Search results for: supports vectors machine

Authors: Jinan Fiaidhi, Sabah Mohammed, Petros Zezos

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Capsule endoscopy (CE) is an established noninvasive diagnostic modality in investigating small bowel disease. CE has a pivotal role in assessing patients with suspected bleeding or identifying evidence of active Crohn's disease in the small bowel. However, CE produces lengthy videos with at least eighty thousand frames, with a frequency rate of 2 frames per second. Gastroenterologists cannot dedicate 8 to 15 hours to reading the CE video frames to arrive at a diagnosis. This is why the issue of analyzing CE videos based on modern artificial intelligence techniques becomes a necessity. However, machine learning, including deep learning, has failed to report robust results because of the lack of large samples to train its neural nets. In this paper, we are describing a thick data approach that learns from a few anchor images. We are using sound datasets like KVASIR and CrohnIPI to filter candidate frames that include interesting anomalies in any CE video. We are identifying candidate frames based on feature extraction to provide representative measures of the anomaly, like the size of the anomaly and the color contrast compared to the image background, and later feed these features to a decision tree that can classify the candidate frames as having a condition like the Crohn's Disease. Our thick data approach reported accuracy of detecting Crohn's Disease based on the availability of ulcer areas at the candidate frames for KVASIR was 89.9% and for the CrohnIPI was 83.3%. We are continuing our research to fine-tune our approach by adding more thick data methods for enhancing diagnosis accuracy.

Keywords: thick data analytics, capsule endoscopy, Crohn’s disease, siamese neural network, decision tree

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Authors: Pauline Calleja, Brooke Alexander

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In 2010 the College of Emergency Nursing Australasia (CENA) undertook sole administration of the Trauma Nursing Program (TNP) across Australia. The original TNP was developed from recommendations by the Review of Trauma and Emergency Services-Victoria. While participant and faculty feedback about the program was positive, issues were identified that were common for industry training programs in Australia. These issues included didactic approaches, with many lectures and little interaction/activity for participants. Participants were not necessarily encouraged to undertake deep learning due to the teaching and learning principles underpinning the course, and thus participants described having to learn by rote, and only gain a surface understanding of principles that were not always applied to their working context. In Australia, a trauma or emergency nurse may work in variable contexts that impact on practice, especially where resources influence scope and capacity of hospitals to provide trauma care. In 2011, a program review was undertaken resulting in major changes to the curriculum, teaching, learning and assessment approaches. The aim was to improve learning including a greater emphasis on pre-program preparation for participants, the learning environment and clinically applicable contextualized outcomes participants experienced. Previously if participants wished to undertake assessment, they were given a take home examination. The assessment had poor uptake and return, and provided no rigor since assessment was not invigilated. A new assessment structure was enacted with an invigilated examination during course hours. These changes were implemented in early 2012 with great improvement in both faculty and participant satisfaction. This presentation reports on a comparison of participant evaluations collected from courses post implementation in 2012 and in 2015 to evaluate if positive changes were sustained. Methods: Descriptive statistics were applied in analyzing evaluations. Since all questions had more than 20% of cells with a count of <5, Fisher’s Exact Test was used to identify significance (p = <0.05) between groups. Results: A total of fourteen group evaluations were included in this analysis, seven CENA TNP groups from 2012 and seven from 2015 (randomly chosen). A total of 173 participant evaluations were collated (n = 81 from 2012 and 92 from 2015). All course evaluations were anonymous, and nine of the original 14 questions were applicable for this evaluation. All questions were rated by participants on a five-point Likert scale. While all items showed improvement from 2012 to 2015, significant improvement was noted in two items. These were in regard to the content being delivered in a way that met participant learning needs and satisfaction with the length and pace of the program. Evaluation of written comments supports these results. Discussion: The aim of redeveloping the CENA TNP was to improve learning and satisfaction for participants. These results demonstrate that initial improvements in 2012 were able to be maintained and in two essential areas significantly improved. Changes that increased participant engagement, support and contextualization of course materials were essential for CENA TNP evolution.

Keywords: emergency nursing education, industry training programs, teaching and learning, trauma education

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Authors: Dija Sulekha

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Nowadays, a good percentage of reported cybercrimes involve the usage of the Internet, directly or indirectly for committing the crime. Usually, Web Browsers leave traces of browsing activities on the host computer’s hard disk, which can be used by investigators to identify internet-based activities of the suspect. But criminals, who involve in some organized crimes, disable browser file generation feature to hide the evidence while doing illegal activities through the Internet. In such cases, even though browser files were not generated in the storage media of the system, traces of recent and ongoing activities were generated in the Physical Memory of the system. As a result, the analysis of Physical Memory Dump collected from the suspect's machine retrieves lots of forensically crucial information related to the browsing history of the Suspect. This information enables the cyber forensic investigators to concentrate on a few highly relevant selected artefacts while doing the Offline Forensics analysis of storage media. This paper addresses the reconstruction of web browsing activities by conducting live forensics to identify searched terms, downloaded files, visited sites, email headers, email ids, etc. from the physical memory dump collected from Windows 10 Systems. Well-known entry points are available for retrieving all the above artefacts except searched terms. The paper describes a novel methodology to retrieve the searched terms from Windows 10 Physical Memory. The searched terms retrieved in this way can be used for doing advanced file and keyword search in the storage media files reconstructed from the file system recovery in offline forensics.

Keywords: browser forensics, digital forensics, live Forensics, physical memory forensics

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Authors: Noelia L. Alchapar, Cláudia C. Pezzuto, Erica N. Correa

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Mitigating urban overheating is key to achieving the environmental and energy sustainability of cities. The management of the optical properties of the materials that make up the urban envelope -roofing, pavement, and facades- constitutes a profitable and effective tool to improve the urban microclimate and rehabilitate urban areas. Each material that makes up the urban envelope has a different capacity to reflect received solar radiation, which alters the fraction of solar radiation absorbed by the city. However, the paradigm of increasing solar reflectance in all areas of the city without distinguishing their relative position within the urban canyon can cause serious problems of overheating and discomfort among its inhabitants. The hypothesis that supports the research postulates that not all reflective technologies that contribute to urban radiative cooling favor the thermal comfort conditions of pedestrians to equal measure. The objective of this work is to determine to what degree the management of the optical properties of the facades modifies outdoor thermal comfort, given that the mitigation potential of materials with high reflectance in facades is strongly conditioned by geographical variables and by the geometric characteristics of the urban profile aspect ratio (H/W). This research was carried out under two climatic contexts, that of the city of Mendoza-Argentina and that of the city of Campinas-Brazil, according to the Köppen climate classification: BWk and Cwa, respectively. Two areas in two different climatic contexts (Mendoza - Argentina and Campinas - Brazil) were selected. Both areas have comparable urban morphology patterns. These areas are located in a region with low horizontal building density and residential zoning. The microclimatic conditions were monitored during the summer period with temperature and humidity fixed sensors inside vial channels. The microclimate model was simulated in ENVI-Met V5. A grid resolution of 3.5 x 3.5 x 3.5m was used for both cities, totaling an area of 145x145x30 grids. Based on the validated theoretical model, ten scenarios were simulated, modifying the height of buildings and the solar reflectivity of facades. The solar reflectivity façades ranges were: low (0.3) and high (0.75). The density scenarios range from 1th to the 5th level. The study scenarios' performance was assessed by comparing the air temperature, physiological equivalent temperature (PET), and thermal climate index (UTCI). As a result, it is observed that the behavior of the materials of the urban outdoor space depends on complex interactions. Many urban environmental factors influence including constructive characteristics, urban morphology, geographic locations, local climate, and so forth. The role of the vertical urban envelope is decisive for the reduction of urban overheating. One of the causes of thermal gain is the multiple reflections within the urban canyon, which affects not only the air temperature but also the pedestrian thermal comfort. One of the main findings of this work leads to the remarkable importance of considering both the urban warming and the thermal comfort aspects of pedestrians in urban mitigation strategies.

Keywords: materials facades, solar reflectivity, thermal comfort, urban cooling

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Authors: Khaled M. Khader, Mamdouh I. Elimy

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Reducing energy consumption became the major concern for all countries of the world during the recent decades. In general, power saving is currently the nominal goal of most industrial countries. It is well known that fossil fuels are the main pillar of development of world countries. Unfortunately, the increased rate of fossil fuel consumption will lead to serious problems caused by an expected depletion of fuels. Moreover, dangerous gases and vapors emission lead to severe environmental problems during fuel burning. Consequently, most engineering sectors especially the mechanical sectors are looking for improving any machine accompanied by reducing its energy consumption. Crank-Rocker planar mechanism is the most applied in mechanical systems. Besides, it is one of the most significant parts of the machines for obtaining the oscillatory motion. The transmission angle of this mechanism can be considered as an optimum value when its extreme values are equally varied around 90°. In addition, the transmission angle plays an important role in decreasing the required driving power and improving the dynamic properties of the mechanism. Hence, appropriate selection of mechanism links lengthens, which assures optimum transmission angle leads to decreasing the driving power. Moreover, mechanism's links manufactured from composite materials afford link's lightweight, which decreases the required driving torque. Furthermore, wear and corrosion problems can be treated through using composite links instead of using metal ones. This paper is dealing with improving the performance of crank-rocker mechanism using composite links due to their flexural elastic modulus values and stiffness in addition to high damping of composite materials.

Keywords: Composite Material, Crank-Rocker Mechanism, Transmission angle, Design techniques, Power Saving

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Authors: Annapurna Basavaraju, Andreas Marn, Franz Heitmeir

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The Advisory Council for Aeronautics Research in Europe (ACARE) is cognizant for the overall reduction of NOx emissions by 80% in its vision 2020. Moreover small turbo engines have higher fuel specific emissions compared to large engines due to their limited combustion chamber size. In order to fulfill these requirements, novel combustion concepts are essential. This motivates to carry out the research on the current state of art, catalytic stabilized combustion chamber using hydrogen in small jet engines which are designed and investigated both numerically and experimentally during this project. Catalytic combustion concepts can also be adopted for low caloric fuels and are therefore not constrained to only hydrogen. However, hydrogen has high heating value and has the major advantage of producing only the nitrogen oxides as pollutants during the combustion, thus eliminating the interest on other emissions such as Carbon monoxides etc. In the present work, the combustion chamber is designed based on the ‘Rich catalytic Lean burn’ concept. The experiments are conducted for the characteristic operating range of an existing engine. This engine has been tested successfully at Institute of Thermal Turbomachinery and Machine Dynamics (ITTM), Technical University Graz. One of the facts that the efficient combustion is a result of proper mixing of fuel-air mixture, considerable significance is given to the selection of appropriate mixer. This led to the design of three diverse configurations of mixers and is investigated experimentally and numerically. Subsequently the best mixer would be equipped in the main combustion chamber and used throughout the experimentation. Furthermore, temperatures and pressures would be recorded at various locations inside the combustion chamber and the exhaust emissions will also be analyzed. The instrumented combustion chamber would be inspected at the engine relevant inlet conditions for nine different sets of catalysts at the Hot Flow Test Facility (HFTF) of the institute.

Keywords: catalytic combustion, gas turbine, hydrogen, mixer, NOx emissions

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Authors: Bruno R. A. Oliveira, Italo V. V. Braga, Jonas P. Reges, Luiz P. O. Santos, Sidney C. Duarte, Emilson R. R. Melo, Auzuir R. Alexandria

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This project aims to building a controlled greenhouse, or for better understanding, a structure where one can maintain a given range of temperature values (°C) coming from radiation emitted by an incandescent light, as previously defined, characterizing as a kind of on-off control and a differential, which is the plotting of temperature versus time graphs assisted by MATLAB software via serial communication. That way it is possible to connect the stove with a computer and monitor parameters. In the control, it was performed using a PIC 16F877A microprocessor which enabled convert analog signals to digital, perform serial communication with the IC MAX232 and enable signal transistors. The language used in the PIC's management is Basic. There are also a cooling system realized by two coolers 12V distributed in lateral structure, being used for venting and the other for exhaust air. To find out existing temperature inside is used LM35DZ sensor. Other mechanism used in the greenhouse construction was comprised of a reed switch and a magnet; their function is in recognition of the door position where a signal is sent to a buzzer when the door is open. Beyond it exist LEDs that help to identify the operation which the stove is located. To facilitate human-machine communication is employed an LCD display that tells real-time temperature and other information. The average range of design operating without any major problems, taking into account the limitations of the construction material and structure of electrical current conduction, is approximately 65 to 70 ° C. The project is efficient in these conditions, that is, when you wish to get information from a given material to be tested at temperatures not as high. With the implementation of the greenhouse automation, facilitating the temperature control and the development of a structure that encourages correct environment for the most diverse applications.

Keywords: greenhouse, microcontroller, temperature, control, MATLAB

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Authors: Opeyemi Atiba-Oyewo, Maurice S. Onya, Christian Wolkersdorfer

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Nanostructure formation and characterization of eco-friendly banana peels nanosorbent are thoroughly described in this paper. The transformation of material during mechanical milling to enhance certain properties such as changes in microstructure and surface area to solve the current problems involving water pollution and water quality were studied. The mechanical milling was employed using planetary continuous milling machine and ethanol as process control agent, the sample were taken at time interval between 10 h to 30 h to examine the structural changes. The samples were characterised by X-ray diffraction (XRD), scanning electron microscopy (SEM), Fourier transform infra-red (FTIR), Transmission electron microscopy (TEM) and Brunauer Emmett and teller (BET). Results revealed that the three typical structures with different grain-size, lattice strain and shapes were observed, and the deformation mechanisms in these structures were found to be different, further particles fracturing results to surface area increment which was confirmed by Brunauer Emmett and teller (BET) analysis. X-ray diffraction (XRD) shows high densities of dislocations in large crystallites, implying that dislocation slip is the dominant deformation mechanism. Scanning electron microscopy revealed the morphological properties of the materials at different milling time, nanostructure of the particles and fibres were confirmed by Transmission electron microscopy and FT-IR identified the functional groups responsible for its capacity to coordinate and remove metal ions, such as the carboxylic and amine groups at absorption bands of 1730 and 889 cm-1, respectively. However, the choice of this sorbent material for the sorption of any contaminants will depend on the composition of the effluent to be treated.

Keywords: banana peels, eco-friendly, mechanical milling, nanosorbent, nanostructure water quality

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Authors: Wu Peng, Anders Liljerehn, Martin Magnevall

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In metal cutting, tool wear gradually changes the micro geometry of the cutting edge. Today there is a significant gap in understanding the impact these geometrical changes have on the cutting forces which governs tool deflection and heat generation in the cutting zone. Accurate models and understanding of the interaction between the work piece and cutting tool leads to improved accuracy in simulation of the cutting process. These simulations are useful in several application areas, e.g., optimization of insert geometry and machine tool monitoring. This study aims to develop an extended Kienzle force model to account for the effect of rake angle variations and tool flank wear have on the cutting forces. In this paper, the starting point sets from cutting force measurements using orthogonal turning tests of pre-machined flanches with well-defined width, using triangular coated inserts to assure orthogonal condition. The cutting forces have been measured by dynamometer with a set of three different rake angles, and wear progression have been monitored during machining by an optical measuring collaborative robot. The method utilizes the measured cutting forces with the inserts flank wear progression to extend the mechanistic cutting forces model with flank wear as an input parameter. The adapted cutting forces model is validated in a turning process with commercial cutting tools. This adapted cutting forces model shows the significant capability of prediction of cutting forces accounting for tools flank wear and different-rake-angle cutting tool inserts. The result of this study suggests that the nonlinear effect of tools flank wear and interaction between the work piece and the cutting tool can be considered by the developed cutting forces model.

Keywords: cutting force, kienzle model, predictive model, tool flank wear

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Authors: Valentina A. Mikhailova, Serguei V. Feskov, Anatoly I. Ivanov

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In the last decade the nonequilibrium charge transfer have attracted considerable interest from the scientific community. Examples of such processes are the charge recombination in excited donor-acceptor complexes and the intramolecular electron transfer from the second excited electronic state. In these reactions the charge transfer proceeds predominantly in the nonequilibrium mode. In the excited donor-acceptor complexes the nuclear nonequilibrium is created by the pump pulse. The intramolecular electron transfer from the second excited electronic state is an example where the nuclear nonequilibrium is created by the forward electron transfer. The kinetics of these nonequilibrium reactions demonstrate a number of peculiar properties. Most important from them are: (i) the absence of the Marcus normal region in the free energy gap law for the charge recombination in excited donor-acceptor complexes, (ii) extremely low quantum yield of thermalized charge separated state in the ultrafast charge transfer from the second excited state, (iii) the nonexponential charge recombination dynamics in excited donor-acceptor complexes, (iv) the dependence of the charge transfer rate constant on the excitation pulse frequency. This report shows that most of these kinetic features can be well reproduced in the framework of stochastic point-transition multichannel model. The model involves an explicit description of the nonequilibrium excited state formation by the pump pulse and accounts for the reorganization of intramolecular high-frequency vibrational modes, for their relaxation as well as for the solvent relaxation. The model is able to quantitatively reproduce complex nonequilibrium charge transfer kinetics observed in modern experiments. The interpretation of the nonequilibrium effects from a unified point of view in the terms of the multichannel point transition stochastic model allows to see similarities and differences of electron transfer mechanism in various molecular donor-acceptor systems and formulates general regularities inherent in these phenomena. The nonequilibrium effects in photoinduced ultrafast charge transfer which have been studied for the last 10 years are analyzed. The methods of suppression of the ultrafast charge recombination, similarities and dissimilarities of electron transfer mechanism in different molecular donor-acceptor systems are discussed. The extremely low quantum yield of the thermalized charge separated state observed in the ultrafast charge transfer from the second excited state in the complex consisting of 1,2,4-trimethoxybenzene and tetracyanoethylene in acetonitrile solution directly demonstrates that its effectiveness can be close to unity. This experimental finding supports the idea that the nonequilibrium charge recombination in the excited donor-acceptor complexes can be also very effective so that the part of thermalized complexes is negligible. It is discussed the regularities inherent to the equilibrium and nonequilibrium reactions. Their fundamental differences are analyzed. Namely the opposite dependencies of the charge transfer rates on the dynamical properties of the solvent. The increase of the solvent viscosity results in decreasing the thermal rate and vice versa increasing the nonequilibrium rate. The dependencies of the rates on the solvent reorganization energy and the free energy gap also can considerably differ. This work was supported by the Russian Science Foundation (Grant No. 16-13-10122).

Keywords: Charge recombination, higher excited states, free energy gap law, nonequilibrium

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Authors: K. A. D. D. Kuruppu, R. M. De Silva, K. M. N. De Silva

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This research work was based on developing a solar responsive aircraft window panel which can be used as a self-cleaning surface and also a surface which degrade Volatile Organic compounds (VOC) available in the aircraft cabin areas. Further, this surface has the potential of harvesting energy from Solar. The transparent inorganic nano sol solution was prepared. The obtained sol solution was characterized using X-ray diffraction, Particle size analyzer and FT-IR. The existing nano material which shows the similar characteristics was also used to compare the efficiencies with the newly prepared nano sol. Nano sol solution was coated on cleaned four aircraft window pieces separately using a spin coater machine. The existing nano material was dissolved and prepared a solution having the similar concentration as nano sol solution. Pre-cleaned four aircraft window pieces were coated with this solution and the rest cleaned four aircraft window pieces were considered as control samples. The control samples were uncoated from anything. All the window pieces were allowed to dry at room temperature. All the twelve aircraft window pieces were uniform in all the factors other than the type of coating. The surface morphologies of the samples were analyzed using SEM. The photocatalytic degradation of VOC was determined after incorporating gas of Toluene to each sample followed by the analysis done by UV-VIS spectroscopy. The self- cleaning capabilities were analyzed after adding of several types of stains on the window pieces. The self-cleaning property of each sample was analyzed using UV-VIS spectroscopy. The highest photocatalytic degradation of Volatile Organic compound and the highest photocatalytic degradation of stains were obtained for the samples which were coated by the nano sol solution. Therefore, the experimental results clearly show that there is a potential of using this nano sol in aircraft window pieces which favors the self-cleaning property as well as efficient photocatalytic degradation of VOC gases. This will ensure safer environment inside aircraft cabins.

Keywords: aircraft, nano, smart windows, solar

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Authors: Md. Wasiul Islam, Md. Jamius Shams Sowrov

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The Sundarbans is the largest single tract of mangrove forest in the world. This is located in the southwest corner of Bangladesh. This is a unique ecosystem which is a great breeding and nursing ground for a great biodiversity. It supports the livelihood of about 3.5 million coastal dwellers and also protects the coastal belt and inland areas from various natural calamities. Historically, the management of the Sundarbans was controlled by the Bangladesh Forest Department following top-down approach without the involvement of local communities. Such fence and fining-based blue-print approach was not effective to protect the forest which caused Sundarbans to degrade severely in the recent past. Fifty percent of the total tree cover has been lost in the last 30 years. Therefore, local multi-stakeholder based bottom-up co-management approach was introduced at some of the parts of the Sundarbans in 2006 to improve the biodiversity status by enhancing the protection level of the forest. Various co-management organizations were introduced under co-management approach where the local community people could actively involve in various activities related to the management and welfare of the Sundarbans including the decision-making process to achieve the goal. From this backdrop, the objective of the study was to assess the performance of co-management organizations to facilitate sustainable management of the Sundarbans mangrove forests. The qualitative study followed face-to-face interview to collect data using two sets of semi-structured questionnaires. A total of 40 respondents participated in the research that was from eight villagers under two forest ranges. 32 representatives from the local communities as well as 8 official representatives involved in co-management approach were interviewed using snowball sampling technique. The study shows that the co-management approach improved governance system of the Sundarbans through active participation of the local community people and their interactions with the officials via the platform of co-management organizations. It facilitated accountability and transparency system to some extent through following some formal and informal rules and regulations. It also improved the power structure of the management process by fostering local empowerment process particularly the women. Moreover, people were able to learn from their interactions with and within the co-management organizations as well as interventions improved environmental awareness and promoted social learning. The respondents considered good governance as the most important factor for achieving the goal of sustainable management and biodiversity conservation of the Sundarbans. The success of co-management planning process also depends on the active and functional participation of different stakeholders including the local communities where co-management organizations were considered as the most functional platform. However, the governance system was also facing various challenges which resulted in barriers to the sustainable management of the Sundarbans mangrove forest. But still there were some members involved in illegal forest operations and created obstacles against sustainable management of the Sundarbans. Respondents recommended greater patronization from the government, financial and logistic incentives for alternative income generation opportunities with effective participatory monitoring and evaluation system to improve sustainable management of the Sundarbans.

Keywords: Bangladesh, co-management approach, co-management organizations, governance, Sundarbans, sustainable management

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Authors: Drishti Sharma, Mona Duggal

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Background: WhatsApp can serve as a cost-effective, scalable, convenient, and popular medium for public health management related communication in the developing world where the existing system of communication is top-down and slow. The product supports sending and receiving a variety of media: text, photos, videos, documents, and location, as well as voice/video calls. With growing number of users of smartphones and improving access and penetration of internet, the scope of information technology remains immense in resolving the hurdles faced by traditional public health system. Poor infrastructure, gap in digital literacy, faulty documentation, strict organizational hierarchy and slow movement of information across desks and offices- all these, make WhatsApp an efficient prospect to complement the existing system for communication, feedback and leadership for public health system in India. Objective: This study investigates the benefits, challenges and limitations associated with WhatsApp usage as a public health management tool. Methods: The study was conducted within the Chandigarh Union Territory. We used a qualitative approach and conducted individual semi-structured interviews and group interviews (n = 10). Participants included medical officers (n 20), Program managers (n = 4), academicians (n=2) and administrators (n=2). Thematic and content qualitative analyses were conducted. Message log of the WhatsApp group of one of the health program was assessed. Results: Medical Officers said that WhatsApp helped them remain in touch with the program officer. They could easily give feedback and highlight those challenges which needed immediate intervention from the program managers, hence they felt supported. Also, the application helped them share pictures of their activities (meetings and field activities) with the group which they thought inspired others and gave themselves immense satisfaction. Also, it helped build stronger relationships and better coordination among themselves, the same being important in team events. For program managers, it had become a portal for coordinating large scale campaigns. Its reach and the fact that the feedback is real-time make WhatsApp ideal for district level events. Though the easy informal connectivity made them answerable to their staff but it also provided them with flexibility in operations. It turned out to be an important portal for sharing outcome and goals related feedback (both positive and negative) to the team. To be sure, using WhatsApp for the purpose of public health program presents considerable challenges, including technological barriers, organizational challenges, gender issues, confidentiality concerns and unplanned aftereffects. Nevertheless, its advantages in a low-cost setting make it an efficient alternative. Conclusion: WhatsApp has become an integral part of our lives. Use of this app for public health program management within closed groups looks promising and useful. At the same time, addressing the challenges involved would make its usage safer.

Keywords: communication, mobile technology, public health management, WhatsApp

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Authors: Ramkumar R., Gaurav Shinde, Pratik Shroff, Sachin Kumar Jain, Nagesh Walke

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Advancements in electric vehicles have significantly reduced the powertrain noise and moving components of vehicles. As a result, in-cab noises have become more noticeable to passengers inside the car. To ensure a comfortable ride for drivers and other passengers, it has become crucial to eliminate undesirable component noises during the development phase. Standard practices are followed to identify the severity of noises based on subjective ratings, but it can be a tedious process to identify the severity of each development sample and make changes to reduce it. Additionally, the severity rating can vary from jury to jury, making it challenging to arrive at a definitive conclusion. To address this, an automotive component was identified to evaluate squeak and rattle noise issue. Physical tests were carried out for random and sine excitation profiles. Aim was to subjectively assess the noise using jury rating method and objectively evaluate the same by measuring the noise. Suitable jury evaluation method was selected for the said activity, and recorded sounds were replayed for jury rating. Objective data sound quality metrics viz., loudness, sharpness, roughness, fluctuation strength and overall Sound Pressure Level (SPL) were measured. Based on this, correlation co-efficients was established to identify the most relevant sound quality metrics that are contributing to particular identified noise issue. Regression analysis was then performed to establish the correlation between subjective and objective data. Mathematical model was prepared using artificial intelligence and machine learning algorithm. The developed model was able to predict the subjective rating with good accuracy.

Keywords: BSR, noise, correlation, regression

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Authors: Jeaha Yang, Ahmed Khan, Donna L. Rodela, Mohammed A. Qaudeer

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Traditional supply chain silos still exist today due to the difficulty of establishing trust between various partners and technological barriers across industries. Companies lose opportunities and revenue and inadvertently make poor business decisions resulting in further challenges. Blockchain technology can bring a new level of transparency through sharing information with a distributed ledger in a decentralized manner that creates a basis of trust for business. Blockchain is a loosely coupled, hub-style communication network in which trading partners can work indirectly with each other for simpler integration, but they work together through the orchestration of their supply chain operations under a coherent process that is developed jointly. A Blockchain increases efficiencies, lowers costs, and improves interoperability to strengthen and automate the supply chain management process while all partners share the risk. Blockchain ledger is built to track inventory lifecycle for supply chain transparency and keeps a journal of inventory movement for real-time reconciliation. State design patterns are used to capture the life cycle (behavior) of inventory management as a state machine for a common, transparent and coherent process which creates an opportunity for trading partners to become more responsive in terms of changes or improvements in process, reconcile discrepancies, and comply with internal governance and external regulations. It enables end-to-end, inter-company visibility at the unit level for more accurate demand planning with better insight into order fulfillment and replenishment.

Keywords: supply chain management, inventory trace-ability, perpetual inventory system, inventory lifecycle, blockchain, inventory consignment, supply chain transparency, digital thread, demand planning, hyper ledger fabric

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Authors: António J. Gano, Carmen Rangel

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Currently, electric energy storage systems for stationary applications have known an increasing interest, namely with the integration of local renewable energy power sources into energy communities. Li-ion batteries are considered the leading electric storage devices to achieve this integration, and Battery Management Systems (BMS) are decisive for their control and optimum performance. In this work, the advancement of a smart BMS (sBMS) prototype with a modular distributed topology is described. The system, still under development, has a distributed architecture with modular characteristics to operate with different battery pack topologies and charge capacities, integrating adaptive algorithms for functional state real-time monitoring and management of multicellular Li-ion batteries, and is intended for application in the context of a local energy community fed by renewable energy sources. This sBMS system includes different developed hardware units: (1) Cell monitoring units (CMUs) for interfacing with each individual cell or module monitoring within the battery pack; (2) Battery monitoring and switching unit (BMU) for global battery pack monitoring, thermal control and functional operating state switching; (3) Main management and local control unit (MCU) for local sBMS’s management and control, also serving as a communications gateway to external systems and devices. This architecture is fully expandable to battery packs with a large number of cells, or modules, interconnected in series, as the several units have local data acquisition and processing capabilities, communicating over a standard CAN bus and will be able to operate almost autonomously. The CMU units are intended to be used with Li-ion cells but can be used with other cell chemistries, with output voltages within the 2.5 to 5 V range. The different unit’s characteristics and specifications are described, including the different implemented hardware solutions. The developed hardware supports both passive and active methods for charge equalization, considered fundamental functionalities for optimizing the performance and the useful lifetime of a Li-ion battery package. The functional characteristics of the different units of this sBMS system, including different process variables data acquisition using a flexible set of sensors, can support the development of custom algorithms for estimating the parameters defining the functional states of the battery pack (State-of-Charge, State-of-Health, etc.) as well as different charge equalizing strategies and algorithms. This sBMS system is intended to interface with other systems and devices using standard communication protocols, like those used by the Internet of Things. In the future, this sBMS architecture can evolve to a fully decentralized topology, with all the units using Wi-Fi protocols and integrating a mesh network, making unnecessary the MCU unit. The status of the work in progress is reported, leading to conclusions on the system already executed, considering the implemented hardware solution, not only as fully functional advanced and configurable battery management system but also as a platform for developing custom algorithms and optimizing strategies to achieve better performance of electric energy stationary storage devices.

Keywords: Li-ion battery, smart BMS, stationary electric storage, distributed BMS

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Authors: K. Sathishkumar, V. Thiagarasu

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Due to recent advances in DNA microarray technology, it is now feasible to obtain gene expression profiles of tissue samples at relatively low costs. Many scientists around the world use the advantage of this gene profiling to characterize complex biological circumstances and diseases. Microarray techniques that are used in genome-wide gene expression and genome mutation analysis help scientists and physicians in understanding of the pathophysiological mechanisms, in diagnoses and prognoses, and choosing treatment plans. DNA microarray technology has now made it possible to simultaneously monitor the expression levels of thousands of genes during important biological processes and across collections of related samples. Elucidating the patterns hidden in gene expression data offers a tremendous opportunity for an enhanced understanding of functional genomics. However, the large number of genes and the complexity of biological networks greatly increase the challenges of comprehending and interpreting the resulting mass of data, which often consists of millions of measurements. A first step toward addressing this challenge is the use of clustering techniques, which is essential in the data mining process to reveal natural structures and identify interesting patterns in the underlying data. This work presents an analysis of several clustering algorithms proposed to deals with the gene expression data effectively. The existing clustering algorithms like Support Vector Machine (SVM), K-means algorithm and evolutionary algorithm etc. are analyzed thoroughly to identify the advantages and limitations. The performance evaluation of the existing algorithms is carried out to determine the best approach. In order to improve the classification performance of the best approach in terms of Accuracy, Convergence Behavior and processing time, a hybrid clustering based optimization approach has been proposed.

Keywords: microarray technology, gene expression data, clustering, gene Selection

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Authors: Gaurav D. Sonawane, Vikas G. Sargade

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The present investigation is a study of the effect of advanced Physical Vapor Deposition (PVD) coatings on cutting temperature residual stresses and surface roughness during Duplex Stainless Steel (DSS) 2205 turning. Austenite stabilizers like nickel, manganese, and molybdenum reduced the cost of DSS. Surface Integrity (SI) plays an important role in determining corrosion resistance and fatigue life. Resistance to various types of corrosion makes DSS suitable for applications with critical environments like Heat exchangers, Desalination plants, Seawater pipes and Marine components. However, lower thermal conductivity, poor chip control and non-uniform tool wear make DSS very difficult to machine. Cemented carbide tools (M grade) were used to turn DSS in a dry environment. AlTiN and AlTiCrN coatings were deposited using advanced PVD High Pulse Impulse Magnetron Sputtering (HiPIMS) technique. Experiments were conducted with cutting speed of 100 m/min, 140 m/min and 180 m/min. A constant feed and depth of cut of 0.18 mm/rev and 0.8 mm were used, respectively. AlTiCrN coated tools followed by AlTiN coated tools outperformed uncoated tools due to properties like lower thermal conductivity, higher adhesion strength and hardness. Residual stresses were found to be compressive for all the tools used for dry turning, increasing the fatigue life of the machined component. Higher cutting temperatures were observed for coated tools due to its lower thermal conductivity, which results in very less tool wear than uncoated tools. Surface roughness with uncoated tools was found to be three times higher than coated tools due to lower coefficient of friction of coating used.

Keywords: cutting temperature, DSS2205, dry turning, HiPIMS, surface integrity

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Authors: Maryam Shirmohammadi, Prasad K. D. V. Yarlagadda, YuanTong Gu

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The mechanical damage on the agricultural crop during and after harvesting can create high volume of damage on tissue. Uniaxial compression and tensile loading were performed on flesh and peel samples of pumpkin. To investigate the structural changes on the tissue, Scanning Electron Microscopy (SEM) was used to capture the cellular structure change before and after loading on tissue for tensile, compression and indentation tests. To obtain required mechanical properties of tissue for the finite element analysis (FEA) model, laser measurement sensors were used to record the lateral displacement of tissue under the compression loading. Uniaxial force versus deformation data were recorded using Universal Testing Machine for both tensile and compression tests. The experimental Results were employed to develop a material model with failure criteria. The results obtained by the simulation were compared with those obtained by experiments. Note that although modelling food materials’ behaviour is not a new concept however, majority of previous studies focused on elastic behaviour and damages under linear limit, this study, however, has developed FEA models for tensile and compressive loading of pumpkin flesh and peel samples using, as the first study, both elastic and elasto-plastic material types. In addition, pumpkin peel and flesh tissues were considered as two different materials with different properties under mechanical loadings. The tensile and compression loadings were used to develop the material model for a composite structure for FEA model of mechanical peeling of pumpkin as a tough skinned vegetable.

Keywords: compressive and tensile response, finite element analysis, poisson’s ratio, elastic modulus, elastic and plastic response, rupture and bio-yielding

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Authors: Irene Yi

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Machine learning, natural language processing, and neural network models of language are becoming more and more prevalent in the fields of technology and linguistics today. Training data for machines are at best, large corpora of human literature and at worst, a reflection of the ugliness in society. Machines have been trained on millions of human books, only to find that in the course of human history, derogatory and sexist adjectives are used significantly more frequently when describing females in history and literature than when describing males. This is extremely problematic, both as training data, and as the outcome of natural language processing. As machines start to handle more responsibilities, it is crucial to ensure that they do not take with them historical sexist and misogynistic notions. This paper gathers data and algorithms from neural network models of language having to deal with syntax, semantics, sociolinguistics, and text classification. Results are significant in showing the existing intentional and unintentional misogynistic notions used to train machines, as well as in developing better technologies that take into account the semantics and syntax of text to be more mindful and reflect gender equality. Further, this paper deals with the idea of non-binary gender pronouns and how machines can process these pronouns correctly, given its semantic and syntactic context. This paper also delves into the implications of gendered grammar and its effect, cross-linguistically, on natural language processing. Languages such as French or Spanish not only have rigid gendered grammar rules, but also historically patriarchal societies. The progression of society comes hand in hand with not only its language, but how machines process those natural languages. These ideas are all extremely vital to the development of natural language models in technology, and they must be taken into account immediately.

Keywords: gendered grammar, misogynistic language, natural language processing, neural networks

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Authors: Irina-Emily Hansen, Ola Jon Mork

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The European economic growth strategy and supporting it framework for research and innovation highlight the importance of nurturing new open innovation in order to strengthen Europe’s competitiveness. One of the main approaches to enhance innovation in European society is the Triple Helix model that centres on science- industry collaboration where the universities are assigned the managerial role. In spite of the defined collaboration strategy, the collaboration between academics and in-dustry in Europe has still many challenges. Many of them are explained by culture difference: academic culture aims towards scientific knowledge, while businesses are oriented towards pro-duction and profitable results; also execution of collaborative projects is seen differently by part-ners involved. That proves that traditional management strategies applied to collaboration between researchers and businesses are not effective. There is a need for dynamic strategies that can support the interaction between researchers and industry intensifying knowledge co-creation and contributing to development of national innovation system (NIS) by incorporating individual, organizational and inter-organizational learning. In order to find a good subject to follow, the researchers of a given paper have investigated one of the most rapidly developing knowledge-based, innovation society, Singapore. Singapore does not dispose much land- or sea- resources that normally provide income for any country. Therefore, Singapore was forced to think differently and build society on resources that are available: talented people and knowledge. Singapore has during the last twenty years developed attracting high rated university camps, research institutions and leading industrial companies from all over the world. This article elucidates and elaborates Singapore’s national innovation strategies from Knowledge Management perspective. The research is done on the variety of organizations that enable and support knowledge development in this state: governmental research and development (R&D) centers in universities, private talent incubators for entrepreneurs, and industrial companies with own R&D departments. The research methods are based on presentations, documents, and visits at a number of universities, research institutes, innovation parks, governmental institutions, industrial companies and innovation exhibitions in Singapore. In addition, a literature review of science articles is made regarding the topic. The first finding is that objectives of collaboration between researchers, entrepreneurs and industry in Singapore correspond primary goals of the state: knowledge- and economy growth. There are common objectives for all stakeholders on all national levels. The second finding is that Singapore has enabled system on a national level that supports innovation the entire way from fostering or capturing the new knowledge, providing knowledge exchange and co-creation to application of it in real-life. The conclusion is that innovation means not only new idea, but also the enabling mechanism for its execution and the marked-oriented approach in order that new knowledge can be absorbed in society. The future research can be done with regards to application of Singapore knowledge management strategy in innovation to European countries.

Keywords: knowledge management strategy, national innovation system, research industry and business collaboration, knowledge enabling

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Authors: Shuyu Zhang

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The waterfront historical district, as a type of historical districts on the verge of waters such as the sea, lake, and river, have a relatively special urban form. In the past preservation and renewal of traditional historic districts, there have been many discussions on the land range, and the waterfront and marginal spaces are easily overlooked. However, the waterfront space of the historic districts, as a cultural landscape heritage combining historical buildings and landscape elements, has strong ecological and sustainable values. At the same time, Suzhou and Venice, as sister water cities in history, have more waterfront spaces that can be compared in urban form and other levels. Therefore, this paper focuses on the waterfront historic districts in Venice and Suzhou, establishes quantitative evaluation indicators for environmental perception, makes analogies, and promotes the renewal and activation of the entire historical district by improving the spatial quality and vitality of the waterfront area. First, this paper uses multi-source data for analysis, such as Baidu Maps and Google Maps API to crawl the street view of the waterfront historic districts, uses machine learning algorithms to analyze the proportion of cultural landscape elements such as green viewing rate in the street view pictures, and uses space syntax software to make quantitative selectivity analysis, so as to establish environmental perception evaluation indicators for the waterfront historic districts. Finally, by comparing and summarizing the waterfront historic districts in Venice and Suzhou, it reveals their similarities and differences, characteristics and conclusions, and hopes to provide a reference for the heritage preservation and renewal of other waterfront historic districts.

Keywords: waterfront historical district, cultural landscape, perception, multi-source Data

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Authors: Lucilla Crosta, Anthony Edwards

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Companies and the market place nowadays struggle to find employees with adequate skills in relation to anticipated growth of their businesses. At least half of workers will need to undertake some form of up-skilling process in the next five years in order to remain aligned with the requests of the market . In order to meet these challenges, there is a clear need to explore the potential uses of AI (artificial Intelligence) based tools in assessing transversal skills (critical thinking, communication and soft skills of different types in general) of workers and adult students while empowering them to develop those same skills in a reliable trustworthy way. Companies seek workers with key transversal skills that can make a difference between workers now and in the future. However, critical thinking seems to be the one of the most imprtant skill, bringing unexplored ideas and company growth in business contexts. What employers have been reporting since years now, is that this skill is lacking in the majority of workers and adult students, and this is particularly visible trough their writing. This paper investigates how critical thinking and communication skills are currently developed in Higher Education environments through use of AI tools at postgraduate levels. It analyses the use of a branch of AI namely Machine Learning and Big Data and of Neural Network Analysis. It also examines the potential effect the acquisition of these skills through AI tools and what kind of effects this has on employability This paper will draw information from researchers and studies both at national (Italy & UK) and international level in Higher Education. The issues associated with the development and use of one specific AI tool Edulai, will be examined in details. Finally comparisons will be also made between these tools and the more recent phenomenon of Chat GPT and forthcomings and drawbacks will be analysed.

Keywords: critical thinking, artificial intelligence, higher education, soft skills, chat GPT

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Authors: Nadia Allouache, Mohamed Belmedani

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Energy source is a sustainable, totally inexhaustible and environmentally friendly alternative to the fossil fuels available. It is a renewable and economical energy that can be harnessed sustainably over the long term and thus stabilizes energy costs. Solar cooling technologies have been developed to decrease the augmentation electricity consumption for air conditioning and to displace the peak load during hot summer days. A numerical analysis of thermal and solar performances of an annular finned adsorber, which is the most important component of the adsorption solar refrigerating system, is considered in this work. Different adsorbent/adsorbate pairs, such as activated carbon AC35/methanol, activated carbon AC35/ethanol, and activated carbon BPL/Ammoniac, are undertaken in this study. The modeling of the adsorption cooling machine requires the resolution of the equation describing the energy and mass transfer in the tubular finned adsorber. The Wilson and Dubinin- Astakhov models of the solid-adsorbate equilibrium are used to calculate the adsorbed quantity. The porous medium and the fins are contained in the annular space, and the adsorber is heated by solar energy. Effects of key parameters on the adsorbed quantity and on the thermal and solar performances are analysed and discussed. The AC35/methanol pair is the best pair compared to BPL/Ammoniac and AC35/ethanol pairs in terms of system performance. The system performances are sensitive to the fin geometry. For the considered data measured for clear type days of July 2023 in Algeria and Morocco, the performances of the cooling system are very significant in Algeria.

Keywords: activated carbon AC35-methanol pair, activated carbon AC35-ethanol pair, activated carbon BPL-ammoniac pair, annular finned adsorber, performance coefficients, numerical analysis, solar cooling system

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Authors: Drew Commandeur, Ryan Brodie, Sandra Hundza, Marc Klimstra

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The amplitude of raw electromyography (EMG) is affected by recording conditions and often requires normalization to make meaningful comparisons. Bioelectric methods normalize with an EMG signal recorded during a standardized task or from the experimental protocol itself, while biomechanical methods often involve measurements with an additional sensor such as a force transducer. Common bioelectric normalization techniques for treadmill walking include maximum voluntary isometric contraction (MVIC), dynamic EMG peak (EMGPeak) or dynamic EMG mean (EMGMean). There are several concerns with using MVICs to normalize EMG, including poor reliability and potential discomfort. A limitation of bioelectric normalization techniques is that they could result in a misrepresentation of the absolute magnitude of force generated by the muscle and impact the interpretation of EMG between functionally disparate groups. Additionally, methods that normalize to EMG recorded during the task may eliminate some real inter-individual variability due to biological variation. This study compared biomechanical and bioelectric EMG normalization techniques during treadmill walking to assess the impact of the normalization method on the functional interpretation of EMG data. For the biomechanical method, we normalized EMG to a target torque (EMGTS) and the bioelectric methods used were normalization to the mean and peak of the signal during the walking task (EMGMean and EMGPeak). The effect of normalization on muscle activation pattern, EMG amplitude, and inter-individual variability were compared between disparate cohorts of OLD (76.6 yrs N=11) and YOUNG (26.6 yrs N=11) adults. Participants walked on a treadmill at a self-selected pace while EMG was recorded from the right lower limb. EMG data from the soleus (SOL), medial gastrocnemius (MG), tibialis anterior (TA), vastus lateralis (VL), and biceps femoris (BF) were phase averaged into 16 bins (phases) representing the gait cycle with bins 1-10 associated with right stance and bins 11-16 with right swing. Pearson’s correlations showed that activation patterns across the gait cycle were similar between all methods, ranging from r =0.86 to r=1.00 with p<0.05. This indicates that each method can characterize the muscle activation pattern during walking. Repeated measures ANOVA showed a main effect for age in MG for EMGPeak but no other main effects were observed. Interactions between age*phase of EMG amplitude between YOUNG and OLD with each method resulted in different statistical interpretation between methods. EMGTS normalization characterized the fewest differences (four phases across all 5 muscles) while EMGMean (11 phases) and EMGPeak (19 phases) showed considerably more differences between cohorts. The second notable finding was that coefficient of variation, the representation of inter-individual variability, was greatest for EMGTS and lowest for EMGMean while EMGPeak was slightly higher than EMGMean for all muscles. This finding supports our expectation that EMGTS normalization would retain inter-individual variability which may be desirable, however, it also suggests that even when large differences are expected, a larger sample size may be required to observe the differences. Our findings clearly indicate that interpretation of EMG is highly dependent on the normalization method used, and it is essential to consider the strengths and limitations of each method when drawing conclusions.

Keywords: electromyography, EMG normalization, functional EMG, older adults

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Authors: Rana Parween, Rob Marchant

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With the continued loss of global biodiversity despite the application of modern conservation techniques, it has become crucial to investigate non-conventional methods. Accelerated destruction of ecosystems due to altered land use, climate change, cultural and social change, necessitates the exploration of society-biodiversity attitudes and links. While the loss of species and their extinction is a well-known and well-documented process that attracts much-needed attention from researchers, academics, government and non-governmental organizations, the loss of traditional ecological knowledge and practices is more insidious and goes unnoticed. The growing availability of 'indirect experiences' such as the internet and media are leading to a disaffection towards nature and the 'Extinction of Experience'. Exacerbated by the lack of documentation of traditional practices and skills, there is the possibility for the 'extinction' of traditional practices and skills before they are fully recognized and captured. India, as a mega-biodiverse country, is also known for its historical conservation strategies entwined in traditional beliefs. Indigenous communities hold skillsets, knowledge, and traditions that have accumulated over multiple generations and may play an important role in conserving biodiversity today. This study explores the differences in knowledge and attitudes towards conserving biodiversity, of three different stakeholder groups living around Jim Corbett National Park, based on their age, traditions, and association with the protected area. A triangulation designed multi-strategy investigation collected qualitative and quantitative data through a questionnaire survey of village elders, the general public, and forest officers. Following an inductive approach to analyzing qualitative data, the thematic content analysis was followed. All coding and analysis were completed using NVivo 11. Although the village elders and some general public had vast amounts of traditional knowledge, most of it was related to animal husbandry and the medicinal value of plants. Village elders were unfamiliar with the concept of the term ‘biodiversity’ albeit their way of life and attitudes ensured that they care for the ecosystem without having the scientific basis underpinning biodiversity conservation. Inherently, village elders were keen to conserve nature; the superimposition of governmental policies without any tangible benefit or consultation was seen as detrimental. Alienating villagers and consequently the village elders who are the reservoirs of traditional knowledge would not only be damaging to the social network of the area but would also disdain years of tried and tested techniques held by the elders. Forest officers advocated for biodiversity and conservation education for women and children. Women, across all groups, when questioned about nature conservation, showed more interest in learning and participation. Biodiversity not only has an ethical and cultural value, but also plays a role in ecosystem function and, thus, provides ecosystem services and supports livelihoods. Therefore, underpinning and using traditional knowledge and incorporating them into programs of biodiversity conservation should be explored with a sense of urgency.

Keywords: biological diversity, mega-biodiverse countries, traditional ecological knowledge, society-biodiversity links

Procedia PDF Downloads 92

Authors: Bushra Zafar, Usman Qamar

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Large data sample size and dimensions render the effectiveness of conventional data mining methodologies. A data mining technique are important tools for collection of knowledgeable information from variety of databases and provides supervised learning in the form of classification to design models to describe vital data classes while structure of the classifier is based on class attribute. Classification efficiency and accuracy are often influenced to great extent by noisy and undesirable features in real application data sets. The inherent natures of data set greatly masks its quality analysis and leave us with quite few practical approaches to use. To our knowledge first time, we present a new approach for investigation of structure and quality of datasets by providing a targeted analysis of localization of noisy and irrelevant features of data sets. Machine learning is based primarily on feature selection as pre-processing step which offers us to select few features from number of features as a subset by reducing the space according to certain evaluation criterion. The primary objective of this study is to trim down the scope of the given data sample by searching a small set of important features which may results into good classification performance. For this purpose, a heuristic for wrapper-based feature selection using genetic algorithm and for discriminative feature selection an external classifier are used. Selection of feature based on its number of occurrence in the chosen chromosomes. Sample dataset has been used to demonstrate proposed idea effectively. A proposed method has improved average accuracy of different datasets is about 95%. Experimental results illustrate that proposed algorithm increases the accuracy of prediction of different diseases.

Keywords: data mining, generic algorithm, KNN algorithms, wrapper based feature selection

Procedia PDF Downloads 307

Authors: M. S. Wickramarachchi, L. S. Nawarathna, C. M. B. Dematawewa

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Hatchery performance is critical for the profitability of poultry breeder operations. Some extrinsic parameters of eggs and breeders cause to increase or decrease the hatchability. This study aims to identify the affecting extrinsic parameters on the commercial hatchability of local chicken's eggs and determine the most efficient classification model with a hatchability rate greater than 90%. In this study, seven extrinsic parameters were considered: egg weight, moisture loss, breeders age, number of fertilised eggs, shell width, shell length, and shell thickness. Multiple linear regression was performed to determine the most influencing variable on hatchability. First, the correlation between each parameter and hatchability were checked. Then a multiple regression model was developed, and the accuracy of the fitted model was evaluated. Linear Discriminant Analysis (LDA), Classification and Regression Trees (CART), k-Nearest Neighbors (kNN), Support Vector Machines (SVM) with a linear kernel, and Random Forest (RF) algorithms were applied to classify the hatchability. This grouping process was conducted using binary classification techniques. Hatchability was negatively correlated with egg weight, breeders' age, shell width, shell length, and positive correlations were identified with moisture loss, number of fertilised eggs, and shell thickness. Multiple linear regression models were more accurate than single linear models regarding the highest coefficient of determination (R²) with 94% and minimum AIC and BIC values. According to the classification results, RF, CART, and kNN had performed the highest accuracy values 0.99, 0.975, and 0.972, respectively, for the commercial hatchery process. Therefore, the RF is the most appropriate machine learning algorithm for classifying the breeder outcomes, which are economically profitable or not, in a commercial hatchery.

Keywords: classification models, egg weight, fertilised eggs, multiple linear regression

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Authors: Annalakshmi G., Sakthivel Murugan S.

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This paper presents a local directional encoded derivative binary pattern (LDEDBP) feature extraction method that can be applied for the classification of submarine coral reef images. The classification of coral reef images using texture features is difficult due to the dissimilarities in class samples. In coral reef image classification, texture features are extracted using the proposed method called local directional encoded derivative binary pattern (LDEDBP). The proposed approach extracts the complete structural arrangement of the local region using local binary batten (LBP) and also extracts the edge information using local directional pattern (LDP) from the edge response available in a particular region, thereby achieving extra discriminative feature value. Typically the LDP extracts the edge details in all eight directions. The process of integrating edge responses along with the local binary pattern achieves a more robust texture descriptor than the other descriptors used in texture feature extraction methods. Finally, the proposed technique is applied to an extreme learning machine (ELM) method with a meta-heuristic algorithm known as weighted distance grey wolf optimizer (GWO) to optimize the input weight and biases of single-hidden-layer feed-forward neural networks (SLFN). In the empirical results, ELM-WDGWO demonstrated their better performance in terms of accuracy on all coral datasets, namely RSMAS, EILAT, EILAT2, and MLC, compared with other state-of-the-art algorithms. The proposed method achieves the highest overall classification accuracy of 94% compared to the other state of art methods.

Keywords: feature extraction, local directional pattern, ELM classifier, GWO optimization

Procedia PDF Downloads 149

Authors: А. I. Dovgyalo, S. O. Nekrasova, D. V. Sarmin, A. A. Shimanov, D. A. Uglanov

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Usually liquefied natural gas (LNG) gasification is performed due to atmospheric heat. In order to produce a liquefied gas a sufficient amount of energy is to be consumed (about 1 kW∙h for 1 kg of LNG). This study offers a number of solutions, allowing using a cold energy of LNG. In this paper it is evaluated the application turbines installed behind the evaporator in LNG complex due to its work additional energy can be obtained and then converted into electricity. At the LNG consumption of G=1000kg/h the expansion work capacity of about 10 kW can be reached. Herewith-open Rankine cycle is realized, where a low capacity cryo-pump (about 500W) performs its normal function, providing the cycle pressure. Additionally discussed an application of Stirling engine within the LNG complex also gives a possibility to realize cold energy. Considering the fact, that efficiency coefficient of Stirling engine reaches 50 %, LNG consumption of G=1000 kg/h may result in getting a capacity of about 142 kW of such a thermal machine. The capacity of the pump, required to compensate pressure losses when LNG passes through the hydraulic channel, will make 500 W. Apart from the above-mentioned converters, it can be proposed to use thermoelectric generating packages (TGP), which are widely used now. At present, the modern thermoelectric generator line provides availability of electric capacity with coefficient of efficiency up to 15%. In the proposed complex, it is suggested to install the thermoelectric generator on the evaporator surface is such a way, that the cold end is contacted with the evaporator’s surface, and the hot one – with the atmosphere. At the LNG consumption of G=1000 kgг/h and specified coefficient of efficiency the capacity of the heat flow Qh will make about 32 kW. The derivable net electric power will be P=4,2 kW, and the number of packages will amount to about 104 pieces. The carried out calculations demonstrate the research perceptiveness in this field of propulsion plant development, as well as allow realizing the energy saving potential with the use of liquefied natural gas and other cryogenics technologies.

Keywords: cold energy, gasification, liquefied natural gas, electricity

Procedia PDF Downloads 264