aylott

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Individuals with Autism, Intellectual and Developmental disabilities (AIDD) are one of the most vulnerable groups in society, hampered not only by their own limitations to understand and interact with the wider society, but also societal limitations in perception and understanding. Communication to express their needs and wishes is fundamental to enable such individuals to live and prosper in society. This research project was designed as an organisational case study, in a large secondary health care hospital within the National Health Service (NHS), to assess the quality of care provided to people with AIDD and to review the role of advocacy to reduce health inequalities in these individuals. Methods: The research methodology adopted was as an “insider researcher”. Data collection included both quantitative and qualitative data i.e. a mixed method approach. A semi-structured interview schedule was designed and used to obtain qualitative and quantitative primary data from a wide range of interdisciplinary frontline health care workers to assess their understanding and awareness of systems, processes and evidence based practice to offer a quality service to people with AIDD. Secondary data were obtained from sources within the organisation, in keeping with “Case Study” as a primary method, and organisational performance data were then compared against national benchmarking standards. Further data sources were accessed to help evaluate the effectiveness of different types of advocacy that were present in the organisation. This was gauged by measures of user and carer experience in the form of retrospective survey analysis, incidents and complaints. Results: Secondary data demonstrate near compliance of the Organisation with the current national benchmarking standard (Monitor Compliance Framework). However, primary data demonstrate poor knowledge of the Mental Capacity Act 2005, poor knowledge of organisational systems, processes and evidence based practice applied for people with AIDD. In addition there was poor knowledge and awareness of frontline health care workers of advocacy and advocacy schemes for this group. Conclusions: A significant amount of work needs to be undertaken to improve the quality of care delivered to individuals with AIDD. An operational strategy promoting the widespread dissemination of information may not be the best approach to deliver quality care and optimal patient experience and patient advocacy. In addition, a more robust set of standards, with appropriate metrics, needs to be developed to assess organisational performance which will stand the test of professional and public scrutiny.

Keywords: advocacy, autism, health inequalities, intellectual developmental disabilities, quality of care

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Authors: Cristina Damian, Eduard Malcek, Ana Leahu, Sorina Ropciuc, Andrei Lobiuc

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Given the high rivalry nowadays, the food sector must offer the markets an attractive product, which at the same time has good quality and is safe from health aspects for the consumers. Known for their high content of antioxidant compounds, especially anthocyanins, which proven human health benefits, berries from the Rosaceae family plants have a significantly high level of phytochemicals: phenolic flavonoids, such as anthocyanins, ellagic acid (tannin), quercetin, gallic acid, cyanidin, pelargonidine, catechins, kaempferol and salicylic acid. Colour and bioactive compounds, such as vitamin C and anthocyanins, are important for the attractiveness of berries and their preserved products. The levels of bioactive compounds and sensory properties of the product as it reaches the consumer are dependent on raw material, i.e., berries used, processing, and storage conditions. In this study, four varieties of raspberry jam were analyzed, 3 of them purchased commercially; they were purchased at reasonable prices, precisely to include as large a sample of the consumer population as possible. The fourth assortment was made at home according to the traditional recipe without the addition of sweeteners or preservatives. As for the homemade red raspberry jam, it had a sugar concentration of 64.9%, being the most appreciated of all assortments. The homemade raspberry jam was most appreciated due to the taste and aroma of the product. The SCHWARTAU assortment was chosen in second place by the participants in the study (sensory analysis). The quality/price ratio is also valid this time, finding that a high-quality product will have a higher purchase price. Thus, the study had the role of presenting the preferences of the sample participating in the study by age categories.

Keywords: red raspberry, jam, antioxidant, colour, sensory analysis

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Authors: Richard Mitchell, Robert Mitchell, Thai Duong, Kyungbin Bae, Daegon Kim, Youngsub Lee, Inho Kim, Inho Park, Hyungseok Lee

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Although X-band radar is commonly used to measure the properties of ocean waves, the use of a higher frequency has several advantages, such as increased backscatter coefficient, better Doppler sensitivity, lower power, and a smaller package. A low-power Ku-band radar system was developed to demonstrate these advantages. It is fully coherent, and it interleaves short and long pulses to achieve a transmit duty ratio of 25%, which makes the best use of solid-state amplifiers. The range scales are 2 km, 4 km, and 8 km. The minimum range is 100 m, 200 m, and 400 m for the three range scales, and the range resolution is 4 m, 8 m, and 16 m for the three range scales. Measurements of the significant wave height, wavelength, wave period, and wave direction have been made using traditional 3D-FFT methods. Radar and ultrasonic sensor results collected over an extended period of time at a coastal site in South Korea are presented.

Keywords: measurement of ocean wave parameters, Ku-band radar, coherent radar, compact radar

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Authors: Muhammad Rafi Ullah Khan, Yaodong Guo, Vanee Chonhenchob, Jinjin Pei, Chongxing Huang

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The effect of sodium alginate (1%) based edible coating incorporated natural essential oils; thymol, carvone and carvacrol as antimicrobial agents at different concentrations (0.1, 0.5 and 1.0 %) on the quality changes of fresh-cut pineapple were investigated. Pineapple dipped in distilled water was served as control. After coating, fruit were sealed in a modified atmosphere package (MAP) using high permeable film; and stored at 5 °C. Gas composition in package headspace, color values (L*, a*, b*, C*), TSS, pH, ethanol, browning, and microbial decay were monitored during storage. Oxygen concentration continuously decreased while carbon dioxide concentration inside all packages continuously increased over time. Color parameters (L*, b*, c*) decreased and a* values increased during storage. All essential oils significantly (p ≤ 0.05) prevented microbial growth than control. A significantly higher (p ≤ 0.05) ethanol content was found in the control than in all other treatments. Visible microbial growth, high ethanol, and low color values limited the shelf life to 6 days in control as compared to 9 days in all other treatments. Among all essential oils, thymol at all concentrations maintained the overall quality of the pineapple and could potentially be used commercially in fresh fruit industries for longer storage.

Keywords: essential oils, antibrowning agents, antimicrobial agents, modified atmosphere packaging, microbial decay, pineapple

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Authors: Asaduzzaman Rimon, Pankaj Kumar Jha, Abdullah Al Mansur, Mohammad Mofizul Islam, Nasrin Sultana Juyena, Farida Yeasmin Bari

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This study was conducted to determine the effects of multi-species skim milk based extenders on sperm quality at 5ºC with the advancement of preservation time. Altogether forty ejaculates, 8 ejaculates for each of the 5 home-made semen extenders: cow skim milk (CSM), goat skim milk (GSM), sheep skim milk (SSM), buffalo skim milk (BSM) and commercial dried skim milk (CDSM) were examined for motility, plasma membrane integrity and normal morphology % of sperm at 0, 24, 48, 72, 96 and 120 hours, respectively. Sperm motility was significantly decreased (P < 0.05) with the increase of preservation time. There were no significant difference in motility % among CSM (84.0±1.4, 82.3±2.1), GSM (84.5±1.0, 82.5±0.6) and CDSM (85.0±80.3±1.3) extenders at 0 and 24 hours, respectively. However, the motility in GSM extender was significantly higher than BSM, SSM and CDSM extender at 48, 72, 96 and 120 hours. The plasma membrane integrity % at 0 hour had no significant difference among the extenders. But, the plasma membrane integrity % in GSM (84.3±0.9, 81.8±1.3, 78.0±2.2, 74.8±0.5, 72.0±1.4) and CSM (82.8±0.5, 80.8±1.0, 78.0±1.4, 73.5±1.7, 70.3±0.5) extenders were significantly higher than BSM (81.0±1.4, 76.3±2.5, 72.5±1.7, 63.8±2.5, 54.0±4.6), SSM (78.5±1.5, 75.0±1.6, 71.5±2.4, 64.3±1.7, 56.5±2.4) and CDSM extenders (78.3±2.4, 75.8±3.9, 72.5±3.3, 64.8±1.0, 60.5±3.3) at 24, 48, 72, 96 and 120 hours, respectively. The sperm morphology % had no significant difference at 0 hour among the extenders but were significantly higher in GSM (83.0±0.8, 81.3±1.5, 79.3±1.3, 73.0±2.2, 70.3±1.3) and CSM (81.5±1.7, 79.3±1.5, 75.8±1.5, 70.3±1.3, 66.3±1.5) than BSM (79.0±1.2, 75.0±1.4, 69.5±1.7, 64.5±3.1, 56.8±2.2), SSM (79.8±1.3, 76.8±2.1, 71.3±3.0, 66.0±2.7, 60.3±4.5) and CDSM (80.0±1.6, 77.0±2.2, 72.0±2.5, 66.3±2.5, 62.0±4.0) extenders at 24, 48, 72, 96 and 120 hours, respectively. The motility, plasma membrane integrity and normal morphology % of sperm had shown no significant difference between GSM and CSM but were found to be higher in GSM extenders. In the end, we concluded from the above study that the goat milk based extenders (GSM) had optimum sperm preserving quality. However, further studies are required to validate followed by fertility rate.

Keywords: chilled semen, indigenous ram, multi-species skim milk based extenders, preservation

Procedia PDF Downloads 421

Authors: Chung-Yu Wu, Chia-Chi Chang, Wei-Ming Chen, Pu-Wei Wu, Shih-Fan Chen, Po-Chun Chen

Abstract:

Electrostimulation medical devices for neural diseases require electroactive and biocompatible materials to transmit signals from electrodes to targeting tissues. Protection of surrounding tissues has become a great challenge for long-term implants. In this study, we designed back-end processes with compatible, efficient, and reliable advantages over the current state-of-the-art. We explored a hermetic packaging process with high quality of adhesion and uniformity as the biocompatible devices for long-term implantation. This approach is able to provide both excellent biocompatibility and protection to the biomedical electronic devices by performing conformal coating of biocompatible materials. We successfully developed a packaging process that is capable of exposing the stimulating electrode and cover all other faces of chip with high quality of protection to prevent leakage of devices and body fluid.

Keywords: biocompatible package, medical microelectronics, surface coating, long-term implantation

Procedia PDF Downloads 525

Authors: So-Ra Lee, Myung-Min Oh

Abstract:

Generally, plants growing on the earth are under the influence of natural electric fields and may even require exposure of the electric field to survive. Electric signals have been observed within plants and seem to play an important role on various metabolic processes, but their role is not fully understood. In this study, we attempted to explore the response of plants under external electric fields in kale (Brassica oleracea var. acephala). The plants were hydroponically grown for 28 days in a plant factory. Electric currents at 10, 50 and 100 mA were supplied to nutrient solution for 3 weeks. Additionally, some of the plants were cultivated in a Faraday cage to remove the natural electric field. Kale plants exposed to electric fields had higher fresh weight than the control and plants in Faraday cage. Absence of electric field caused a significant decrease in shoot dry weight and root growth. Leaf area also showed a similar response with shoot fresh weight. Supplying weak electric stimulation enhanced nutritional quality including total phenolic content and antioxidant capacity. This work provides basic information on the effects of electric fields on plants and is a meaningful attempt for developing a new economical technology to increase crop productivity and quality by applying an electric field. This work was supported by Korea Institute of Planning and Evaluation for Technology in Food, Agriculture, Forestry and Fisheries (IPET) through Agriculture, Food and Rural Affairs Research Center Support Program, funded by Ministry of Agriculture, Food and Rural Affairs (MAFRA) (717001-07-02-HD240).

Keywords: electroculture, electric signal, faraday cage, electric field

Procedia PDF Downloads 292

Authors: Richard Ren

Abstract:

Air pollution is a serious danger to international well-being and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.

Keywords: air quality prediction, air pollution, artificial intelligence, machine learning algorithms

Procedia PDF Downloads 130

Authors: Halil Bas, Unal Demiray, Sukru Dursun

Abstract:

Water and ground water pollution at the most of the countries is important problem. Investigation of water pollution source must be carried out to save fresh water. Because fresh water sources are very limited and recent sources are not enough for increasing population of world. In this study, investigation was carried out on pollution factors effecting the quality of the groundwater in Çorum Stream Basin in Turkey. Effect of geological structure of the region and the interaction between the stream and groundwater was researched. For the investigation, stream and groundwater sampling were performed at rainy and dry seasons to see if there is a change on quality parameters. The results were evaluated by the computer programs and then graphics, distribution maps were prepared. Thus, degree of the quality and pollution were tried to understand. According to analysis results, because the results of streams and the ground waters are not so close to each other we can say that there is no interaction between the stream and the groundwater. As the irrigation water, the stream waters are generally in the range between C3S1 region and the ground waters are generally in the range between C3S1 and C4S2 regions according to US Salinity Laboratory Diagram. According to Wilcox diagram stream waters are generally good-permissible and ground waters are generally good permissible, doubtful to unsuitable and unsuitable type. Especially ground waters are doubtful to unsuitable and unsuitable types in dry season. It may be assumed that as the result of relative increase in concentration of salt minerals. Especially samples from groundwater wells bored close to gypsium bearing units have high hardness, electrical conductivity and salinity values. Thus for drinking and irrigation these waters are determined as unsuitable. As a result of these studies, it is understood that the groundwater especially was effected by the lithological contamination rather than the anthropogenic or the other types of pollution. Because the alluvium is covered by the silt and clay lithology it is not affected by the anthropogenic and the other foreign factors. The results of solid waste disposal site leachate indicate that this site would have a risk potential for pollution in the future. Although the parameters did not exceed the maximum dangerous values it does not mean that they will not be dangerous in the future, and this case must be taken into account.

Keywords: Çorum, environment, groundwater, hydrogeology, geology, pollution, quality, stream

Procedia PDF Downloads 504

Authors: Masoumeh Khailghi Sikaroudi, Mohsen Masoodi, Fazad Shidfar, Meghdad Sedaghat

Abstract:

Background: The hypertonicity of internal anal sphincter resting pressure is one of the main reasons for chronic anal fissures. The aim of this study is to assess the effect of oral administration of L-arginine on anal fissure symptom improvement by relaxation of the internal anal sphincter. Method: Seventy-six chronic anal fissure patients (age: 18-65 years) took part in this randomized, double-blind, placebo-controlled trial study from February 2019 to October 2020 at Rasoul-e-Akram Hospital, Tehran, Iran. Participants were allocated into treatment (L-arginine) or placebo groups. They took a 1000 mg capsule three times a day for one month and were followed up at the end of the first and third months after receiving the intervention. Clinical symptoms, anal sphincter resting pressure, and quality of life (QoL) were completed at baseline and the end of the study. Result: The analysis of data was shown significant improvement in bleeding, fissure size, and pain within each group; however, this effect was more seen in the arginine group compared to the control group at the end of the study (P-values<0.001). Following that, a significant increase in QoL was seen just in patients who were treated with arginine (P-value=0.006). Also, the comparison of anal pressures to baseline and between groups at the end of the study showed a significant reduction in sphincter pressure in treated patients (P-value<0.001, =0.049; respectively). Conclusion: Oral administration of 3000 mg L-arginine can heal chronic anal fissures by reducing anal internal sphincter pressure with fewer side effects. However, a long-term study with more follow-up is recommended.

Keywords: L-arginine, anal fissure, sphincter pressure, clinical symptoms, quality of life

Procedia PDF Downloads 72

Authors: Christos Stamopoulos

Abstract:

Nowadays, the technological evolution has brought changes and new requirements not only on human’s life but also on the environment in which they live. Cities have begun to be organized in new ways which comply with contemporary living standards. The aim of this paper was to present the characteristics and to introduce good construction strategies of smart cities around the world. Also, a case study of the city of Kalampaka and its residents was surveyed. More specifically, residents’ knowledge about smart cities and their opinion for future progress was examined. Statistical analysis showed that residents’ knowledge about smart cities was fairly good (48% knew the phrase 'smart city'). However, respondents believe that the appearance of the city of Kalampaka needs improvement in many areas (the 75% are disappointed with the current appearance of the city). Furthermore, regression analysis showed that the value of the environmental sustainability is greatly influenced by the energy saving, as well as, innovation has an impact on the level of quality of life, while older people seem satisfied with administration’s efforts for development.

Keywords: development, economy, environment, governance, quality of life, smart city

Procedia PDF Downloads 337

Authors: Kriangkrai Maneerat, Chutima Prommak

Abstract:

Indoor wireless localization systems have played an important role to enhance context-aware services. Determining the position of mobile objects in complex indoor environments, such as those in multi-floor buildings, is very challenging problems. This paper presents an effective floor estimation algorithm, which can accurately determine the floor where mobile objects located. The proposed algorithm is based on the confidence interval of the summation of online Received Signal Strength (RSS) obtained from the IEEE 802.15.4 Wireless Sensor Networks (WSN). We compare the performance of the proposed algorithm with those of other floor estimation algorithms in literature by conducting a real implementation of WSN in our facility. The experimental results and analysis showed that the proposed floor estimation algorithm outperformed the other algorithms and provided highest percentage of floor accuracy up to 100% with 95-percent confidence interval.

Keywords: floor estimation algorithm, floor determination, multi-floor building, indoor wireless systems

Procedia PDF Downloads 419