Search results for: advanced%20process%20control

Authors: Sun Zhe, Ruggero Micheletto

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The research of neural network is very important for the development of advanced next generation intelligent devices and the medical treatment. The most important part of the neural network research is the learning. The process of learning in our brain is essentially several adjustment processes of connection strength between neurons. It is very difficult to figure out how this mechanism works in the complex network and how the connection strength influences brain functions. For this reason, we made a model with only two coupled neurons and studied the influence of connection strength between them. To emulate the neuronal activity of realistic neurons, we prefer to use the Izhikevich neuron model. This model can simulate the neuron variables accurately and it’s simplicity is very suitable to implement on computers. In this research, the parameter ρ is used to estimate the correlation coefficient between spike train of two coupling neurons.We think the results is very important for figuring out the mechanism between synchronization of coupling neurons and synaptic plasticity. The result also presented the importance of the spike frequency adaptation in complex systems.

Keywords: neural networks, noise, stochastic processes, coupled neurons, correlation coefficient, synchronization, pacemaker, synaptic plasticity

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Authors: Ram Sharan Mehta

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The number of new cancer cases annually is estimated to rise from 10.9 million in 2002 to more than 16 million by 2020, if current trends continue. Much of this increase in absolute numbers derives from the ageing of populations worldwide. The objectives of this study were to find out the demographic characteristics of the admitted cancer patients in BPKIHS. It was hospital based descriptive cross-sectional study conducted reviewing all the records of admitted diagnosed cancer patients in BPKIHS from 15th October 2004 to 14th October 2012. Using total enumerative sampling technique all 1379 diagnosed cancer patients record were reviewed after obtaining the permission from concerned authorities. Using SPSS-15 software package data was analyzed. It was found that majority (71%) of cancer patients were of age more than 40 years and equal of both sexes. Most of the clients were form Sunsari (31.1%), Morang (16.6%) and Jhapa (17%) districts. The mean hospitalization day is 8.32 and very few patients (5.2%) were only cured. The numbers of cancer patients are markedly increases in BPKIHS, especially in advanced stage. It is mandatory to start the cancer information and education programme in eastern region of Nepal and proper management of cancer patients using chemotherapy, radiotherapy and surgery at BPKIHS for quality patient care.

Keywords: lung, cancer, patients, Nepal

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Authors: Seyyed Hossein Alavi, Soudabeh Mehri Talarposhti

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Quick development of urban population need for housing on the one hand and prevention of irregular urban extension for optimum usage of urban land, resolving problems of urban physiognomy, land using, and environmental issues and urban transport, on the other hand, proposed tall building as urban area extension requirement in developing and advanced countries. Beside the tall building, protection, and creation of green architecture is one the most important issues of today's architecture world. This research is about attending tall building with green architecture in Babolsar city 2015. For this, the issues that can make favorite conditions for green architecture has been discussed. The purpose of this discussion is skeleton extension and accessing interactions between architecture and related technologies. This discussion with using of qualitative research methods (Analytical Description) tried to studying designed performance models and also studying and analyzing the inside and foreign articles and books. Hope this research is useful in solving the existing problems in this issue.

Keywords: tall building, green architecture, skeleton extension, Babolsar city

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Authors: Xuemei Jiang, Kunfu Zhu, Shouyang Wang

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In this paper, we selected China as a case and employ a time-series of unique input-output tables distinguishing firm ownership and processing exports, to evaluate the role of foreign-invested enterprises (FIEs) in China’s rapid carbon dioxide emission growth. The results suggested that FIEs contributed to 11.55% of the economic outputs’ growth in China between 1992-2010, but accounted for only 9.65% of the growth of carbon dioxide emissions. In relative term, until 2010 FIEs still emitted much less than Chinese-owned enterprises (COEs) when producing the same amount of outputs, although COEs experienced much faster technology upgrades. In an ideal scenario where we assume the final demands remain unchanged and COEs completely mirror the advanced technologies of FIEs, more than 2000 Mt of carbon dioxide emissions would be reduced for China in 2010. From a policy perspective, the widespread FIEs are very effective and efficient channel to encourage technology transfer from developed to developing countries.

Keywords: carbon dioxide emissions, foreign-invested enterprises, technology transfer, input–output analysis, China

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Authors: Neelofar, Khursheed Alam, Jamal Ahmad

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Protein modification in diabetes mellitus may lead to early glycation products (EGPs) or amadori product as well as advanced glycation end products (AGEs). Early glycation involves the reaction of glucose with N-terminal and lysyl side chain amino groups to form Schiff’s base which undergoes rearrangements to form more stable early glycation product known as Amadori product. After Amadori, the reactions become more complicated leading to the formation of advanced glycation end products (AGEs) that interact with various AGE receptors, thereby playing an important role in the long-term complications of diabetes. Millard reaction or nonenzymatic glycation reaction accelerate in diabetes due to hyperglycation and alter serum protein’s structure, their normal functions that lead micro and macro vascular complications in diabetic patients. In this study, Human Serum Albumin (HSA) with a constant concentration was incubated with different concentrations of glucose at 370C for a week. At 4th day, Amadori product was formed that was confirmed by colorimetric method NBT assay and TBA assay which both are authenticate early glycation product. Conformational changes in native as well as all samples of Amadori albumin with different concentrations of glucose were investigated by various biophysical and biochemical techniques. Main biophysical techniques hyperchromacity, quenching of fluorescence intensity, FTIR, CD and SDS-PAGE were used. Further conformational changes were observed by biochemical assays mainly HMF formation, fructoseamine, reduction of fructoseamine with NaBH4, carbonyl content estimation, lysine and arginine residues estimation, ANS binding property and thiol group estimation. This study find structural and biochemical changes in Amadori modified HSA with normal to hyperchronic range of glucose with respect to native HSA. When glucose concentration was increased from normal to chronic range biochemical and structural changes also increased. Highest alteration in secondary and tertiary structure and conformation in glycated HSA was observed at the hyperchronic concentration (75mM) of glucose. Although it has been found that Amadori modified proteins is also involved in secondary complications of diabetes as AGEs but very few studies have been done to analyze the conformational changes in Amadori modified proteins due to early glycation. Most of the studies were found on the structural changes in Amadori protein at a particular glucose concentration but no study was found to compare the biophysical and biochemical changes in HSA due to early glycation with a range of glucose concentration at a constant incubation time. So this study provide the information about the biochemical and biophysical changes occur in Amadori modified albumin at a range of glucose normal to chronic in diabetes. Although many implicates currently in use i.e. glycaemic control, insulin treatment and other chemical therapies that can control many aspects of diabetes. However, even with intensive use of current antidiabetic agents more than 50 % of diabetic patient’s type 2 suffers poor glycaemic control and 18 % develop serious complications within six years of diagnosis. Experimental evidence related to diabetes suggests that preventing the nonenzymatic glycation of relevant proteins or blocking their biological effects might beneficially influence the evolution of vascular complications in diabetic patients or quantization of amadori adduct of HSA by authentic antibodies against HSA-EGPs can be used as marker for early detection of the initiation/progression of secondary complications of diabetes. So this research work may be helpful for the same.

Keywords: diabetes mellitus, glycation, albumin, amadori, biophysical and biochemical techniques

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Authors: Ly. Benbahouche

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Currently, several soft switching topologies have been studied to achieve high power switching efficiency, reduced cost, improved reliability and reduced parasites. It is well known that improvement in power electronics systems always depend on advanced in power devices. The IGBT has been successfully used in a variety of switching applications such as motor drives and appliance control because of its superior characteristics. The aim of this paper is focuses on simulation and explication of the internal dynamics of IGBTs behaviour under the most popular soft switching schemas that is Zero Current Switching (ZCS) environments. The main purpose of this paper is to point out some mechanisms relating to current tail during the turn-off and examination of the response at turn-off with variation of temperature, inductance L, snubber capacitors Cs, and bus voltage in order to achieve an improved understanding of internal carrier dynamics. It is shown that the snubber capacitor, the inductance and even the temperature controls the magnitude and extent of the tail current, hence the turn-off time (switching speed of the device). Moreover, it has also been demonstrated that the ZCS switching can be utilized efficiently to improve and reduce the power losses as well as the turn-off time. Furthermore, the turn-off loss in ZCS was found to depend on the time of switching of the device.

Keywords: PT-IGBT, ZCS, turn-off losses, dV/dt

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Authors: Junqi Zou

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As one of the world’s most tech-ready countries, Singapore has initiated the Smart Nation plan to harness the full power and potential of digital technologies to transform the way people live and work, through the more efficient government and business processes, to make the economy more productive. The key evolutions of digital technology transformation in healthcare and the increasing deployment of Internet of Things (IoTs), Big Data, AI/cognitive, Robotic Process Automation (RPA), Electronic Health Record Systems (EHR), Electronic Medical Record Systems (EMR), Warehouse Management System (WMS in the most recent decade have significantly stepped up the move towards an information-driven healthcare ecosystem. The advances in information technology not only bring benefits to patients but also act as a key force in changing management accounting in healthcare sector. The aim of this study is to investigate the impacts of digital technology transformation on Singapore’s healthcare sector from a management accounting perspective. Adopting a Balanced Scorecard (BSC) analysis approach, this paper conducted an exploratory case study of a newly launched Singapore public hospital, which has been recognized as amongst the most digitally advanced healthcare facilities in Asia-Pacific region. Specifically, this study gains insights on how the new technology is changing healthcare organizations’ management accounting from four perspectives under the Balanced Scorecard approach, 1) Financial Perspective, 2) Customer (Patient) Perspective, 3) Internal Processes Perspective, and 4) Learning and Growth Perspective. Based on a thorough review of archival records from the government and public, and the interview reports with the hospital’s CIO, this study finds the improvements from all the four perspectives under the Balanced Scorecard framework as follows: 1) Learning and Growth Perspective: The Government (Ministry of Health) works with the hospital to open up multiple training pathways to health professionals that upgrade and develops new IT skills among the healthcare workforce to support the transformation of healthcare services. 2) Internal Process Perspective: The hospital achieved digital transformation through Project OneCare to integrate clinical, operational, and administrative information systems (e.g., EHR, EMR, WMS, EPIB, RTLS) that enable the seamless flow of data and the implementation of JIT system to help the hospital operate more effectively and efficiently. 3) Customer Perspective: The fully integrated EMR suite enhances the patient’s experiences by achieving the 5 Rights (Right Patient, Right Data, Right Device, Right Entry and Right Time). 4) Financial Perspective: Cost savings are achieved from improved inventory management and effective supply chain management. The use of process automation also results in a reduction of manpower costs and logistics cost. To summarize, these improvements identified under the Balanced Scorecard framework confirm the success of utilizing the integration of advanced ICT to enhance healthcare organization’s customer service, productivity efficiency, and cost savings. Moreover, the Big Data generated from this integrated EMR system can be particularly useful in aiding management control system to optimize decision making and strategic planning. To conclude, the new digital technology transformation has moved the usefulness of management accounting to both financial and non-financial dimensions with new heights in the area of healthcare management.

Keywords: balanced scorecard, digital technology transformation, healthcare ecosystem, integrated information system

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Authors: Samira Haghbin, Behnam Daryayelaal, Zeinab Amiri

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As a result of rapid progress of technology in various industries, the only way to survive in a competitive market of business is to update one's situation along with the said developments. During recent decades, Robotics and automation of the construction operation has emerged as one of the important technologies grabbing the attention of various industries and specially the construction industry. Because of the coming labor shortage of the aging society in the near future, robots will be used in construction fields more than ever. By predicting the condition of Robotics in world's future construction industry, we can make necessary preparations to face with needs imposed by the time and stay ahead. This article takes a library study approach and presents a literature review of existing studies with an aim to investigate the use of robotics in past, present and future of construction industry and make predictions on its' growth and change process. Therefore, to make familiar with this kind of technology and its' requirements in the construction industry, the status of Robotics in construction industry of different countries of the world has been studied and necessary context for its' future progress is expressed. It is hoped that identifying needs and required contexts will facilitate further development of advanced technologies such as robotics industry and lead to more preparation for future.

Keywords: future of robotics, construction industry, construction automation, trends of automation

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Authors: Wei-Han Wang, Hsiang-Yu Yu, Mau-Sun Hua

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Theory of Mind (ToM) refers to the ability to infer another’s mental state. With appropriate ToM, one can behave well in social interactions. A growing body of evidence has demonstrated that patients with temporal lobe epilepsy (TLE) may have damaged ToM due to impact on regions of the underlying neural network of ToM. However, the question of whether there is cerebral laterality for ToM functions remains open. This study aimed to examine whether there is cerebral lateralization for ToM abilities in TLE patients. Sixty-seven adult TLE patients and 30 matched healthy controls (HC) were recruited. Patients were classified into right (RTLE), left (LTLE), and bilateral (BTLE) TLE groups on the basis of a consensus panel review of their seizure semiology, EEG findings, and brain imaging results. All participants completed an intellectual test and four tasks measuring basic and advanced ToM. The results showed that, on all ToM tasks; (1)each patient group performed worse than HC; (2)there were no significant differences between LTLE and RTLE groups; (3)the BTLE group performed the worst. It appears that the neural network responsible for ToM is distributed evenly between the cerebral hemispheres.

Keywords: cerebral lateralization, social cognition, temporal lobe epilepsy, theory of mind

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Authors: Zate Zewdneh Zana

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Coffea arabica (Arabica coffee), a cornerstone of the global beverage industry, necessitates rigorous genetic conservation due to its economic significance and genetic complexity. In this study, we performed whole-genome resequencing of wild species collected from its birthplace, Ethiopia. Advanced Illumina sequencing technology facilitated the mapping of a high percentage of clean reads to the C. arabica reference genome, revealing a substantial number of genetic variants, predominantly SNPs. Our comprehensive analysis not only uncovered a notable distribution of genomic variants across the coffee genome but also identified distinct genetic groups through phylogenetic and population structure analyses. This genomic study provides invaluable insights into the genetic diversity of C. arabica, highlighting the potential of identified SNPs and InDels in enhancing our understanding of key agronomic traits. The findings contribute significantly to genetic studies and support strategic breeding and conservation efforts essential for sustaining the global coffee industry.

Keywords: population genetics, wild species, evolutionary study, coffee plant

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Authors: Turuganti Venkateswarlu, Jagadeesh Anmala

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Excessive runoffs from various non-point source land uses, and other point sources are rapidly contaminating the water quality of streams in the Upper Green River watershed, Kentucky, USA. It is essential to maintain the stream water quality as the river basin is one of the major freshwater sources in this province. It is also important to understand the water quality parameters (WQPs) quantitatively and qualitatively along with their important features as stream water is sensitive to climatic events and land-use practices. In this paper, a model was developed for predicting one of the significant WQPs, Fecal Coliform (FC) from precipitation, temperature, urban land use factor (ULUF), agricultural land use factor (ALUF), and forest land-use factor (FLUF) using Random Forest (RF) algorithm. The RF model, a novel ensemble learning algorithm, can even find out advanced feature importance characteristics from the given model inputs for different combinations. This model’s outcomes showed a good correlation between FC and climate events and land use factors (R2 = 0.94) and precipitation and temperature are the primary influencing factors for FC.

Keywords: water quality, land use factors, random forest, fecal coliform

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Authors: Sanjay Kumar, Lillie Dewan

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The study of complex dynamic systems has advanced through various scientific approaches with the help of computer modeling. The common design trends in aerospace system design can be applied to quadcopter design. A quadcopter is a nonlinear, under-actuated system with complex aerodynamics parameters and creates challenges that demand new, robust, and effective control approaches. The flight control stability can be improved by planning and tracking the trajectory and reducing the effect of sensors and the operational environment. This paper presents a modern design Simmechanics visual modeling approach for a mechanical model of a quadcopter with three degrees of freedom. The Simmechanics model, considering inertia, mass, and geometric properties of a dynamic system, produces multiple translation and rotation maneuvers. The proportional, integral, and derivative (PID) controller is integrated with the Simmechanics model to follow a predefined quadcopter rotational trajectory for a fixed time interval. The results presented are satisfying. The simulation of the quadcopter control performed operations successfully.

Keywords: nonlinear system, quadcopter model, simscape modelling, proportional-integral-derivative controller

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Authors: Andrew Hardman, Alistair T. McIlhagger, Edward Archer

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A degree of research has been undertaken in the determination of 3D textile preforms behaviour to compression with direct comparison to 2D counterparts. Multiscale simulations have been developed to try and accurately analyse the behaviour of varying architectures post-consolidation. However, further understanding is required to experimentally identify the mechanisms and deformations that exist upon conforming to a complex contour. Due to the complexity of 3D textile preforms, determination of yarn behaviour to a complex contour is assessed through consolidation by means of vacuum assisted resin transfer moulding (VARTM), and the resulting mechanisms are investigated by micrograph analysis. Varying architectures; with known areal densities, pic density and thicknesses are assessed for a cohesive study. The resulting performance of each is assessed qualitatively as well as quantitatively from the perspective of material in terms of the change in representative unit cell (RVE) across the curved beam contour, in crimp percentage, tow angle, resin rich areas and binder distortion. A novel textile is developed from the resulting analysis to overcome the observed deformations.

Keywords: comformability, compression, binder architecture, 3D weaving, textile preform

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Authors: Vijay H. Ingole, Efthimia Lioliou

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Indirubin, a key bioactive component of traditional Chinese medicine, has gained increasing recognition for its potential in modern biomedical applications, particularly in pharmacology and therapeutics. The present work aimed to harness the potential by engineering an Escherichia coli strain capable of high-yield indirubin production. Through meticulous genetic engineering, we optimized the metabolic pathways in E. coli to enhance indirubin synthesis. Further, to explored the optimization of culture media and indirubin yield via batch and fed-batch fermentation techniques. By fine-tuning upstream process (USP) parameters, including nutrient composition, pH, temperature, and aeration, we established conditions that maximized both cell growth and indirubin production. Additionally, significant efforts were dedicated to refining downstream process (DSP) conditions for the extraction, purification, and quantification of indirubin. Utilizing advanced biochemical methods and analytical techniques such as UHPLC, we ensured the production of high purity indirubin. This approach not only improved the economic viability of indirubin bioproduction but also aligned with the principles of green production and sustainability.

Keywords: indirubin, bacterial strain, fermentation, HPLC

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Authors: G. Hodaifa, J. A. Páez, C. Agabo, E. Ramos, J. C. Gutiérrez, A. Rosal

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Currently, the continuous two-phase decanter process used for olive oil production is the more internationally widespread. The wastewaters generated from this industry (OMW) is a real environmental problem because of its high organic load. Among proposed treatments for these wastewaters, the advanced oxidation technologies (Fenton process, ozone, photoFenton, etc.) are the most favourable. The direct application of these processes is somewhat expensive. Therefore, the application of a previous stage based on a flocculation-sedimentation operation is of high importance. In this research five commercial flocculants (three cationic, and two anionic) have been used to achieve the separation of phases (liquid clarified-sludge). For each flocculant, different concentrations (0-1000 mg/L) have been studied. In these experiments, sludge volume formed over time and the final water quality were determined. The final removal percentages of total phenols (11.3-25.1%), COD (5.6-20.4%), total carbon (2.3-26.5%), total organic carbon (1.50-23.8%), total nitrogen (1.45-24.8%), and turbidity (27.9-61.4%) were obtained. Also, the variation on the electric conductivity reduction percentage (1-8%) was determined. Finally, the best flocculants with highest removal percentages have been determined (QG2001 and Flocudex CS49).

Keywords: flocculants, flocculation, olive oil mill wastewater, water quality

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Authors: Yumee Kim, Seung-Guk Hyeon, Kukjin Chun

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An adjustable aperture using a liquid crystal is proposed for real-time range detection and obtaining images simultaneously. The adjustable aperture operates as two types of aperture stops which can create two different Depth of Field images. By analyzing these two images, the distance can be extracted from camera to object. Initially, the aperture stop has large size with zero voltage. When the input voltage is applied, the aperture stop transfer to smaller size by orientational transition of liquid crystal molecules in the device. The diameter of aperture stop is 1.94mm and 1.06mm. The proposed device has low driving voltage of 7.0V and fast response time of 6.22m. Compact size aperture of 6×6×1.1 mm3 is assembled in conventional camera which contain 1/3” HD image sensor and focal length of 3.3mm that can be used in autonomous. The measured range was up to 5m. The adjustable aperture has high stability due to no mechanically moving parts. This range sensor can be applied to the various field of 3D depth map application which is the Advanced Driving Assistance System (ADAS), drones and manufacturing machine.

Keywords: adjustable aperture, dual aperture, liquid crystal, ranging and imaging, ADAS, range sensor

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Authors: Hesham Moustafa, Ahmed M. Youssef

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The demand for green packagingin the food field has been gained increasing attention in recent decades because of its degradability and safely. Thus, this study revealed that the by-product bagasse papers (BPs) derived from sugarcane waste can be decorated with a thin layer of polystyrene (PS) nanocomposites using the spreading approach.Three variable concentrations of TiO2 nanoparticles (i.e. 0.5, 1.0, 1.5 wt.%) were used to fabricate PS nanocomposites. The morphology of coated BP-PS biofilms was examined by X-ray diffraction, Fourier transferred Infrared spectroscopy (FT-IR), and scanning electron microscopy (SEM). Moreover, other measurements such as mechanical, thermal stability, flammability, wettability by the contact angle, water vapor, and gas barrier properties were carried out on the fabricated BP-PS biofilms. Most outcomes showed that the major properties were enhanced when the PS nanocomposites were implemented. The use of 1.5 wt.% TiO2 in PS nanocomposite for coated BP-PS biofilm increased the tensile stress by ~ 217 % compared to uncoated BP film. Furthermore, the rate of burning for BP-PS-1.5% film was reduced to ~ 33 mm/min because of the crystallinity of PS and the barrier effect provided by TiO₂ NPs. These coated sheets provide a promising candidate for use in advanced packaging applications.

Keywords: bagasse paper, polystyrene nanocomposites, TiO2 nanoparticles, active packaging, mechanical properties, flammability

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Authors: M. R. Naroui Rad, A. Ghalandarzehi, J. A. Koohpayegani

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Nine advanced cultivars and lines were planted in transplant trays on March, 2013. In mid-April 2014, nine cultivars and lines were taken from the seedling trays and were evaluated and compared in an experiment in form of a completely randomized block design with three replications at the Agricultural Research Station, Zahak. The results of the analysis of variance showed that there was a significant difference between the studied cultivars in terms of average fruit weight, fruit length, fruit diameter, ratio of fruit length to its diameter, the relative number of seeds per fruit, and each plant yield. The total yield of Sohrab and Y6 line with and an average of 41.9 and 36.7 t/ ha allocated the highest yield respectively to themselves. The results of simple correlation between the analyzed traits showed the final yield was affected by the average fruit weight due to direct and indirect effects of fruit weight and plant yield on the final yield. The genotypic and heritability values were high for fruit weight, fruit length and number of seed per fruit. The first two principal components accounted for 81.6% of the total variation among the characters describing genotypes.

Keywords: eggplant, principal component, variation, path analysis

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Authors: Hadeer R. M. Tawfik, Rania A. K. Birry, Amani A. Saad

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Eyes are considered to be the most sensitive and important organ for human being. Thus, any eye disorder will affect the patient in all aspects of life. Cataract is one of those eye disorders that lead to blindness if not treated correctly and quickly. This paper demonstrates a model for automatic detection, classification, and grading of cataracts based on image processing techniques and artificial intelligence. The proposed system is developed to ease the cataract diagnosis process for both ophthalmologists and patients. The wavelet transform combined with 2D Log Gabor Wavelet transform was used as feature extraction techniques for a dataset of 120 eye images followed by a classification process that classified the image set into three classes; normal, early, and advanced stage. A comparison between the two used classifiers, the support vector machine SVM and the artificial neural network ANN were done for the same dataset of 120 eye images. It was concluded that SVM gave better results than ANN. SVM success rate result was 96.8% accuracy where ANN success rate result was 92.3% accuracy.

Keywords: cataract, classification, detection, feature extraction, grading, log-gabor, neural networks, support vector machines, wavelet

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Authors: Raghavi Janaswamy, Saraswathi K. Vasudev

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Music is one of the supreme arts of expressions, next to the speech itself. Its evolution over centuries has paved the way with a variety of training protocols and performing methods. Indian classical music is one of the most elaborate and refined systems with immense emphasis on the voice culture related to range, breath control, quality of the tone, flexibility and diction. Several exercises namely saraliswaram, jantaswaram, dhatuswaram, upper stayi swaram, alamkaras and varnams lay the required foundation to gain the voice culture and deeper understanding on the voice development and further on to the intricacies of the raga system. This article narrates a few of the Carnatic music training methods with an emphasis on the advanced practice methods for articulating the vocal skills, continuity in the voice, ability to produce gamakams, command in the multiple speeds of rendering with reasonable volume. The creativity on these exercises and their impact on the voice production are discussed. The articulation of the outlined conscious practice methods and vocal exercises bestow the optimum use of the natural human vocal system to not only enhance the signing quality but also to gain health benefits.

Keywords: Carnatic music, Saraliswaram, Varnam, vocal training

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Authors: Xu Rumin, Chen Jianyi, Yue Ti, Wang Yaan

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With the rapid development of subsea oil and gas exploitation, the demand for the related underwater process equipment is increasing fast. In order to reduce the energy consuming, people tend to separate the gas and oil phase directly on the seabed. Accordingly, an advanced separator is needed. In this paper, the pressure drop of a new type of separator named Gas Liquid Cylindrical Cyclone (GLCC) which is used in the subsea system is investigated by both experiments and numerical simulation. In the experiments, the single phase flow and gas-liquid two phase flow in GLCC were tested. For the simulation, the performance of GLCC under both laboratory and industrial conditions was calculated. The Eulerian model was implemented to describe the mixture flow field in the GLCC under experimental conditions and industrial oil-natural gas conditions. Furthermore, a relationship among Euler number (Eu), Reynolds number (Re), and Froude number (Fr) is generated according to similarity analysis and simulation data, which can present the GLCC separation performance of pressure drop. These results can give reference to the design and application of GLCC in deep sea.

Keywords: dimensionless analysis, gas-liquid cylindrical cyclone, numerical simulation, pressure drop

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Authors: Sulihantoro, Muhamad Irga Fahreza

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Age of onset of the crisis makes more advanced understanding of the values of Islam that has been etched in architectural design. The majority Muslim mosque architecture designing buildings when they designed the architecture of Islam has always stuck in a cultural symbol, the shape of the facade, carving calligraphy, and all things that are closely related to the culture of the Middle East. As well as the interpretation of symbols, by designing a dome in every mosque, calligraphy carvings inside the mosque, and the other elements in the building which is interpreted by middle eastern culture. So here we have a problem understanding the meaning of Islam with kaf fah (overall), which appears distorted understanding to distinguish between cultural values and theological in design. This paper will try to evaluate the design of a contemporary mosque in Indonesia, with a case study in Masjid Kauman Yogyakarta Indonesia. building characteristics focused on the function of the building, history, aesthetics, comfort, and safety. The results of this study should be found on the evaluation of the integrated design of contemporary mosques are based on a study of the Quran and Hadith.

Keywords: characteristics, Islamic concept, culture, Kauman Mosque

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Authors: Jianyong Xue, Olivier L. Georgeon, Salima Hassas

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During the initial phase of cognitive development, infants exhibit amazing abilities to generate novel behaviors in unfamiliar situations, and explore actively to learn the best while lacking extrinsic rewards from the environment. These abilities set them apart from even the most advanced autonomous robots. This work seeks to contribute to understand and replicate some of these abilities. We propose the Bottom-up hiErarchical sequential Learning algorithm with Constructivist pAradigm (BEL-CA) to design agents capable of learning autonomously and continuously through interactions. The algorithm implements no assumption about the semantics of input and output data. It does not rely upon a model of the world given a priori in the form of a set of states and transitions as well. Besides, we propose a toolkit to analyze the learning process at run time called GAIT (Generating and Analyzing Interaction Traces). We use GAIT to report and explain the detailed learning process and the structured behaviors that the agent has learned on each decision making. We report an experiment in which the agent learned to successfully interact with its environment and to avoid unfavorable interactions using regularities discovered through interaction.

Keywords: cognitive development, constructivist learning, hierarchical sequential learning, self-adaptation

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Authors: Giuseppe Spampinato, Salvatore Curti, Ivana Guarneri, Arcangelo Bruna

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This document describes an advanced system and methodology for Cross Traffic Alert (CTA), able to detect vehicles that move into the vehicle driving path from the left or right side. The camera is supposed to be not only on a vehicle still, e.g. at a traffic light or at an intersection, but also moving slowly, e.g. in a car park. In all of the aforementioned conditions, a driver’s short loss of concentration or distraction can easily lead to a serious accident. A valid support to avoid these kinds of car crashes is represented by the proposed system. It is an extension of our previous work, related to a clustering system, which only works on fixed cameras. Just a vanish point calculation and simple optical flow filtering, to eliminate motion vectors due to the car relative movement, is performed to let the system achieve high performances with different scenarios, cameras and resolutions. The proposed system just uses as input the optical flow, which is hardware implemented in the proposed platform and since the elaboration of the whole system is really speed and power consumption, it is inserted directly in the camera framework, allowing to execute all the processing in real-time.

Keywords: clustering, cross traffic alert, optical flow, real time, vanishing point

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Authors: Siyao Zhu, Yifang Xu

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After natural and man-made disasters, robots can bypass the danger, expedite the search, and acquire unprecedented situational awareness to design rescue plans. The hands-free requirement from the first responders excludes the use of tedious manual control and operation. In unknown, unstructured, and obstructed environments, natural-language-based supervision is not amenable for first responders to formulate, and is difficult for robots to understand. Brain-computer interface is a promising option to overcome the limitations. This study aims to test the feasibility of using electroencephalography (EEG) signals to decode human intentions and detect the level of consensus on robot-provided information. EEG signals were classified using machine-learning and deep-learning methods to discriminate search intentions and agreement perceptions. The results show that the average classification accuracy for intention recognition and consensus assessment is 67% and 72%, respectively, proving the potential of incorporating recognizable users’ bioelectrical responses into advanced robot-assisted systems for emergency response.

Keywords: consensus assessment, electroencephalogram, emergency response, human-robot collaboration, intention recognition, search and rescue

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Authors: Rahul Mohite, Lahcen Ouarbya

Abstract:

This paper focuses on the interplay between humans and computer systems and the ability of these systems to understand and respond to human emotions, including non-verbal communication. Current emotion recognition systems are based solely on either facial or verbal expressions. The limitation of these systems is that it requires large training data sets. The paper proposes a system for recognizing human emotions that combines both speech and emotion recognition. The system utilizes advanced techniques such as deep learning and image recognition to identify facial expressions and comprehend emotions. The results show that the proposed system, based on the combination of facial expression and speech, outperforms existing ones, which are based solely either on facial or verbal expressions. The proposed system detects human emotion with an accuracy of 86%, whereas the existing systems have an accuracy of 70% using verbal expression only and 76% using facial expression only. In this paper, the increasing significance and demand for facial recognition technology in emotion recognition are also discussed.

Keywords: facial reputation, expression reputation, deep gaining knowledge of, photo reputation, facial technology, sign processing, photo type

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Authors: Venkata Narayana Chejarla, Nafisa Parvez Shaik, Gopi Vara Prasad Marabathula, Deva Kumar Bejjam

Abstract:

Yoga is an advanced, well-recognized method with roots in Indian philosophy. Yoga benefits both the body and the psyche. Yoga is a regular exercise that helps people relax and sleep better while also enhancing their balance, endurance, and concentration. Yoga can be learned in a variety of settings, including at home with the aid of books and the internet as well as in yoga studios with the guidance of an instructor. Self-learning does not teach the proper yoga poses, and doing them without the right instruction could result in significant injuries. We developed "Online Yoga Asana Trainer using Deep Learning" so that people could practice yoga without a teacher. Our project is developed using Tensorflow, Movenet, and Keras models. The system makes use of data from Kaggle that includes 25 different yoga poses. The first part of the process involves applying the movement model for extracting the 17 key points of the body from the dataset, and the next part involves preprocessing, which includes building a pose classification model using neural networks. The system scores a 98.3% accuracy rate. The system is developed to work with live videos.

Keywords: yoga, deep learning, movenet, tensorflow, keras, CNN

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Authors: Maria Nabakooza

Abstract:

Efficient agricultural production is very significant in attaining food sufficiency and security in the world. Many methods are employed by the farmers while attending to their gardens, from manual to mechanized, with Farmers range from subsistence to commercial depending on the motive. This creates a lacuna in the modes of operation in this field as different farmers will take different approaches. This has led to many e-Learning courses being introduced to address this gap. Many e-learning systems use advanced network technologies like Web services, grid computing to promote learning at any time and any place. Many of the existing systems have not inculcated the applicability of the modules in them, the tools to be used and further access whether they are the right tools for the right job. A thorough investigation into the applicability of adaptive eLearning in the agricultural sector has not been taken into account; enabling the assumption that eLearning is the right tool for boosting productivity in this sector. This study comes in to provide an insight and thorough analysis as to whether adaptive eLearning is the right tool for boosting agricultural productivity. The Simulation will adopt a system dynamics modeling approach as a way of examining causality and effect relationship. This study will provide teachers with an insight into which tools they should adopt in designing, and provide students the opportunities to achieve an orderly learning experience through adaptive navigating e-learning services.

Keywords: agriculture, adaptive, e-learning, technology

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Authors: Yasaswi Palagummi, Sareh Rowlands

Abstract:

Generalised Zero-Shot Learning, often known as GZSL, is an advanced variant of zero-shot learning in which the samples in the unseen category may be either seen or unseen. GZSL methods typically have a bias towards the seen classes because they learn a model to perform recognition for both the seen and unseen classes using data samples from the seen classes. This frequently leads to the misclassification of data from the unseen classes into the seen classes, making the task of GZSL more challenging. In this work of ours, to solve the GZSL problem, we propose an approach leveraging the Shifted Window based Self-Attention in the Swin Transformer (Swin-GZSL) to work in the inductive GSZL problem setting. We run experiments on three popular benchmark datasets: CUB, SUN, and AWA2, which are specifically used for ZSL and its other variants. The results show that our model based on Swin Transformer has achieved state-of-the-art harmonic mean for two datasets -AWA2 and SUN and near-state-of-the-art for the other dataset - CUB. More importantly, this technique has a linear computational complexity, which reduces training time significantly. We have also observed less bias than most of the existing GZSL models.

Keywords: generalised, zero-shot learning, inductive learning, shifted-window attention, Swin transformer, vision transformer

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Authors: Drashti G. Daraji, Rosa E. Moo-Puc, Hitesh D. Patel

Abstract:

Substituted 2-Thioimidazole analogues have been synthesized and confirmed by advanced spectroscopic techniques. Among them, ten compounds have been selected and evaluated for their in vitro anti-cancer activity at the National Cancer Institute (NCI) for testing against a panel of 60 different human tumor cell lines derived from nine neoplastic cancer types. Furthermore, synthesized compounds were tested for their in vitro antiprotozoal activity, and none of them exhibited significant potency against antiprotozoans. It was observed that the tested all compounds seem effective on the UACC-62 melanoma cancer cell line as compared to other cancer cell lines and also exhibited the least potent in the Non-Small Cell Lung Cancer cell line in one-dose screening. In silico studies of these derivatives were carried out by molecular docking techniques and Absorption, Distribution, Metabolism, and Excretion (ADME) using Schrödinger software to find potent B-Raf kinase inhibitor (PDB ID: 3OG7). All the compounds have been performed for docking study; Compound D4 has a good docking score for melanoma cancer as compared with other.

Keywords: anticancer activity, cancer cell line, 2-thio imidazole, one-dose assay, molecular docking

Procedia PDF Downloads 138