Search results for: feed forward network

Authors: Farid Khosravikia, Patricia Clayton

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The main objective of this work is to evaluate the advantages and disadvantages of various machine learning techniques in two key steps of seismic hazard and risk assessment of different types of structures. The first step is the development of ground-motion models, which are used for forecasting ground-motion intensity measures (IM) given source characteristics, source-to-site distance, and local site condition for future events. IMs such as peak ground acceleration and velocity (PGA and PGV, respectively) as well as 5% damped elastic pseudospectral accelerations at different periods (PSA), are indicators of the strength of shaking at the ground surface. Typically, linear regression-based models, with pre-defined equations and coefficients, are used in ground motion prediction. However, due to the restrictions of the linear regression methods, such models may not capture more complex nonlinear behaviors that exist in the data. Thus, this study comparatively investigates potential benefits from employing other machine learning techniques as statistical method in ground motion prediction such as Artificial Neural Network, Random Forest, and Support Vector Machine. The results indicate the algorithms satisfy some physically sound characteristics such as magnitude scaling distance dependency without requiring pre-defined equations or coefficients. Moreover, it is shown that, when sufficient data is available, all the alternative algorithms tend to provide more accurate estimates compared to the conventional linear regression-based method, and particularly, Random Forest outperforms the other algorithms. However, the conventional method is a better tool when limited data is available. Second, it is investigated how machine learning techniques could be beneficial for developing probabilistic seismic demand models (PSDMs), which provide the relationship between the structural demand responses (e.g., component deformations, accelerations, internal forces, etc.) and the ground motion IMs. In the risk framework, such models are used to develop fragility curves estimating exceeding probability of damage for pre-defined limit states, and therefore, control the reliability of the predictions in the risk assessment. In this study, machine learning algorithms like artificial neural network, random forest, and support vector machine are adopted and trained on the demand parameters to derive PSDMs for them. It is observed that such models can provide more accurate estimates of prediction in relatively shorter about of time compared to conventional methods. Moreover, they can be used for sensitivity analysis of fragility curves with respect to many modeling parameters without necessarily requiring more intense numerical response-history analysis.

Keywords: artificial neural network, machine learning, random forest, seismic risk analysis, seismic hazard analysis, support vector machine

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Authors: Mohammed Ali Faqeeh

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SCADA System Alarms Optimization Process has been introduced recently and applied accordingly in different implemented stages. First, MODBUS communication protocols between RTU/SCADA were improved at the level of I/O points scanning intervals. Then, some of the technical issues related to manufacturing limitations were resolved. Afterward, another approach was followed to take a decision on the configured alarms database. So, a couple of meetings and workshops were held among all system stakeholders, which resulted in an agreement of disabling unnecessary (Diagnostic) alarms. Moreover, a leap forward step was taken to segregate the SCADA Operator Graphics in a way to show only process-related alarms while some other graphics will ensure the availability of field alarms related to maintenance and engineering purposes. This overall system management and optimization have resulted in a huge effective impact on all operations, maintenance, and engineering. It has reduced unneeded open tickets for maintenance crews which led to reduce the driven mileages accordingly. Also, this practice has shown a good impression on the operation reactions and response to the emergency situations as the SCADA operators can be staying much vigilant on the real alarms rather than gets distracted by noisy ones. SCADA System Alarms Optimization process has been executed utilizing all applicable in-house resources among engineering, maintenance, and operations crews. The methodology of the entire enhanced scopes is performed through various stages.

Keywords: SCADA, RTU Communication, alarm management system, SCADA alarms, Modbus, DNP protocol

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Authors: Abduxukur Zayit, Guo Rui Chen

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Universities play important role for develop and distribute sustainable development ideas. This research based on the current situation of large and widely distributed university campuses in China. In view of the deterioration of campus performance, the aging of function and facilities, the large consumption of energy and resources, a logic of "problem-oriented-goal-oriented- At the level, taking the problem orientation as the focus,this paper analyzes the main influencing factors of the existing characteristics of the university campuses, establishes the digital assessment methods and clarifies the key points of the rennovation. Based on the goal orientation, this paper puts forward the existing university campus design principles, builds the green transformation-carding model and sets up the post-use evaluation model. In the end, with dual guidance as the constraint, we will formulate green design standards for campus greening, construct a greening enhancement measure for campus environment, and develop and promote a green campus after-use assessment platform. It provides useful research methods and research ideas for the reconstruction of the existing campus in China, especially the urban universities.

Keywords: design method, existing university campus, green renovation, sustainable development

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Authors: Alev Atak

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In this paper, we aim to create a financial sentiment index by investigating the company’s voluntary information disclosures. We retrieve structured content from BIST 100 companies’ financial reports for the period 1998-2018 and extract relevant financial information for sentiment analysis through Natural Language Processing. We measure strategy-related disclosures and their cross-sectional variation and classify report content into generic sections using synonym lists divided into four main categories according to their liquidity risk profile, risk positions, intra-annual information, and exposure to risk. We use Word Error Rate and Cosin Similarity for comparing and measuring text similarity and derivation in sets of texts. In addition to performing text extraction, we will provide a range of text analysis options, such as the readability metrics, word counts using pre-determined lists (e.g., forward-looking, uncertainty, tone, etc.), and comparison with reference corpus (word, parts of speech and semantic level). Therefore, we create an adequate analytical tool and a financial dictionary to depict the importance of granular financial disclosure for investors to identify correctly the risk-taking behavior and hence make the aggregated effects traceable.

Keywords: financial sentiment, machine learning, information disclosure, risk

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Authors: Akanksha Indora

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Environmental problems are considered a vital social issue in terms of the world’s problems with pollution, environmental degradation, and resource depletion. And populism is about appropriating the social issues according to the social condition for mobilizing a mass and constructing a ‘general will’. Populism encourages a move towards a common cause, it channelizes the emotions of the ‘common people’ towards a nation and nature. The Gandhian ideology has been received as a dominant ideology and the ‘only’ solution to environmental problems. This paper strives to understand the symmetry of environmentalism and Gandhianismi.e., how the debate on the environment in India has been primarily studied through the Gandhian ideology. The Indian Social Sciences visualize the broader issues of the environment from these perspectives, thus, making it a hegemonic approach. Being anti pluralist rhetoric is major rhetoric in the becoming of a populist. This paper shall focus on the idea that how this hegemonic construction of Gandhian ideology in the debates on environmentalism has contributed to the making of anti-pluralistic rhetoric. This anti-pluralistic rhetoric has eliminated the possibility of a pluralistic perspective in the debates on the environment. The quest for a moral inspiration embedded in Gandhianism, whose situatedness is found in the Hindu Social order, seems to have been completely rationalized through the larger politics of knowledge and thus making it appear as the only way forward when it is not.

Keywords: environmental populism, gandhianism, populist rhetoric, environmentalism

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Authors: Javad Taherahmadi, Mohammad Jafarian, Mohammad Naser Asefi

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The global capacity of wind power has dramatically increased in recent years. Therefore, improving the technology of wind turbines to take different advantages of this enormous potential in the power grid, could be interesting subject for scientists. The doubly-fed induction generator (DFIG) wind turbine is a popular system due to its many advantages such as the improved power quality, high energy efficiency and controllability, etc. With an increase in wind power penetration in the network and with regard to the flexible control of wind turbines, the use of wind turbine systems to improve the dynamic stability of power systems has been of significance importance for researchers. Subsynchronous oscillations are one of the important issues in the stability of power systems. Damping subsynchronous oscillations by using wind turbines has been studied in various research efforts, mainly by adding an auxiliary control loop to the control structure of the wind turbine. In most of the studies, this control loop is composed of linear blocks. In this paper, simple adaptive control is used for this purpose. In order to use an adaptive controller, the convergence of the controller should be verified. Since adaptive control parameters tend to optimum values in order to obtain optimum control performance, using this controller will help the wind turbines to have positive contribution in damping the network subsynchronous oscillations at different wind speeds and system operating points. In this paper, the application of simple adaptive control in DFIG wind turbine systems to improve the dynamic stability of power systems is studied and the essential condition for using this controller is considered. It is also shown that this controller has an insignificant effect on the dynamic stability of the wind turbine, itself.

Keywords: almost strictly positive real (ASPR), doubly-fed induction generator (DIFG), simple adaptive control (SAC), subsynchronous oscillations, wind turbine

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Authors: Niroshan K. Walgama Wellalage, Tieling Zhang, Richard Dwight

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State-based Markov deterioration models (SMDM) sometimes fail to find accurate transition probability matrix (TPM) values, and hence lead to invalid future condition prediction or incorrect average deterioration rates mainly due to drawbacks of existing nonlinear optimization-based algorithms and/or subjective function types used for regression analysis. Furthermore, a set of separate functions for each condition state with age cannot be directly derived by using Markov model for a given bridge element group, which however is of interest to industrial partners. This paper presents a new approach for generating Homogeneous SMDM model output, namely, the Modified Weibull approach, which consists of a set of appropriate functions to describe the percentage condition prediction of bridge elements in each state. These functions are combined with Bayesian approach and Metropolis Hasting Algorithm (MHA) based Markov Chain Monte Carlo (MCMC) simulation technique for quantifying the uncertainty in model parameter estimates. In this study, factors contributing to rail bridge deterioration were identified. The inspection data for 1,000 Australian railway bridges over 15 years were reviewed and filtered accordingly based on the real operational experience. Network level deterioration model for a typical bridge element group was developed using the proposed Modified Weibull approach. The condition state predictions obtained from this method were validated using statistical hypothesis tests with a test data set. Results show that the proposed model is able to not only predict the conditions in network-level accurately but also capture the model uncertainties with given confidence interval.

Keywords: bridge deterioration modelling, modified weibull approach, MCMC, metropolis-hasting algorithm, bayesian approach, Markov deterioration models

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Authors: M. Pushparani, A. Sagaya

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Embedded systems have emerged as important elements in various domains with extensive applications in automotive, commercial, consumer, healthcare and transportation markets, as there is emphasis on intelligent devices. On the other hand, Business Intelligence (BI) has also been extensively used in a range of applications, especially in the agriculture domain which is the area of this research. The aim of this research is to create a framework for Embedded Weight Comparison Algorithm with Business Intelligence (EWCA-BI). The weight comparison algorithm will be embedded within the plantation management system and the weighbridge system. This algorithm will be used to estimate the weight at the site and will be compared with the actual weight at the plantation. The algorithm will be used to build the necessary alerts when there is a discrepancy in the weight, thus enabling better decision making. In the current practice, data are collected from various locations in various forms. It is a challenge to consolidate data to obtain timely and accurate information for effective decision making. Adding to this, the unstable network connection leads to difficulty in getting timely accurate information. To overcome the challenges embedding is done on a portable device that will have the embedded weight comparison algorithm to also assist in data capture and synchronize data at various locations overcoming the network short comings at collection points. The EWCA-BI will provide real-time information at any given point of time, thus enabling non-latent BI reports that will provide crucial information to enable efficient operational decision making. This research has a high potential in bringing embedded system into the agriculture industry. EWCA-BI will provide BI reports with accurate information with uncompromised data using an embedded system and provide alerts, therefore, enabling effective operation management decision-making at the site.

Keywords: embedded business intelligence, weight comparison algorithm, oil palm plantation, embedded systems

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Authors: Sajjad Ur Rahman, Muhammad Tahir, Mukarram Bashir, Jawad, Aoun Muhammad, Muhammad Zohaib, Hannan Khan, Seemal Javaid, Mariam Azam

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The efficiency of natural metabolites obtained from partially fermented soya hulls and wheat bran using Saccharomyces cerevisiae (DL-22 S/N) ensures a potential impact on the total milk yield and quality of milk production. On attaining a moderate number of Saccharomyces cerevisiae cells around 1×10⁹ CFU/ml, the concentrate was further elevated under in-vivo conditions to study the quality of milk production in lactating buffalo. Ten lactating buffalos of the Nili Ravi breed having the same physical factors were given 12 gm of microbial metabolites daily, along with the palleted feed having 22 % proteins. Another group of 10 lactating animals with the same characteristics was maintained without metabolites. The body score, overall health, incidence of mastitis, milk fat, milk proteins, ash and solid not fat (SNF) were elevated on a weekly basis up to thirty days of trial. It was recorded that the average total increase in quality milk production was 0.9 liter/h/d, whereas SNF in the milk was enhanced to 0.71, and fats were decreased to 0.09 %. Moreover, during all periods of the trial, the overall non-specific immunity of buffalo was increased, as indicated by less than 0.2 % of mastitis incidence compared to 1.8% in the untreated buffalos.

Keywords: natural metabolites, quality milk, milk yield, microorganisms, fermentation, nonspecific immunity, better performing animals

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Authors: Dalia. G. Aseel, E. E. Hafez, S. M. Hammad

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Viral RNAs of both potato leaf roll virus (PLRV) and potato virus Y (PVY) were extracted from infected potato leaves collected from different Egyptian regions. Differential Display Polymerase Chain Reaction (DD-PCR) using (Endogluconase, β-1,3-glucanases, Chitinase, Peroxidase and Polyphenol oxidase) primers (forward strand) for was performed. The obtained data revealed different banding patterns depending on the viral type and the region of infection. Regarding PLRV, a 58 up regulated and 19 down regulated genes were detected, while, 31 up regulated and 14 down regulated genes were observed in case of PVY. Based on the nucleotide sequencing, variable phylogenetic relationships were reported for the three sequenced genes coding for: Induced stolen tip protein, Disease resistance RPP-like protein and non-specific lipid-transfer protein. In a complementary approach, using the quantitative Real-time PCR, the expressions of PRs genes understudy were estimated in the infected leaves by PLRV and PVY of three potato cultivars (Spunta, Diamont and Cara). The infection with both viruses inhibited the expressions of the five PRs genes. On the contrary, infected leaves by PLRV or PVY elevated the expression of some defense genes. This interaction also may be enhanced and/or inhibited the expression of some genes responsible for the plant defense mechanisms.

Keywords: PLRV, PVY, PR genes, DD-PCR, qRT-PCR, sequencing

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Authors: Vano Benidze, Ioseb Berikashvili

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Since 2003, Georgia has implemented many successful reforms, however, economic growth, poverty alleviation and unemployment reduction are still major challenges facing country’s economy. This is due to the fact that most reforms during the past 2 decades were mainly geared toward improving the institutional environment, while economy’s sectoral composition and industrial policy were largely ignored. Each individual sector plays its own specific role in the functioning of the whole economy that cannot be accomplished by any other sector. However, given the unavoidable reality that one sector uses intermediate inputs from other industries to produce its output and sells part of its output to other sectors, the importance of sectors should consider these sectoral interdependencies as well. Simply put, not all industries are equally useful for economic growth and development. In this context, the aim of this paper is to identify the key economic sectors of the Georgian economy. Leontief input-output analysis has been used in deriving backward and forwards linkages for all sectors in the Georgian economy for 2020 and 2021. Sectors with both high backward and forward linkages have been identified as key sectors of the economy. The results obtained are beneficial for the success of the economic and industrial policy of Georgia. If targeted properly by thoughtful policy intervention, key sectors identified in this paper will have a high potential of spreading growth impulses throughout the economy and will possibly generate higher economic growth.

Keywords: structural change, key sectors, development strategies, input-output analysis

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Authors: Roghaieh Parvizsedghy, Seyyed Mojtaba Sadrameli

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Biodiesel as an alternative diesel fuel is steadily gaining more attention and significance. However, there are some drawbacks while using biodiesel regarding its properties that requires it to be blended with petrol based diesel and/or additives to improve the fuel characteristics. This study analyses thermal cracking as an alternative technology to improve biodiesel characteristics in which, FAME based biodiesel produced by transesterification of castor oil is fed into a continuous thermal cracking reactor at temperatures range of 450-500°C and flowrate range of 20-40 g/hr. Experiments designed by response surface methodology and subsequent statistical studies show that temperature and feed flowrate significantly affect the products yield. Response surfaces were used to study the impact of temperature and flowrate on the product properties. After each experiment, the produced crude bio-oil was distilled and diesel cut was separated. As shorter chain molecules are produced through thermal cracking, the distillation curve of the diesel cut fitted more with petrol based diesel curve in comparison to the biodiesel. Moreover, the produced diesel cut properties adequately pose within property ranges defined by the related standard of petrol based diesel. Cold flow properties, high heating value as the main drawbacks of the biodiesel are improved by this technology. Thermal cracking decreases kinematic viscosity, Flash point and cetane number.

Keywords: biodiesel, castor oil, fuel properties, thermal cracking

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Authors: Catelyn Coyle, Helena Kwakwa

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Objective: As novel and better tolerated therapies become available, effective HCV testing and care models become increasingly necessary to not only identify individuals with active infection but also link them to HCV providers for medical evaluation and treatment. Our aim is to describe an effective HCV testing and linkage to care model piloted in a network of five community health centers located in Philadelphia, PA. Methods: In October 2012, National Nursing Centers Consortium piloted a routine opt-out HCV testing model in a network of community health centers, one of which treats HCV, HIV, and co-infected patients. Key aspects of the model were medical assistant initiated testing, the use of laboratory-based reflex test technology, and electronic medical record modifications to prompt, track, report and facilitate payment of test costs. Universal testing on all adult patients was implemented at health centers serving patients at high-risk for HCV. The other sites integrated high-risk based testing, where patients meeting one or more of the CDC testing recommendation risk factors or had a history of homelessness were eligible for HCV testing. Mid-course adjustments included the integration of dual HIV testing, development of a linkage to care coordinator position to facilitate the transition of HIV and/or HCV-positive patients from primary to specialist care, and the transition to universal HCV testing across all testing sites. Results: From October 2012 to June 2015, the health centers performed 7,730 HCV tests and identified 886 (11.5%) patients with a positive HCV-antibody test. Of those with positive HCV-antibody tests, 838 (94.6%) had an HCV-RNA confirmatory test and 590 (70.4%) progressed to current HCV infection (overall prevalence=7.6%); 524 (88.8%) received their RNA-positive test result; 429 (72.7%) were referred to an HCV care specialist and 271 (45.9%) were seen by the HCV care specialist. The best linkage to care results were seen at the test and treat the site, where of the 333 patients were current HCV infection, 175 (52.6%) were seen by an HCV care specialist. Of the patients with active HCV infection, 349 (59.2%) were unaware of their HCV-positive status at the time of diagnosis. Since the integration of dual HCV/HIV testing in September 2013, 9,506 HIV tests were performed, 85 (0.9%) patients had positive HIV tests, 81 (95.3%) received their confirmed HIV test result and 77 (90.6%) were linked to HIV care. Dual HCV/HIV testing increased the number of HCV tests performed by 362 between the 9 months preceding dual testing and first 9 months after dual testing integration, representing a 23.7% increment. Conclusion: Our HCV testing model shows that integrated routine testing and linkage to care is feasible and improved detection and linkage to care in a primary care setting. We found that prevalence of current HCV infection was higher than that seen in locally in Philadelphia and nationwide. Intensive linkage services can increase the number of patients who successfully navigate the HCV treatment cascade. The linkage to care coordinator position is an important position that acts as a trusted intermediary for patients being linked to care.

Keywords: HCV, routine testing, linkage to care, community health centers

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Authors: Namugenyi Ephrance Eunice, Julianne Sansa Otim, Marco Zennaro, Stephen D. Wolthusen

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The Internet of Things (IoT) is a network of connected data processing devices, mechanical and digital machinery, items, animals, or people that may send data across a network without requiring human-to-human or human-to-computer interaction. Each component has sensors that can pick up on specific phenomena, as well as processing software and other technologies that can link to and communicate with other systems and/or devices over the Internet or other communication networks and exchange data with them. IoT is increasingly being used in fields other than consumer electronics, such as public safety, emergency response, industrial automation, autonomous vehicles, the Internet of Medical Things (IoMT), and general environmental monitoring. Consumer-based IoT applications, like smart home gadgets and wearables, are also becoming more prevalent. This paper presents the main IoT deployment areas for environmental monitoring in developing regions and the backhaul options suitable for them. A detailed review of each of the list of papers selected for the study is included in section III of this document. The study includes an overview of existing IoT deployments, the underlying communication architectures, protocols, and technologies that support them. This overview shows that Low Power Wireless Area Networks (LPWANs), as summarized in Table 1, are very well suited for monitoring environment architectures designed for remote locations. LoRa technology, particularly the LoRaWAN protocol, has an advantage over other technologies due to its low power consumption, adaptability, and suitable communication range. The prevailing challenges of the different architectures are discussed and summarized in Table 3 of the IV section, where the main problem is the obstruction of communication paths by buildings, trees, hills, etc.

Keywords: communication technologies, environmental monitoring, Internet of Things, IoT deployment challenges

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Authors: Nadir Atayev, Mehman Hasanov

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Future spacecraft will require a structural change in the way data is transmitted due to the increase in the volume of data required for space communication. Current radio frequency communication systems are already facing a bottleneck in the volume of data sent to the ground segment due to their technological and regulatory characteristics. To overcome these issues, free space optics communication plays an important role in the integrated terrestrial space network due to its advantages such as significantly improved data rate compared to traditional RF technology, low cost, improved security, and inter-satellite free space communication, as well as uses a laser beam, which is an optical signal carrier to establish satellite-ground & ground-to-satellite links. In this approach, there is a need for high-speed and energy-efficient systems as a base platform for sending high-volume video & audio data. Nano Satellite and its branch CubeSat platforms have more technical functionality than large satellites, wheres cover an important part of the space sector, with their Low-Earth-Orbit application area with low-cost design and technical functionality for building networks using different communication topologies. Along the research theme developed in this regard, the output parameter indicators for the FSO of the optical communication transceiver subsystem on the existing CubeSat platforms, and in the direction of improving the mentioned parameters of this communication methodology, 3D optical switch and laser beam controlled optical transponder with 2U CubeSat structural subsystems and application in the Low Earth Orbit satellite network topology, as well as its functional performance and structural parameters, has been studied accordingly.

Keywords: cubesat, free space optics, nano satellite, optical laser communication.

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Authors: Muhammad Zaheer Awan, Adnan Qadir, Zeeshan Anjum

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Housefly, Musca domestica Linnaeus is ubiquitous and hazardous for Homo sapiens and livestock in sundry venerations. Musca domestica cart 100 different pathogens, such as typhoid, salmonella, bacillary dysentery, tuberculosis, anthrax and parasitic worms. The flies in rural areas usually carry more pathogens. Houseflies feed on liquid or semi-liquid substances besides solid materials which are softened by saliva. Neem botanically known as Azadirachta indica belongs to the family Meliaceae and is an indigenous tree to Pakistan. The neem tree is also one such tree which has been revered by the Pakistanis and Kashmiris for its medicinal properties. Present study showed neem seed extract has potentially toxic ability that affect Total Haemocyte Count (THC) and Differential Haemocytes Count (DHC) in insect’s blood cells, of the housefly. A significant variation in haemolymph density was observed just after application, 30 minutes and 60 minutes post treatment in term of THC and DHC in comparison with novastar. The study strappingly acclaim use of neem seed extract as insecticide as compare to artificial insecticides.

Keywords: neem, Azadirachta indica, Musca domestica, differential haemocyte count (DHC), total haemocytes count (DHC), novastar

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Authors: Munir Majdalawieh, Adam Marks

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In today’s very competitive higher education industry (HEI), HEIs are faced with the primary concern of developing, deploying, and sustaining high quality academic programs. Today, the HEI has well-established accreditation systems endorsed by a country’s legislation and institutions. The accreditation system is an educational pathway focused on the criteria and processes for evaluating educational programs. Although many aspects of the accreditation process highlight both the past and the present (prove), the “program review” assessment is "forward-looking assessment" (improve) and thus transforms the process into a continuing assessment activity rather than a periodic event. The purpose of this study is to propose a conceptual measurement framework for program review to be used by HEIs to undertake a robust and targeted approach to proactively and continuously review their academic programs to evaluate its practicality and effectiveness as well as to improve the education of the students. The proposed framework consists of two main components: program review principles and the program review measurement matrix.

Keywords: academic program, program review principles, curriculum development, accreditation, evaluation, assessment, review measurement matrix, program review process, information technologies supporting learning, learning/teaching methodologies and assessment

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Authors: Athena Pedro, Laura Bradfield, Mike Dare, Zandile Bantwana, Ashley Nayman

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The purpose of the research was to explore mother’s unique experience and knowledge of mothering in the first 1000 day of their child’s life, from birth to age 2. The study used a qualitative research methodology with an exploratory research design. A sample of 12 mothers was used, comprising different racial backgrounds from low income areas in the Western Cape. The data was collected by means of semi-structured, in-depth interviews, which were transcribed verbatim, analysed using Braun’s and Clark’s (2006) six phases of thematic analysis. Some of the findings revealed that the mothers who participated in the study were consistently unable to feed their children and themselves due to profound and extreme situations of poverty, stress, and lack of infrastructural support. These mothers residing in low-income communities are not adequately supported both financially and socially and are often unable to meet the needs of their infants within the first 1000 days. Given the consequential nature of this period, it is imperative that mothers are able to access such support. Single mothers especially are in need of social and financial support. Appropriate interventions are required to assist mothers generally but more specifically, mothers who have children within the first 1000 days of life. By implementing appropriate interventions to address these needs, it will assist mothers to ensure optimal developmental growth of their children. This will positively impact the developmental trajectory of children in South Africa.

Keywords: caring, economic hardship, first one thousand days, mothers

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Authors: Yoonjung An, Yongtae Park

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Knowledge flows are a critical source of faster technological progress and stouter economic growth. Knowledge flows have been accelerated dramatically with the establishment of a patent system in which each patent is required by law to disclose sufficient technical information for the invention to be recreated. Patent analysis, thus, has been widely used to help investigate technological knowledge flows. However, the existing research is limited in terms of both subject and approach. Particularly, in most of the previous studies, business method (BM) patents were not covered although they are important drivers of knowledge flows as other patents. In addition, these studies usually focus on the static analysis of knowledge flows. Some use approaches that incorporate the time dimension, yet they still fail to trace a true dynamic process of knowledge flows. Therefore, we investigate dynamic patterns of knowledge flows driven by BM patents using a Hidden Markov Model (HMM). An HMM is a popular statistical tool for modeling a wide range of time series data, with no general theoretical limit in regard to statistical pattern classification. Accordingly, it enables characterizing knowledge patterns that may differ by patent, sector, country and so on. We run the model in sets of backward citations and forward citations to compare the patterns of knowledge utilization and knowledge dissemination.

Keywords: business method patents, dynamic pattern, Hidden-Markov Model, knowledge flow

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Authors: M. N. Islam, B. Boswell, Y. R. Ginting

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The influence of canned cycles and cutting parameters on hole quality in cryogenic drilling has been investigated experimentally and analytically. A three-level, three-parameter experiment was conducted by using the design-of-experiment methodology. The three levels of independent input parameters were the following: for canned cycles—a chip-breaking canned cycle (G73), a spot drilling canned cycle (G81), and a deep hole canned cycle (G83); for feed rates—0.2, 0.3, and 0.4 mm/rev; and for cutting speeds—60, 75, and 100 m/min. The selected work and tool materials were aluminum 6061-6T and high-speed steel (HSS), respectively. For cryogenic cooling, liquid nitrogen (LN2) was used and was applied externally. The measured output parameters were the three widely used quality characteristics of drilled holes—diameter error, circularity, and surface roughness. Pareto ANOVA was applied for analyzing the results. The findings revealed that the canned cycle has a significant effect on diameter error (contribution ratio 44.09%) and small effects on circularity and surface finish (contribution ratio 7.25% and 6.60%, respectively). The best results for the dimensional accuracy and surface roughness were achieved by G81. G73 produced the best circularity results; however, for dimensional accuracy, it was the worst level.

Keywords: circularity, diameter error, drilling canned cycle, pareto ANOVA, surface roughness

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Authors: Hang Yang, Jichao Li, Kewei Yang, Tianyang Lei

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Multivariate time series anomaly detection is a significant research topic in the field of data mining, encompassing a wide range of applications across various industrial sectors such as traffic roads, financial logistics, and corporate production. The inherent spatial dependencies and temporal characteristics present in multivariate time series introduce challenges to the anomaly detection task. Previous studies have typically been based on the assumption that all variables belong to the same spatial hierarchy, neglecting the multi-level spatial relationships. To address this challenge, this paper proposes a multi-scale spatial and unified temporal feature fusion network, denoted as MSUT-Net, for multivariate time series anomaly detection. The proposed model employs a multi-level modeling approach, incorporating both temporal and spatial modules. The spatial module is designed to capture the spatial characteristics of multivariate time series data, utilizing an adaptive graph structure learning model to identify the multi-level spatial relationships between data variables and their attributes. The temporal module consists of a unified temporal processing module, which is tasked with capturing the temporal features of multivariate time series. This module is capable of simultaneously identifying temporal dependencies among different variables. Extensive testing on multiple publicly available datasets confirms that MSUT-Net achieves superior performance on the majority of datasets. Our method is able to model and accurately detect systems data with multi-level spatial relationships from a spatial-temporal perspective, providing a novel perspective for anomaly detection analysis.

Keywords: data mining, industrial system, multivariate time series, anomaly detection

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Authors: Melissa Lubitz

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Water scarcity is one of the crucial challenges of our time. There needs to be a focus on creating a society where people and nature flourish, regardless of climatic conditions. One of the solutions we can look to is decentralized greywater recycling. The vision is simple. Every building has its own water source being greywater from the bath, shower, sink and washing machine. By treating this in the home, you can save 25-45% of potable water use and wastewater production, a reduction in energy consumption and CO2 emissions. This reusable water is clean, and safe to be used for toilet flushing, washing machine, and outdoor irrigation. Companies like Hydraloop have been committed to the greywater recycle-ready building concept for years. This means that drinking water conservation and water reuse are included as standards in the design of all new buildings. Sustainability and renewal go hand in hand. This vision includes not only optimizing water savings and waste reduction but also forging strong partnerships that bring this ambition to life. Together with regulators, municipalities and builders, a sustainable and water-conscious future is pursued. This is an opportunity to be part of a movement that is making a difference. By pushing this initiative forward, we become part of a growing community that resists dehydration, believes in sustainability, and is committed to a living environment at the forefront of change: sustainable living, where saving water is the norm and where we shape the future together.

Keywords: greywater, wastewater treatment, water conservation, circular water society

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Authors: Shahed Vahedi, Mohd Salmi Md Noorani

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This paper investigates cluster synchronization phenomena between community networks. We focus on the situation where a variety of dynamics occur in the clusters. In particular, we show that different synchronization states simultaneously occur between the networks. The controller is designed having an adaptive control gain, and theoretical results are derived via Lyapunov stability. Simulations on well-known dynamical systems are provided to elucidate our results.

Keywords: cluster synchronization, adaptive control, community network, simulation

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Authors: Sangita Pokhrel, Nalinda Somasiri, Rebecca Jeyavadhanam, Swathi Ganesan

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Tourism is a booming industry with huge future potential for global wealth and employment. There are countless data generated over social media sites every day, creating numerous opportunities to bring more insights to decision-makers. The integration of Big Data Technology into the tourism industry will allow companies to conclude where their customers have been and what they like. This information can then be used by businesses, such as those in charge of managing visitor centers or hotels, etc., and the tourist can get a clear idea of places before visiting. The technical perspective of natural language is processed by analysing the sentiment features of online reviews from tourists, and we then supply an enhanced long short-term memory (LSTM) framework for sentiment feature extraction of travel reviews. We have constructed a web review database using a crawler and web scraping technique for experimental validation to evaluate the effectiveness of our methodology. The text form of sentences was first classified through Vader and Roberta model to get the polarity of the reviews. In this paper, we have conducted study methods for feature extraction, such as Count Vectorization and TFIDF Vectorization, and implemented Convolutional Neural Network (CNN) classifier algorithm for the sentiment analysis to decide the tourist’s attitude towards the destinations is positive, negative, or simply neutral based on the review text that they posted online. The results demonstrated that from the CNN algorithm, after pre-processing and cleaning the dataset, we received an accuracy of 96.12% for the positive and negative sentiment analysis.

Keywords: counter vectorization, convolutional neural network, crawler, data technology, long short-term memory, web scraping, sentiment analysis

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Authors: Qiong Hu, Ming Yue

Abstract:

Language variation signals the newest usage of language community, which might become the developmental trend of that language. However, language textbooks cannot keep up with these emergent usages. Most Chinese English learners nowadays are still exposed to traditional grammar prescribed in the textbook so that some variational usages cannot be acquired. The personal pronoun we is prescribed as a plural pronoun in the textbook grammar, but its number value is more flexible in actual use. Based on the Chinese Learner English Corpus (CLEC), and with the homemade Friends corpus as reference, the present research explores the number value of the first person pronoun we used by Chinese English learners. With consideration of the subjectivity of we, this paper annotated the number value of all the wes in “we+ PCU (Perception-cognation-utterance) verbs” collocations. Results show that though exposed to traditional textbooks which prescribe the plural reference of we, there still exists some unconventional usage (singular or vague in reference) in the writings of Chinese English learners, which is less frequent than that of the native speeches. Corpus data and results from manual semantic annotation show that this could be due to the impact of formulaic sequence on the learners and the positive transfer from their native language. An improved SLA model of native language, target language and interlanguage is put forward to recognize the existence of variation in second language acquisition, which should be given more attention during teaching.

Keywords: Chinese English learners, number, PCU verbs, Personal pronoun we

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Authors: Mehmet Akoz, Mustafa Kul

Abstract:

Ewes and goats are seasonally polyestrus animals. Their reproductive activities are associated with the reduction or extending of daylight. Melatonin releasing from pineal gland regulates the sexual activities depending on daylight. In recent years, number of ewes decreased in our country. This situation dispatched to developing of some methods to increase productivity. Small ruminants can be synchronized with the natural and medical methods. known methods from natural light set with ram and goat participation. The most important natural methods of male influence, daylight is regulated and feed. On the other hand, progestagens, PGF2α, melatonin, and gonadotropins are commonly used for the purpose of estrus synchranization. But it is not effective PGF2α anestrous season The short-term and long-term progesterone treatment was effective to synchronize estrus in small ruminats during both breeding and anestrus seasons. Alternative choices of progesterone/progestagen have been controlled internal drug release (CIDR) devices, supplying natural progesterone, norgestomet implants, and orally active melengestrol acetate Melatonin anestrous season and should be applied during the transition period, but the season can be synchronized. Estrus synchronisation shortens anestrus season, decreases labor for mating/insemination and estrus pursuit, and induces multiple pregnancies.

Keywords: ewes, goat, synchronization, progestagen, PGF2α

Procedia PDF Downloads 344

Authors: Shayli Varasteh Moradi, Wayne A. Johnston, Dejan Gagoski, Kirill Alexandrov

Abstract:

The demand for a rapid and more efficient technique to identify protein-protein interaction particularly in the areas of therapeutics and diagnostics development is growing. The method described here is a rapid in vitro protein-protein interaction analysis approach based on AlphaLISA technology combined with Leishmania tarentolae cell-free protein production (LTE) system. Cell-free protein synthesis allows the rapid production of recombinant proteins in a multiplexed format. Among available in vitro expression systems, LTE offers several advantages over other eukaryotic cell-free systems. It is based on a fast growing fermentable organism that is inexpensive in cultivation and lysate production. High integrity of proteins produced in this system and the ability to co-express multiple proteins makes it a desirable method for screening protein interactions. Following the translation of protein pairs in LTE system, the physical interaction between proteins of interests is analysed by AlphaLISA assay. The assay is performed using unpurified in vitro translation reaction and therefore can be readily multiplexed. This approach can be used in various research applications such as epitope mapping, antigen-antibody analysis and protein interaction network mapping. The intra-viral protein interaction network of Zika virus was studied using the developed technique. The viral proteins were co-expressed pair-wise in LTE and all possible interactions among viral proteins were tested using AlphaLISA. The assay resulted to the identification of 54 intra-viral protein-protein interactions from which 19 binary interactions were found to be novel. The presented technique provides a powerful tool for rapid analysis of protein-protein interaction with high sensitivity and throughput.

Keywords: AlphaLISA technology, cell-free protein expression, epitope mapping, Leishmania tarentolae, protein-protein interaction

Procedia PDF Downloads 240

Authors: Dušica L. Marić, Mirela Erić, Dušan M. Maić, Nebojša T. Milošević, Dragana Radošević, Nikola Vučinić

Abstract:

The anatomical existence of transforaminal ligaments has been studied widely. The crucial anatomic study of these structures describes the transforaminal ligaments as an anomalous structure. The ligaments associated with the intervertebral foramen were classified in the external, intraforaminal and internal foraminal ligaments. The external ligaments are the most frequently reported type of transforaminal ligaments in adult spine. The purpose of this study was to examine the appearance of the ligaments within the external space of the intervertebral foramen in adult cadavers. External transforaminal ligaments branch out forward from the root of the transverse process toward the vertebral body with superior, transverse and inferior directions. The ligament detected in the study was different from the other reported descriptions of L1 foraminal ligaments. This ligament extends from the root of the pedicle to the inferior border of the vertebral body below the level of the disc and forms the compartment through which pass the ventral root of the spinal nerve and a small branch of the spinal artery. The results of this study show that the external ligaments can be clearly macroscopic visualized, and it is very important to have prior knowledge of the cadaveric specimens, to identify these structures. The presence of these ligaments is clinically important. These ligaments could be the cause of nerve root compression and the low back syndrome.

Keywords: anatomy, ligaments, lumbar spine, spinal nerve roots

Procedia PDF Downloads 334

Authors: Matthew Brady

Abstract:

Lack of affordable housing for individuals has the potential to create gaps in society, which result in thousands of people facing homelessness every year in some of the worlds most affluent cities. This paper examines strategies for providing a more economic living environment for single occupants. Focusing on comparisons of successful examples reducing homeless populations around the world, with an emphasis on social inclusion and community living. Practically exploring the architectural considerations of ensuring a suitable living environment for multiple single occupancy residents, as well as selecting the appropriate materials to ensure costs are kept to manageable level for investment from local governments. The aim of this paper is to make some practical recommendations for low cost communal living space, with particular reference to recycled shipping container homes on a potential unused site on the River Clyde in Glasgow. Ideally, the suggestions and recommendations put forward in this paper can be replicable or used for reference in other similar situations. The proposal explored in this paper is sensitive towards addressing people's standard of living and adapting homes to match may be one solution to reducing the number of people being evicted from unaffordable homes as the generally upward global trend for urbanization continues.

Keywords: affordable housing, community living, shipping container, urban regeneration

Procedia PDF Downloads 184

Authors: Sergio A. Navarro Tuch, Martin Rogelio Bustamante Bello, Leopoldo Julian Lechuga Lopez

Abstract:

In recent years, Mexico’s population has seen a rise of different physiological and mental negative states. Two main consequences of this problematic are deficient work performance and high levels of stress generating and important impact on a person’s physical, mental and emotional health. Several approaches, such as the use of audiovisual stimulus to induce emotions and modify a person’s emotional state, can be applied in an effort to decreases these negative effects. With the use of different non-invasive physiological sensors such as EEG, luminosity and face recognition we gather information of the subject’s current emotional state. In a controlled environment, a subject is shown a series of selected images from the International Affective Picture System (IAPS) in order to induce a specific set of emotions and obtain information from the sensors. The raw data obtained is statistically analyzed in order to filter only the specific groups of information that relate to a subject’s emotions and current values of the physical variables in the controlled environment such as, luminosity, RGB light color, temperature, oxygen level and noise. Finally, a neural network based control algorithm is given the data obtained in order to feedback the system and automate the modification of the environment variables and audiovisual content shown in an effort that these changes can positively alter the subject’s emotional state. During the research, it was found that the light color was directly related to the type of impact generated by the audiovisual content on the subject’s emotional state. Red illumination increased the impact of violent images and green illumination along with relaxing images decreased the subject’s levels of anxiety. Specific differences between men and women were found as to which type of images generated a greater impact in either gender. The population sample was mainly constituted by college students whose data analysis showed a decreased sensibility to violence towards humans. Despite the early stage of the control algorithm, the results obtained from the population sample give us a better insight into the possibilities of emotional domotics and the applications that can be created towards the improvement of performance in people’s lives. The objective of this research is to create a positive impact with the application of technology to everyday activities; nonetheless, an ethical problem arises since this can also be applied to control a person’s emotions and shift their decision making.

Keywords: data analysis, emotional domotics, performance improvement, neural network

Procedia PDF Downloads 143