Search results for: cluster integration

Authors: Su Yin Chiam, Qing Xin Zhang, Jaehoon Chung

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Complementary metal-oxide-semiconductor (CMOS) integrated circuits (ICs) have obtained increased attention in the biosensor community because CMOS technology provides cost-effective and high-performance signal processing at a mass-production level. In order to supply biological samples and reagents effectively to the sensing elements, there are increasing demands for seamless integration of microfluidic components on the fabricated CMOS wafers by post-processing. Although the PDMS microfluidic channels replicated from separately prepared silicon mold can be typically aligned and bonded onto the CMOS wafers, it remains challenging owing the inherently limited aligning accuracy ( > ± 10 μm) between the two layers. Here we present a new post-processing method to create three-dimensional microfluidic components using two different polarities of photoresists, an epoxy-based negative SU-8 photoresist and positive SPR220-7 photoresist. The positive photoresist serves as a sacrificial layer and the negative photoresist was utilized as a structural material to generate three-dimensional structures. Because both photoresists are patterned using a standard photolithography technology, the dimensions of the structures can be effectively controlled as well as the alignment accuracy, moreover, is dramatically improved (< ± 2 μm) and appropriately can be adopted as an alternative post-processing method. To validate the proposed processing method, we applied this technique to build cell-trapping structures. The SU8 photoresist was mainly used to generate structures and the SPR photoresist was used as a sacrificial layer to generate sub-channel in the SU8, allowing fluid to pass through. The sub-channel generated by etching the sacrificial layer works as a cell-capturing site. The well-controlled dimensions enabled single-cell capturing on each site and high-accuracy alignment made cells trapped exactly on the sensing units of CMOS biosensors.

Keywords: SU-8, microfluidic, MEMS, microfabrication

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Authors: Chin-Yun Chen

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Numerical integration is an essential tool for deriving different physical quantities in engineering and science. The effectiveness of a numerical integrator depends on different factors, where the crucial one is the error estimation. This work presents an error estimator that combines a derivative free method to improve the performance of verified numerical quadrature.

Keywords: numerical quadrature, error estimation, derivative free method, interval computation

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Authors: Mi Ju Choi

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This study investigated the perception of gaming tourists toward Macau and developed a typology of gaming tourists. The 1,497 responses from tourists in Macau were collected through convenience sampling method. The dimensions of multi-culture, convenience, economy, gaming, and unsafety, were subsequently extracted as the factors of perception of gaming tourists in Macau. Cluster analysis was performed using the delineated factors (perception of tourists on Macau). Four heterogonous groups were generated, namely, gaming lovers (n = 467, 31.2%), exotic lovers (n = 509, 34.0%), reasonable budget seekers (n = 269, 18.0%), and convenience seekers (n = 252, 16.8%). Further analysis was performed to investigate any difference in gaming behavior and tourist activities. The findings are expected to contribute to the efforts of destination marketing organizations (DMOs) in establishing effective business strategies, provide a profile of gaming tourists in certain market segments, and assist DMOs and casino managers in establishing more effective marketing strategies for target markets.

Keywords: destination image, gaming tourists, Macau, segmentation

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Authors: Zhuanfang Fred Zhang, Tim C. Johnson, Yilin Fang, Chris E. Strickland

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A variety of geophysical techniques are available to image the opaque subsurface with little or no contact with the soil. It is common to conduct time-lapse surveys of different types for a given site for improved results of subsurface imaging. Regardless of the chosen survey methods, it is often a challenge to process the massive amount of survey data. The currently available software applications are generally based on the one-dimensional assumption for a desktop personal computer. Hence, they are usually incapable of imaging the three-dimensional (3D) processes/variables in the subsurface of reasonable spatial scales; the maximum amount of data that can be inverted simultaneously is often very small due to the capability limitation of personal computers. Presently, high-performance or integrating software that enables real-time integration of multi-process geophysical methods is needed. E4D-MP enables the integration and inversion of time-lapsed large-scale data surveys from geophysical methods. Using the supercomputing capability and parallel computation algorithm, E4D-MP is capable of processing data across vast spatiotemporal scales and in near real time. The main code and the modules of E4D-MP for inverting individual or combined data sets of time-lapse 3D electrical resistivity, spectral induced polarization, and gravity surveys have been developed and demonstrated for sub-surface imaging. E4D-MP provides capability of imaging the processes (e.g., liquid or gas flow, solute transport, cavity development) and subsurface properties (e.g., rock/soil density, conductivity) critical for successful control of environmental engineering related efforts such as environmental remediation, carbon sequestration, geothermal exploration, and mine land reclamation, among others.

Keywords: gravity survey, high-performance computing, sub-surface monitoring, electrical resistivity tomography

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Authors: K. Assis, B. Bonaventure, A. Abdul Rahim, H. Affendy, A. Mohammad Amizi

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Oil palm smallholders are considered as a very important producer of oil palm in Malaysia. They are categorized into two, which are organized smallholder and independent smallholder. In this study, there were 1000 oil palms smallholders have been interviewed by using a structured questionnaire. The main objective of the survey is to identify the relationship between socioeconomic characteristics of smallholders with their knowledge, attitude, and practices toward Ganoderma disease. The locations of study include Peninsular Malaysia and Sabah. There were three important aspects studied, namely knowledge of Ganoderma disease, attitude towards the disease as well as the practices in managing the disease. Cluster analysis, factor analysis, and binary logistic regression were used to analyze the data collected. The findings of the study should provide a baseline data which can be used by the relevant agencies to conduct programs or to formulate a suitable development plan to improve the knowledge, attitude and practices of oil palm smallholders in managing Ganoderma disease.

Keywords: attitude, Ganoderma, knowledge, oil palm, practices, smallholders

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Authors: Gachara Grace, Kebira Anthony, Harvey Jagger, Wainaina James

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Aflatoxin contamination of maize in Africa poses a major threat to food security and the health of many African people. In Kenya, aflatoxin contamination of maize is high due to the environmental, agricultural and socio-economic factors. Many studies have been conducted to understand the scope of the problem, especially at pre-harvest level. This research was carried out to gather scientific information on the fungi population, diversity and aflatoxin level during the post-harvest period. The study was conducted in three geographical locations of; Kitui, Kitale and Nakuru. Samples were collected from storage structures of farmers and transported to the Biosciences eastern and central Africa (BecA), International Livestock and Research Institute (ILRI) hub laboratories. Mycoflora was recovered using the direct plating method. A total of five fungal genera (Aspergillus, Penicillium, Fusarium, Rhizopus and Bssyochlamys spp.) were isolated from the stored maize samples. The most common fungal species that were isolated from the three study sites included A. flavus at 82.03% followed by A.niger and F.solani at 49% and 26% respectively. The aflatoxin producing fungi A. flavus was recovered in 82.03% of the samples. Aflatoxin levels were analysed on both the maize samples and in vitro. Most of the A. flavus isolates recorded a high level of aflatoxin when they were analysed for presence of aflatoxin B1 using ELISA. In Kitui, all the samples (100%) had aflatoxin levels above 10ppb with a total aflatoxin mean of 219.2ppb. In Kitale, only 3 samples (n=39) had their aflatoxin levels less than 10ppb while in Nakuru, the total aflatoxin mean level of this region was 239.7ppb. When individual samples were analysed using Vicam fluorometer method, aflatoxin analysis revealed that most of the samples (58.4%) had been contaminated. The means were significantly different (p=0.00<0.05) in all the three locations. Genetic relationships of A. flavus isolates were determined using 13 Simple Sequence Repeats (SSRs) markers. The results were used to generate a phylogenetic tree using DARwin5 software program. A total of 5 distinct clusters were revealed among the genotypes. The isolates appeared to cluster separately according to the geographical locations. Principal Coordinates Analysis (PCoA) of the genetic distances among the 91 A. flavus isolates explained over 50.3% of the total variation when two coordinates were used to cluster the isolates. Analysis of Molecular Variance (AMOVA) showed a high variation of 87% within populations and 13% among populations. This research has shown that A. flavus is the main fungal species infecting maize grains in Kenya. The influence of aflatoxins on human populations in Kenya demonstrates a clear need for tools to manage contamination of locally produced maize. Food basket surveys for aflatoxin contamination should be conducted on a regular basis. This would assist in obtaining reliable data on aflatoxin incidence in different food crops. This would go a long way in defining control strategies for this menace.

Keywords: aflatoxin, Aspergillus flavus, genotyping, Kenya

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Authors: Shih-Wen Hsiao, Yi-Cheng Tsao

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In the field of reverse engineering and creative industries, applying 3D scanning process to obtain geometric forms of the objects is a mature and common technique. For instance, organic objects such as faces and nonorganic objects such as products could be scanned to acquire the geometric information for further application. However, although the data resolution of 3D scanning device is increasing and there are more and more abundant complementary applications, the penetration rate of 3D scanning for the public is still limited by the relative high price of the devices. On the other hand, Kinect, released by Microsoft, is known for its powerful functions, considerably low price, and complete technology and database support. Therefore, related studies can be done with the applying of Kinect under acceptable cost and data precision. Due to the fact that Kinect utilizes optical mechanism to extracting depth information, limitations are found due to the reason of the straight path of the light. Thus, various angles are required sequentially to obtain the complete 3D information of the object when applying a single Kinect for 3D scanning. The integration process which combines the 3D data from different angles by certain algorithms is also required. This sequential scanning process costs much time and the complex integration process often encounter some technical problems. Therefore, this paper aimed to apply multiple Kinects simultaneously on the field of developing a rapid 3D mannequin scan platform and proposed suggestions on the number and angles of Kinects. In the content, a method of establishing the coordination based on the relation between mannequin and the specifications of Kinect is proposed, and a suggestion of angles and number of Kinects is also described. An experiment of applying multiple Kinect on the scanning of 3D mannequin is constructed by Microsoft API, and the results show that the time required for scanning and technical threshold can be reduced in the industries of fashion and garment design.

Keywords: 3D scan, depth sensor, fashion and garment design, mannequin, multiple Kinect sensor

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Authors: Hadi Molaei, Yasavoli Davoud, Keshavarz, Mozhde Poordana

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The present study aimed was to prediction the academic performance based on academic motivation, self-efficacy and Resiliency in the students. The present study was descriptive and correlational. Population of the study consisted of all students in Arak schools in year 1393-94. For this purpose, the number of 304 schools students in Arak was selected using multi-stage cluster sampling. They all questionnaires, self-efficacy, Resiliency and academic motivation Questionnaire completed. Data were analyzed using Pearson correlation and multiple regressions. Pearson correlation showed academic motivation, self-efficacy, and Resiliency with academic performance had a positive and significant relationship. In addition, multiple regression analysis showed that the academic motivation, self-efficacy and Resiliency were predicted academic performance. Based on the findings could be conclude that in order to increase the academic performance and further progress of students must provide the ground to strengthen academic motivation, self-efficacy and Resiliency act on them.

Keywords: academic motivation, self-efficacy, resiliency, academic performance

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Authors: Isari Pairoa, Proud Arunrangsiwed

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Brand mascots are the cartoon characters, which are mainly designed for advertising or other related marketing purposes. Many brand mascots are extremely popular, since they were presented in commercial advertisements and Line Stickers. Brand Line Stickers could lead the users to identify with the brand and brand mascots, where might influence users to become loyal customers, and share the identity with the brand. The objective of the current study is to examine the effect of brand mascots on consumers’ decision and consumers’ intention to purchase the product. This study involved 400 participants, using cluster sampling from 50 districts in Bangkok metropolitan area. The descriptive analysis shows that using brand mascot causes consumers' positive attitude toward the products, and also heightens the possibility to purchasing the products. The current study suggests the new type of marketing strategy, which is brand fandom. This study has also contributed the knowledge to the area of integrated marketing communication and identification theory.

Keywords: brand mascot, consumers’ behavior, marketing communication, purchasing

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Authors: H. Emari, Z. Emari

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The main objective of this research was to determine the dimensions of service quality in the banking industry of Iran. For this purpose, the study empirically examined the European perspective suggesting that service quality consists of three dimensions, technical, functional and image. This research is an applied research and its strategy is casual strategy. A standard questionnaire was used for collecting the data. 287 customers of Melli Bank of Northwest were selected through cluster sampling and were studied. The results from a banking service sample revealed that the overall service quality is influenced more by a consumer’s perception of technical quality than functional quality. Accordingly, the Gronroos model is a more appropriate representation of service quality than the American perspective with its limited concentration on the dimension of functional quality in the banking industry of Iran. So, knowing the key dimensions of the quality of services in this industry and planning for their improvement can increase the satisfaction of customers and productivity of this industry.

Keywords: technical quality, functional quality, banking, image, mediating role

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Authors: Murad Ali, Anderson Konan Seny Kan, Khalid A. Maimani

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Based on the theory of organizational design and the theory of knowledge, this study uses complexity theory to explain and better understand the causal impacts of various patterns of organizational structural factors stimulating absorptive capacity (ACAP). Organizational structure can be thought of as heterogeneous configurations where various components are often intertwined. This study argues that impact of the traditional variables which define a firm’s organizational structure (centralization, formalization, complexity and integration) on ACAP is better understood in terms of set-theoretic relations rather than correlations. This study uses a data sample of 347 from a multiple industrial sector in South Korea. The results from PLS-SEM support all the hypothetical relationships among the variables. However, fsQCA results suggest the possible configurations of centralization, formalization, complexity, integration, age, size, industry and revenue factors that contribute to high level of ACAP. The results from fsQCA demonstrate the usefulness of configurational approaches in helping understand equifinality in the field of knowledge management. A recent fsQCA procedure based on a modeling subsample and holdout subsample is use in this study to assess the predictive validity of the model under investigation. The same type predictive analysis is also made through PLS-SEM. These analyses reveal a good relevance of causal solutions leading to high level of ACAP. In overall, the results obtained from combining PLS-SEM and fsQCA are very insightful. In particular, they could help managers to link internal organizational structural with ACAP. In other words, managers may comprehend finely how different components of organizational structure can increase the level of ACAP. The configurational approach may trigger new insights that could help managers prioritize selection criteria and understand the interactions between organizational structure and ACAP. The paper also discusses theoretical and managerial implications arising from these findings.

Keywords: absorptive capacity, organizational structure, PLS-SEM, fsQCA, predictive analysis, modeling subsample, holdout subsample

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Authors: Li Ni, Pen ManMan, Li KenLi

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Clustering is an intensive research for some years because of its multifaceted applications, such as biology, information retrieval, medicine, business and so on. The expectation maximization (EM) is a kind of algorithm framework in clustering methods, one of the ten algorithms of machine learning. Traditionally, optimization of objective function has been the standard approach in EM. Hence, research has investigated the utility of evolutionary computing and related techniques in the regard. Chemical Reaction Optimization (CRO) is a recently established method. So the property embedded in CRO is used to solve optimization problems. This paper presents an algorithm framework (EM-CRO) with modified CRO operators based on EM cluster problems. The hybrid algorithm is mainly to solve the problem of initial value sensitivity of the objective function optimization clustering algorithm. Our experiments mainly take the EM classic algorithm:k-means and fuzzy k-means as an example, through the CRO algorithm to optimize its initial value, get K-means-CRO and FKM-CRO algorithm. The experimental results of them show that there is improved efficiency for solving objective function optimization clustering problems.

Keywords: chemical reaction optimization, expection maimization, initia, objective function clustering

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Authors: Ebuwa Osagie, Chet Biliyok, Yeung Hoi

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Regeneration energy requirement and ways to reduce it is the main aim of most CO2 capture researches currently being performed and thus, post-combustion carbon capture (PCC) option is identified to be the most suitable for the natural gas-fired power plants. From current research and development (R&D) activities worldwide, two main areas are being examined in order to reduce the regeneration energy requirement of amine-based PCC, namely: (a) development of new solvents with better overall performance than 30wt% monoethanolamine (MEA) aqueous solution, which is considered as the base-line solvent for solvent-based PCC, (b) Integration of the PCC Plant to the power plant. In scaling-up a PCC pilot plant to the size required for a commercial-scale natural gas-fired power plant, process modelling and simulation is very essential. In this work, an integrated process made up of a 482MWe natural gas-fired power plant, an MEA-based PCC plant which is developed and validated has been modelled and simulated. The PCC plant has four absorber columns and a single stripper column, the modelling and simulation was performed with Aspen Plus® V8.4. The gas turbine, the heat recovery steam generator and the steam cycle were modelled based on a 2010 US DOE report, while the MEA-based PCC plant was modelled as a rate-based process. The scaling of the amine plant was performed using a rate based calculation in preference to the equilibrium based approach for 90% CO2 capture. The power plant was integrated to the PCC plant in three ways: (i) flue gas stream from the power plant which is divided equally into four stream and each stream is fed into one of the four absorbers in the PCC plant. (ii) Steam draw-off from the IP/LP cross-over pipe in the steam cycle of the power plant used to regenerate solvent in the reboiler. (iii) Condensate returns from the reboiler to the power plant. The integration of a PCC plant to the NGCC plant resulted in a reduction of the power plant output by 73.56 MWe and the net efficiency of the integrated system is reduced by 7.3 % point efficiency. A secondary aim of this study is the parametric studies which have been performed to assess the impacts of natural gas on the overall performance of the integrated process and this is achieved through investigation of the capture efficiencies.

Keywords: natural gas-fired, power plant, MEA, CO2 capture, modelling, simulation

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Authors: Naomi Seidu, Edward Poluyi, Chibuikem Ikwuegbuenyi, Eghosa Morgan

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The current poor prognosis of glioblastoma has called for the need for an improvement in treatment methods in order to improve its survival rate. Despite the different interventions currently available for this tumor, the average survival is still only a few months. (12-15). The aim is to create a more favorable prognosis and have a reduction in the resistance to treatment currently being experienced, even with surgical interventions and chemotherapy. From the available literature, there is a relationship between the presence of HOX genes (Homeobox genes) and glioblastoma, which could be attributable to the increasing treatment resistance. Hence silencing these genes can be a key to improving survival rates of glioblastoma. A series of studies have highlighted the role that HOX genes play in glioblastoma prognosis. Promotion of human glioblastoma initiation, aggressiveness, and resistance to Temozolomide has been associated with HOXA9. The role of HOX gene expression in cancer stem cells should be studied as it could provide a means of designing CSC-targeted therapies, as CSCs play a part in the initiation and progression of solid tumors.

Keywords: GBM- glioblastoma, HOXA gene- homeobox genes cluster, signaling pathways, temozolomide

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Authors: Vephkhvia Grigalashvili

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This paper provides an overview of criteria for good governance in Georgian defense sector and scientific outcomes of comparative research. A respect for good governance and its realization into Georgian national defense sector represents a fundamental institutional necessity as well as country`s politico-legal obligation within the framework of the existing collaboration mechanisms with NATO (especially Building Integrity (BI) Programme) and the Association Agreement between the EU and Georgia. Furthermore good governance is considered as a democracy measuring criterion in country`s Euro-Atlantic integration process. Accordingly, integration and further development of the contemporary approaches of good governance into Georgian defense management model represents a burning issue of the country. The assessment of an existing model of the country, identification of defects and determination of course of institutional reforms in a mutual comparison format of good governance mechanisms of NATO or/and the EU member Eastern European or Baltic countries positively assessed by the international organizations is considered as a precondition for its effective realization. Scientific aims of this study are: (a) to conduct comparative analysis of Georgian national principles and generalized standards of NATO or/and the EU member Eastern European and Baltic countries in following segments of good governance: open governance; anticorruption policy; conflict of interests; integrity; internal and external control bodies; (b) to formulate theoretical and practical recommendations on reforms to be implemented in the country`s national defence sector. As research reveals, although, institutional / legal pillars of good governance in Georgian defense sector generally are in compliance with international principles, the quality of implementation of good government norms still remains as an area that needs further development by raising awareness of public servants and community.

Keywords: anti-corruption policy within Georgian defense governance, conflict of interests within Georgian defense governance, good governance in Georgian defense sector, principles of integrity in Georgian defense management

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Authors: Jeffrey Chase

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Historically the profession of Occupational Therapy was closely tied to the treatment of those suffering from mental illness; more recently, and especially in the U.S., the percentage of OTs identifying as working in the mental health area has declined significantly despite the estimate that by 2020 behavioral health disorders will surpass physical illnesses as the major cause of disability worldwide. In the U.S. less than 10% of OTs identify themselves as working with the mentally ill and/or practicing in mental health settings. Such a decline has implications for both those suffering from mental illness and the profession of Occupational Therapy. One reason cited for the decline of OT in mental health has been the limited research in the discipline addressing mental health practice. Despite significant advances in technology and growth in the field of neuroscience, major institutions and funding sources such as the National Institute of Mental Health (NIMH) have noted that research into the etiology and treatment of mental illness have met with limited success over the past 25 years. One major reason posited by NIMH is that research has been limited by how we classify individuals, that being mostly on what is observable. A new classification system being developed by NIMH, the Research Domain Criteria (RDoc), has the goal to look beyond just descriptors of disorders for common neural, genetic, and physiological characteristics that cut across multiple supposedly separate disorders. The hope is that by classifying individuals along RDoC measures that both reliability and validity will improve resulting in greater advances in the field. As a result of this change NIH and NIMH will prioritize research funding to those projects using the RDoC model. Multiple disciplines across many different setting will be required for RDoC or similar classification systems to be developed. During this shift in research methodology OT has an opportunity to reassert itself into the research and treatment of mental illness, both in developing new ways to more validly classify individuals, and to document the legitimacy of previously ill-defined and validated disorders such as sensory integration.

Keywords: global mental health and neuroscience, research opportunities for ot, greater integration of ot in mental health research, research and funding opportunities, research domain criteria (rdoc)

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Authors: Tarun Kumar Dalakoti, Debajyoti Majumder, Aditya Prasad Das, Samir Chandra Saxena

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India’s ambitious target to achieve a 50 percent share of energy from non-fossil fuels and the 500-gigawatt (GW) renewable energy capacity before the deadline of 2030, coupled with the global pursuit of sustainable development, will compel the nation to embark on a rapid clean energy transition. As a result, electricity market reforms will emerge as critical policy instruments to facilitate this transition and achieve ambitious environmental targets. This paper will present a comprehensive analysis of the various electricity market reforms to be introduced in the Indian Electricity sector to facilitate the integration of clean energy sources and will assess their impact on the overall energy landscape. The first section of this paper will delve into the policy mechanisms to be introduced by the Government of India and the Central Electricity Regulatory Commission to promote clean energy deployment. These mechanisms include extensive provisions for the integration of renewables in the Indian Electricity Grid Code, 2023. The section will also cover the projection of RE Generation as highlighted in the National Electricity Plan, 2023. It will discuss the introduction of Green Energy Market segments, the waiver of Inter-State Transmission System (ISTS) charges for inter-state sale of solar and wind power, the notification of Promoting Renewable Energy through Green Energy Open Access Rules, and the bundling of conventional generating stations with renewable energy sources. The second section will evaluate the tangible impact of these electricity market reforms. By drawing on empirical studies and real-world case examples, the paper will assess the penetration rate of renewable energy sources in India’s electricity markets, the decline of conventional fuel-based generation, and the consequent reduction in carbon emissions. Furthermore, it will explore the influence of these reforms on electricity prices, the impact on various market segments due to the introduction of green contracts, and grid stability. The paper will also discuss the operational challenges to be faced due to the surge of RE Generation sources as a result of the implementation of the above-mentioned electricity market reforms, including grid integration issues, intermittency concerns with renewable energy sources, and the need for increasing grid resilience for future high RE in generation mix scenarios. In conclusion, this paper will emphasize that electricity market reforms will be pivotal in accelerating the global transition towards clean energy systems. It will underscore the importance of a holistic approach that combines effective policy design, robust regulatory frameworks, and active participation from market actors. Through a comprehensive examination of the impact of these reforms, the paper will shed light on the significance of India’s sustained commitment to a cleaner, more sustainable energy future.

Keywords: renewables, Indian electricity grid code, national electricity plan, green energy market

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Authors: Taha Benarbia

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The advent of automated and connected vehicles has revolutionized the transportation industry, presenting new opportunities for enhancing the efficiency, safety, and sustainability of our transportation networks. This paper explores the integration of automated and connected vehicles into a smart transportation framework, leveraging the power of deep learning techniques to optimize the overall network performance. The first aspect addressed in this paper is the deployment of automated vehicles (AVs) within the transportation system. AVs offer numerous advantages, such as reduced congestion, improved fuel efficiency, and increased safety through advanced sensing and decisionmaking capabilities. The paper delves into the technical aspects of AVs, including their perception, planning, and control systems, highlighting the role of deep learning algorithms in enabling intelligent and reliable AV operations. Furthermore, the paper investigates the potential of connected vehicles (CVs) in creating a seamless communication network between vehicles, infrastructure, and traffic management systems. By harnessing real-time data exchange, CVs enable proactive traffic management, adaptive signal control, and effective route planning. Deep learning techniques play a pivotal role in extracting meaningful insights from the vast amount of data generated by CVs, empowering transportation authorities to make informed decisions for optimizing network performance. The integration of deep learning with automated and connected vehicles paves the way for advanced transportation network optimization. Deep learning algorithms can analyze complex transportation data, including traffic patterns, demand forecasting, and dynamic congestion scenarios, to optimize routing, reduce travel times, and enhance overall system efficiency. The paper presents case studies and simulations demonstrating the effectiveness of deep learning-based approaches in achieving significant improvements in network performance metrics

Keywords: automated vehicles, connected vehicles, deep learning, smart transportation network

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Authors: Azadeh Askari, Ali Nasery Mohamad Abadi

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The present study was conducted to investigate the relationship between career anchors and job satisfaction with emphasis on the mediating role of person-job fit. 502 managers and supervisors of ten operational areas of a large energy Company were selected as a cluster sample appropriate to the volume. The instruments used in this study were Career Anchor Questionnaire, Job Satisfaction Questionnaire and Person-job fit Questionnaire. Pearson correlation coefficient was used to analyze the data and AMOS software was used to determine the effect of career anchor variables and person-job fit on job satisfaction. Anchors of service and dedication, pure challenge and security and stability increase the person-job fit among managers and also the person-job fit plays a mediating role in relation to the effect it has on job satisfaction through these anchors. In contrast, the anchors of independence and autonomy reduce the person-job fit. Considering the importance of positive organizational attitudes and in order to have an optimal fit between job and worker, it is better that in human resources processes such as hiring and employing, the career anchors of the person should be considered so that the person can have more job satisfaction; and thus bring higher productivity for themselves and the organization.

Keywords: career anchor, job satisfaction, person-job fit, energy company, managers

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Authors: Gülşen Akın Evingür, Önder Pekcan

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The fractal analysis is a bridge between the microstructure and macroscopic properties of gels. Fractal structure is usually provided to define the complexity of crosslinked molecules. The complexity in gel systems is described by the fractal dimension (Df). In this study, polyacrylamide- graphene oxide (GO) composite gels were prepared by free radical crosslinking copolymerization. The fractal analysis of polyacrylamide- graphene oxide (GO) composite gels were analyzed in various GO contents during gelation and were investigated by using Fluorescence Technique. The analysis was applied to estimate Df s of the composite gels. Fractal dimension of the polymer composite gels were estimated based on the power law exponent values using scaling models. In addition, here we aimed to present the geometrical distribution of GO during gelation. And we observed that as gelation proceeded GO plates first organized themselves into 3D percolation cluster with Df=2.52, then goes to diffusion limited clusters with Df =1.4 and then lines up to Von Koch curve with random interval with Df=1.14. Here, our goal is to try to interpret the low conductivity and/or broad forbidden gap of GO doped PAAm gels, by the distribution of GO in the final form of the produced gel.

Keywords: composite gels, fluorescence, fractal, scaling

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Authors: Deepak Kumar, Debasish Deb, Reena Mamgain

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Radar signal processing requires high number crunching capability. Most often this is achieved using multiprocessor platform. Though multiprocessor platform provides the capability of meeting the real time computational challenges, the architecture of the same along with mapping of the algorithm on the architecture plays a vital role in efficiently using the platform. Towards this, along with standard performance metrics, few additional metrics are defined which helps in evaluating the multiprocessor platform along with the algorithm mapping. A generic multiprocessor architecture can not suit all the processing requirements. Depending on the system requirement and type of algorithms used, the most suitable architecture for the given problem is decided. In the paper, we study different architectures and quantify the different performance metrics which enables comparison of different architectures for their merit. We also carried out case study of different architectures and their efficiency depending on parallelism exploited on algorithm or data or both.

Keywords: radar signal processing, multiprocessor architecture, efficiency, load imbalance, buffer requirement, pipeline, parallel, hybrid, cluster of processors (COPs)

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Authors: Andres F. Ramirez, Carlos F. Valencia

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The increasing interest in renewable energies strategies application and the path for diminishing the use of carbon related energy sources have encouraged the development of novel strategies for integration of solar energy into the electricity network. A correct inclusion of the fluctuating energy output of a photovoltaic (PV) energy system into an electric grid requires improvements in the forecasting and simulation methodologies for solar energy potential, and the understanding not only of the mean value of the series but the associated underlying stochastic process. We present a methodology for synthetic generation of solar irradiance (shortwave flux) and air temperature bivariate time series based on copula functions to represent the cross-dependence and temporal structure of the data. We explore the advantages of using this nonlinear time series method over traditional approaches that use a transformation of the data to normal distributions as an intermediate step. The use of copulas gives flexibility to represent the serial variability of the real data on the simulation and allows having more control on the desired properties of the data. We use discrete zero mass density distributions to assess the nature of solar irradiance, alongside vector generalized linear models for the bivariate time series time dependent distributions. We found that the copula autoregressive methodology used, including the zero mass characteristics of the solar irradiance time series, generates a significant improvement over state of the art strategies. These results will help to better understand the fluctuating nature of solar energy forecasting, the underlying stochastic process, and quantify the potential of a photovoltaic (PV) energy generating system integration into a country electricity network. Experimental analysis and real data application substantiate the usage and convenience of the proposed methodology to forecast solar irradiance time series and solar energy across northern hemisphere, southern hemisphere, and equatorial zones.

Keywords: copula autoregressive, solar irradiance forecasting, solar energy forecasting, time series generation

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Authors: Qiu Jian-Rong, Li Qing-Hui, Zhan Dong, Zhang Lei

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Facing the problem of the demand of economic restructuring and risk of social economy stagnation due to the ageing of population, the Health Service Industry will play a very important role in the structure of industry in the future. During the process, the orient of Chinese sports medicine as well as the joint with preventive medicine, and the integration with data bank and cloud computing will be involved.

Keywords: China, the health service industry, mass sport, data bank

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Authors: Ricardo Bragança, Tom Vinaimont

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This paper discusses the introduction of processes of self-determined learning (heutagogy) into a graduate course on financial modeling, using elements of entangled pedagogy and Biggs’ constructive alignment. To encourage learners to take control of their own learning journey and develop critical thinking and problem-solving skills, each session in the course receives tailor-made media-enhanced pedagogical assets. The design of those assets specifically supports entangled pedagogy, which opposes technological or pedagogical determinism in support of the collaborative integration of pedagogy and technology. Media assets for each of the ten sessions in this course consist of three components. The first component in this three-pronged approach is a game-cut-like cinematographic representation that introduces the context of the session. The second component represents a character from an open-source-styled community that encourages self-determined learning. The third component consists of a character, which refers to the in-person instructor and also aligns learning outcomes and assessment tasks, using Biggs’ constructive alignment, to the cinematographic and open-source-styled component. In essence, the course's metamorphosis helps students apply the concepts they've studied to actual financial modeling issues. The audio-visual media assets create a storyline throughout the course based on gamified and real-world applications, thus encouraging student engagement and interaction. The structured entanglement of pedagogy and technology also guides the instructor in the design of the in-class interactions and directs the focus on outcomes and assessments. The transformation process of this graduate course in financial modeling led to an institutional teaching award in 2021. The transformation of this course may be used as a model for other courses and programs in many disciplines to help with intended learning outcomes integration, constructive alignment, and Assurance of Learning.

Keywords: innovative education, active learning, entangled pedagogy, heutagogy, constructive alignment, project based learning, financial modeling, graduate business education

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Authors: Marta Fonseca, Pedro Marvão, Beatriz Oliveira, Bruno Heleno, Pedro Carreiro-Martins, Nuno Neuparth, António Rendas

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Background: Concept maps (CMs) visually represent hierarchical connections among related ideas. They foster logical organization and clarify idea relationships, potentially aiding medical students in critical thinking (to think clearly and rationally about what to do or what to believe). However, there are inconsistent claims about the use of CMs in undergraduate medical education. Our three research questions are: 1) What studies have been published on concept mapping in undergraduate medical education? 2) What was the impact of CMs on students’ critical thinking? 3) How and why have these interventions had an educational impact? Methods: Eight databases were systematically searched (plus a manual and an additional search were conducted). After eliminating duplicate entries, titles, and abstracts, and full-texts were independently screened by two authors. Data extraction and quality assessment of the studies were independently performed by two authors. Qualitative and quantitative data were integrated using mixed-methods. The results were reported using the structured approach to the reporting in healthcare education of evidence synthesis statement and BEME guidance. Results: Thirty-nine studies were included from 26 journals (19 quantitative, 8 qualitative and 12 mixed-methods studies). CMs were considered as a tool to promote critical thinking, both in the perception of students and tutors, as well as in assessing students’ knowledge and/or skills. In addition to their role as facilitators of knowledge integration and critical thinking, CMs were considered both teaching and learning methods. Conclusions: CMs are teaching and learning tools which seem to help medical students develop critical thinking. This is due to the flexibility of the tool as a facilitator of knowledge integration, as a learning and teaching method. The wide range of contexts, purposes, and variations in how CMs and instruments to assess critical thinking are used increase our confidence that the positive effects are consistent.

Keywords: concept map, medical education, undergraduate, critical thinking, meaningful learning

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Authors: Ahmad Umar, Ahmed A. Ibrahim, Mohsen A. Alhamami

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This study introduces a facile synthesis method for synthesizing reduced graphene oxide (rGO) nanosheets with surface decoration of polyaniline (PANI). The resultant rGO@PANI nanocomposite (NC) exhibit substantial potential as advanced electrode materials for high-performance supercapacitors. The strategic integration of PANI onto the rGO surface serves dual purposes, effectively mitigating the agglomeration of rGO films and augmenting their utility in supercapacitor applications. The PANI coating manifests a highly porous and nanosized morphology, fostering increased surface area and optimized mass transport by reducing diffusion kinetics. The nanosized structure of PANI contributes to the maximization of active sites, thereby bolstering the efficacy of the nanocomposites for diverse applications. The inherent conductive nature of the rGO surface significantly expedites electron transport, thereby amplifying the overall electrochemical performance of the nanocomposites. To systematically evaluate the influence of PANI concentration on the electrode performance, varying concentrations of PANI were incorporated. Notably, an elevated PANI concentration was found to enhance the response owing to the unique morphology of PANI. Remarkably, the 5% rGO@PANI NC emerged as the most promising candidate, demonstrating exceptional response characteristics with a specific capacitance of 314.2 F/g at a current density of 1 A/g. Furthermore, this catalyst exhibits outstanding long-term stability, retaining approximately 92% of its capacitance even after enduring 4000 cycles. This research underscores the significance of the synergistic integration of rGO and PANI in the design of high-performance supercapacitors. The elucidation of the underlying mechanisms governing the improved electrochemical properties contributes to the fundamental understanding of nanocomposite behavior, thereby paving the way for the rational design of next-generation energy storage materials.

Keywords: reduced graphene oxide, polyaniline, nanocomposites, supercapacitors, energy storage

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Authors: Rishikesh Dingari, Sai Kiran Dornala

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In this paper, a simple method of achieving maximum power by mechanical energy transmission device (METD) with integration to induction generator is proposed. METD functioning is explained and dynamic response of system to step input is plotted. Induction generator is being operated at self-excited mode with excitation capacitor at stator. Voltage and current are observed when linked to METD.

Keywords: mechanical energy transmitting device(METD), self-excited induction generator, wind turbine, hydraulic actuators

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Authors: Messai Amel, Badis Zakaria, Benali-Cherif Nourredine, Dominique Luneaub

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We are interested in molecular polymetallic species having high spin and nuclearities in relation to the field of so call single-molecule magnets (SMMs). The goal is to find a way to synthesis metal clusters which may have application in magnetism and nano sciences. With this purpose, we decided to investigate the coordination chemistry of the Schiff base. Along this way we were able to create cubane-like complexes and elaborate new Single Molecule-Magnets. The idea was to use Schiff base ligands and different metals to generate high nuclear complexes. Complexation of Shiff base with copper (II) has been investigated. Tetra nuclear complex with a cubane like core have been synthesized with (Sciff base), with the same base and cobalt (II) we obtain an other single magnetic complex completely different. In this presentation, we report the synthesis, crystal structure and magnetic properties of the tetranuclear compound (Cu4 L4), and the tetranuclear compound. (Co4L4)

Keywords: cluster-assembled materials, magnetic compounds, Sciff base, cupper, cobalt

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Authors: Sam Zhang

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The landscape of Opto mechatronics is viewed along the line of light vs. matter, photonics vs. semiconductors, and optics vs. mechatronics. Optomechatronics is redefined as the integration of light and matter from the atom, device, and system to the application. The markets and megatrends in Opto mechatronics are further listed. The author then focuses on Opto mechatronic technology in the semiconductor industry as an example and reviews the practical systems, characteristics, and trends. Opto mechatronics, together with photonics and semiconductor, will continue producing the computational and smart infrastructure required for the 4th industrial revolution.

Keywords: photonics, semiconductor, optomechatronics, 4th industrial revolution

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Authors: Andréanne Gagné, Jo Anni Joncas, Éric Tendon

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Teaching in vocational training requires an excellent mastery of the trade being taught, but also solid professional skills in pedagogy. Teachers are typically recruited on the basis of their trade expertise, and they do not necessarily have training or experience in pedagogy. In order to counter this lack, the Ministry of Education (Québec, Canada) requires them to complete a 120-credit university program to obtain their teaching certificate. They must complete this training in addition to their teaching duties. This training was rarely planned in the teacher’s life course, and each teacher approaches it differently: some are enthusiastic, but many feel reluctant discouragement and even frustration at the idea of committing to a training program lasting an average of 10 years to completion. However, Quebec is experiencing an unprecedented shortage of teachers, and the perseverance of vocational teachers in their careers requires special attention because of the conditions of their specific integration conditions. Our research examines the perceptions that vocational teachers in training have of their academic experience in pre-service teaching. It differs from previous research in that it focuses on the influence of the academic experience on the teaching employment experience. The goal is that by better understanding the university experience of teachers in vocational education, we can identify support strategies to support their school experience and their teaching. To do this, the research is based on the theoretical framework of the sociology of experience, which allows us to study the way in which these “teachers-students” give meaning to their university program in articulation with their jobs according to three logics of action. The logic of integration is based on the process of socialization, where the action is preceded by the internalization of values, norms, and cultural models associated with the training context. The logic of strategy refers to the usefulness of this experience where the individual constructs a form of rationality according to his objectives, resources, social position, and situational constraints. The logic of subjectivation refers to reflexivity activities aimed at solving problems and making choices. These logics served as a framework for the development of an online questionnaire. Three hundred respondents, newly enrolled in an undergraduate teaching program (bachelor's degree in vocational education), expressed themselves about their academic experience. This paper relates qualitative data (open-ended questions) subjected to an interpretive repertory analysis approach to descriptive data (closed-ended questions) that emerged. The results shed light on how the respondents perceive themselves as teachers and students, their perceptions of university training and the support offered, and the place that training occupies in their professional path. Indeed, their professional and academic paths are inextricably linked, and it seems essential to take them into account simultaneously to better meet their needs and foster the development of their expertise in pedagogy. The discussion focuses on the strengths and limitations of university training from the perspective of the logic of action. The results also suggest support strategies that can be implemented to better support the integration and retention of student teachers in professional education.

Keywords: teacher, vocational training, pre-service training, academic experience

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