Search results for: network identification

Authors: Anthara Vivek, Manisha Shukla, Mahesh Narayan, Prakash Narayan

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Sickle cell disease disproportionately affects sub-Saharan Africa and certain tribal populaces in India and has consequently drawn little intertest from Pharma. In sickle cell patients, adhesion of erythrocytes or reticulocytes to one another and the vessel wall results in painful ischemic episodes with few, if any, effective treatments for vaso-occlusive crises. Identification of disease-associated adhesion markers on erythrocytes or reticulocytes might inform the use of more effective therapies against vaso-occlusive crises. Increased expression of one or more of bcam, itga4, cd44, cd47, rap1a, vcam1, or icam4 has been reported in sickle cell subjects. Using the miRNet ontology knowledgebase, peripheral blood interactomes were generated by seeding various combinations of the afore-referenced mRNA. These interactomes yielded an array of miR targets. As examples, targeting hsa-miR-155-5p can potentially neutralize the rap1a-bcam-cd44-itga4-vcam1 erythrocyte/reticulocyte adhesion interactome whereas targeting hsa-miRs-103a-3p or 107 can potentially neutralize adhesion in cells overexpressing icam4-cd47-bcam-itga4-cd36. AM3380 (MIRacle™) is an off-the shelf hsa-miR-155-5p agomiR that can potentially neutralize the rap1a-bcam-cd44-itga4-vcam1 signaling axis. Phlebotomy coupled with transcriptomics represents a potentially feasible and effective precision medicine strategy to mitigate vaso-occlusive crises in sickle cell patients.

Keywords: adhesion, interactome, precision, medicine

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Authors: Nyla Anjum, Humaira Bano

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Disability, regardless of its type and nature limits one or two significant life activities. These limitations constitute risk factors for suicide. Rate and intensity of problem upsurges in critical age of adolescence. Researches in the field of mental health over look problem of suicide among persons with disability. Aim of the study was to investigate prevalence and risk factors for suicide among adolescents with disability. The study constitutes purposive sample of 106 elements of both gender with four major categories of disability: hearing impairment, physical impairment, visual impairment and intellectual disabilities. Face to face interview technique was opted for data collection. Other variable are: socio-economic status, social and family support, provision of services for persons with disability, education and employment opportunities. For data analysis independent sample t-test was applied to find out significant differences in gender and One Way Analysis of variance was run to find out differences among four types of disability. Major predictors of suicide were identified with multiple regression analysis. It is concluded that ideation, plans and attempts of suicide among adolescents with disability is a multifaceted and imperative concern in the area of mental health. Urgent research recommendations contains valid measurement of suicide rate and identification of more risk factors for suicide among persons with disability. Study will also guide towards prevention of this pressing problem and will bring message of happy and healthy life not only for persons with disability but also for their families. It will also help to reduce suicide rate in society.

Keywords: suicide, risk factors, adolescent, disability, mental health

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Authors: Amrita Anil Agashe, Sumant Tapas, Ajay Verma Yogesh Sonavane, Sourabh Yeravar

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Due to advancement in MEMS technology today wireless sensors network has gained a lot of importance. The wide range of its applications includes environmental and habitat monitoring, object localization, target tracking, security surveillance etc. Wireless sensor networks consist of tiny sensor devices called as motes. The constrained computation power, battery power, storage capacity and communication bandwidth of the tiny motes pose challenging problems in the design and deployment of such systems. In this paper, we propose a ubiquitous framework for Real-Time Tracking, Sensing and Management System using IITH motes. Also, we explain the algorithm that we have developed for location management in wireless sensor networks with the aspect of mobility. Our developed framework and algorithm can be used to detect emergency events and safety threats and provides warning signals to handle the emergency.

Keywords: mobility management, motes, multihop, wireless sensor networks

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Authors: Iqraq Kamal, Akmal Razif, Sivadas Chandra Sekaran, Ahmad Syazwan Hisaburi

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Painting plays a crucial role in the aerospace manufacturing industry, serving both protective and cosmetic purposes for components. However, the traditional manual painting method is time-consuming and labor-intensive, posing challenges for the sector in achieving higher efficiency. Additionally, the current automated robot path planning has been a bottleneck for spray painting processes, as typical manual teaching methods are time-consuming, error-prone, and skill-dependent. Therefore, it is essential to develop automated tool path planning methods to replace manual ones, reducing costs and improving product quality. Focusing on flat panel painting in aerospace manufacturing, this study aims to address issues related to unreliable part identification techniques caused by the high-mixture, low-volume nature of the industry. The proposed solution involves using a spray gun and a UR10 robotic arm with a vision system that utilizes one-shot object detection (OS2D) to identify parts accurately. Additionally, the research optimizes path planning by concentrating on the region of interest—specifically, the identified part, rather than uniformly covering the entire painting tray.

Keywords: aerospace manufacturing, one-shot object detection, automated spray painting, vision-based path optimization, deep learning, automation, robotic arm

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Authors: Bernardo Cedano, Ahmed H. Eltom, Bob Hay, Jim Glass, Raga Ahmed

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The deployment of smart grid devices such as smart meters and smart switches (SS) supported by a reliable and fast communications system makes automated distribution possible, and thus, provides great benefits to electric power consumers and providers alike. However, more research is needed before the full utility of smart switch data is realized. This paper presents new automated switching techniques using SS within the electric power grid. A concise background of the SS is provided, and operational examples are shown. Organization and presentation of data obtained from SS are shown in the context of the future goal of total automation of the distribution network. The description of application techniques, the examples of success with SS, and the vision outlined in this paper serve to motivate future research pertinent to disturbance analysis automation.

Keywords: disturbance automation, electric power grid, smart grid, smart switches

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Authors: Pau Rodriguez, Jordi Gonzalez, Josep M. Gonfaus, Xavier Roca

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Image sharing in social networks has increased exponentially in the past years. Officially, there are 600 million Instagrammers uploading around 100 million photos and videos per day. Consequently, there is a need for developing new tools to understand the content expressed in shared images, which will greatly benefit social media communication and will enable broad and promising applications in education, advertisement, entertainment, and also psychology. Following these trends, our work aims to take advantage of the existing relationship between text and personality, already demonstrated by multiple researchers, so that we can prove that there exists a relationship between images and personality as well. To achieve this goal, we consider that images posted on social networks are typically conditioned on specific words, or hashtags, therefore any relationship between text and personality can also be observed with those posted images. Our proposal makes use of the most recent image understanding models based on neural networks to process the vast amount of data generated by social users to determine those images most correlated with personality traits. The final aim is to train a weakly-supervised image-based model for personality assessment that can be used even when textual data is not available, which is an increasing trend. The procedure is described next: we explore the images directly publicly shared by users based on those accompanying texts or hashtags most strongly related to personality traits as described by the OCEAN model. These images will be used for personality prediction since they have the potential to convey more complex ideas, concepts, and emotions. As a result, the use of images in personality questionnaires will provide a deeper understanding of respondents than through words alone. In other words, from the images posted with specific tags, we train a deep learning model based on neural networks, that learns to extract a personality representation from a picture and use it to automatically find the personality that best explains such a picture. Subsequently, a deep neural network model is learned from thousands of images associated with hashtags correlated to OCEAN traits. We then analyze the network activations to identify those pictures that maximally activate the neurons: the most characteristic visual features per personality trait will thus emerge since the filters of the convolutional layers of the neural model are learned to be optimally activated depending on each personality trait. For example, among the pictures that maximally activate the high Openness trait, we can see pictures of books, the moon, and the sky. For high Conscientiousness, most of the images are photographs of food, especially healthy food. The high Extraversion output is mostly activated by pictures of a lot of people. In high Agreeableness images, we mostly see flower pictures. Lastly, in the Neuroticism trait, we observe that the high score is maximally activated by animal pets like cats or dogs. In summary, despite the huge intra-class and inter-class variabilities of the images associated to each OCEAN traits, we found that there are consistencies between visual patterns of those images whose hashtags are most correlated to each trait.

Keywords: emotions and effects of mood, social impact theory in social psychology, social influence, social structure and social networks

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Authors: D. S. Malatesh, K. J. Ananda, C. Ansar Kamran, K. Ganesh Udupa

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Dirofilaria repens is a mosquito-borne filarioid nematode of dogs and other carnivores and accidentally affects humans. D. repens is reported in many countries, including India. Subcutaneous dirofilariosis caused by D. repens is a zoonotic disease, widely distributed throughout Europe, Asia, and Africa, with higher prevalence reported in dogs from Sri Lanka (30-60%), Iran (61%) and Italy (21-25%). Dirofilariasis in dogs was diagnosed by detection of microfilariae in blood. Identification of different Dirofilaria species was done by using molecular methods like polymerase chain reaction (PCR). Even though many researchers reported molecular evidence of D. repens across India, to our best knowledge there is no data available on molecular diagnosis of D. repens in dogs and its zoonotic implication in Karnataka state a southern state in India. The aim of the present study was to identify the Dirofilaria species occurring in dogs from Karnataka, India. Out of 310 samples screened for the presence of microfilariae using traditional diagnostic methods, 99 (31.93%) were positive for the presence of microfilariae. Based on the morphometry, the microfilariae were identified as D. repens. For confirmation of species, the samples were subjected to PCR using pan filarial primers (DIDR-F1, DIDR-R1) for amplification of internal transcribed spacer region 2 (ITS2) of the ribosomal DNA. The PCR product of 484 base pairs on agarose gel was indicative of D. repens. Hence, a single PCR reaction using pan filarial primers can be used to differentiate filarial species found in dogs. The present study confirms that dirofilarial species occurring in dogs from Karnataka is D. repens and further sequencing studies are needed for genotypic characterization of D. repens.

Keywords: Dirofilaria repens, molecular characterization, polymerase chain reaction, Karnataka, India

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Authors: Jonardan Koner, Avinash Purandare

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In today’s globalized world international business is a very key area for the country's growth. Some of the strategic areas for holding up a country’s international business to grow are in the areas of connecting Ports, Road Network, and Rail Network. India’s International Business is booming both in Exports as well as Imports. Ports play a very central part in the growth of international trade and ensuring competitive ports is of critical importance. India has a long coastline which is a big asset for the country as it has given the opportunity for development of a large number of major and minor ports which will contribute to the maritime trades’ development. The National Economic Development of India requires a well-functioning seaport system. To know the comparative strength of Indian ports over South-east Asian similar ports, the study is considering the objectives of (I) to identify the key parameters of an international mega container port, (II) to compare the five selected container ports (JNPT, Chennai, Singapore, Dubai, and Colombo Ports) according to user of the ports and iii) to measure the growth of selected five container ports’ throughput over time and their comparison. The study is based on both primary and secondary databases. The linear time trend analysis is done to show the trend in quantum of exports, imports and total goods/services handled by individual ports over the years. The comparative trend analysis is done for the selected five ports of cargo traffic handled in terms of Tonnage (weight) and number of containers (TEU’s). The comparative trend analysis is done between containerized and non-containerized cargo traffic in the five selected five ports. The primary data analysis is done comprising of comparative analysis of factor ratings through bar diagrams, statistical inference of factor ratings for the selected five ports, consolidated comparative line charts of factor rating for the selected five ports, consolidated comparative bar charts of factor ratings of the selected five ports and the distribution of ratings (frequency terms). The linear regression model is used to forecast the container capacities required for JNPT Port and Chennai Port by the year 2030. Multiple regression analysis is carried out to measure the impact of selected 34 explanatory variables on the ‘Overall Performance of the Port’ for each of the selected five ports. The research outcome is of high significance to the stakeholders of Indian container handling ports. Indian container port of JNPT and Chennai are benchmarked against international ports such as Singapore, Dubai, and Colombo Ports which are the competing ports in the neighbouring region. The study has analysed the feedback ratings for the selected 35 factors regarding physical infrastructure and services rendered to the port users. This feedback would provide valuable data for carrying out improvements in the facilities provided to the port users. These installations would help the ports’ users to carry out their work in more efficient manner.

Keywords: throughput, twenty equivalent units, TEUs, cargo traffic, shipping lines, freight forwarders

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Authors: N. Chérif, T. Allaoui, M. Benasla, H. Chaib

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Industrialization and population growth are the prime factors for which the consumption of electricity is steadily increasing. Thus, to have a balance between production and consumption, it is necessary at first to increase the number of power plants, lines and transformers, which implies an increase in cost and environmental degradation. As a result, it is now important to have mesh networks and working close to the limits of stability in order to meet these new requirements. The transient stability studies involve large disturbances such as short circuits, loss of work or production group. The consequence of these defects can be very serious, and can even lead to the complete collapse of the network. This work focuses on the regulation means that networks can help to keep their stability when submitted to strong disturbances. The magnetic energy storage-based superconductor (SMES) comprises a superconducting coil short-circuited on it self. When such a system is connected to a power grid is able to inject or absorb the active and reactive power. This system can be used to improve the stability of power systems.

Keywords: short-circuit, power oscillations, multiband PSS, power system, SMES, transient stability

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Authors: Rubin Dan, Xingcai Wang, Ziyang Chen

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A chaotic time series noise reduction method based on the fusion of the local projection method, wavelet transform, and particle swarm algorithm (referred to as the LW-PSO method) is proposed to address the problem of false recognition due to noise in the recognition process of chaotic time series containing noise. The method first uses phase space reconstruction to recover the original dynamical system characteristics and removes the noise subspace by selecting the neighborhood radius; then it uses wavelet transform to remove D1-D3 high-frequency components to maximize the retention of signal information while least-squares optimization is performed by the particle swarm algorithm. The Lorenz system containing 30% Gaussian white noise is simulated and verified, and the phase space, SNR value, RMSE value, and K value of the 0-1 test method before and after noise reduction of the Schreiber method, local projection method, wavelet transform method, and LW-PSO method are compared and analyzed, which proves that the LW-PSO method has a better noise reduction effect compared with the other three common methods. The method is also applied to the classical system to evaluate the noise reduction effect of the four methods and the original system identification effect, which further verifies the superiority of the LW-PSO method. Finally, it is applied to the Chengdu rainfall chaotic sequence for research, and the results prove that the LW-PSO method can effectively reduce the noise and improve the chaos recognition rate.

Keywords: Schreiber noise reduction, wavelet transform, particle swarm optimization, 0-1 test method, chaotic sequence denoising

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Authors: Jinghui Peng, Shanyu Tang, Jia Li

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Steganalysis seeks to detect the presence of secret data embedded in cover objects, and there is an imminent demand to detect hidden messages in streaming media. This paper shows how a steganalysis algorithm based on Fast Fourier Transform (FFT) can be used to detect the existence of secret data embedded in streaming media. The proposed algorithm uses machine parameter characteristics and a network sniffer to determine whether the Internet traffic contains streaming channels. The detected streaming data is then transferred from the time domain to the frequency domain through FFT. The distributions of power spectra in the frequency domain between original VoIP streams and stego VoIP streams are compared in turn using t-test, achieving the p-value of 7.5686E-176 which is below the threshold. The results indicate that the proposed FFT-based steganalysis algorithm is effective in detecting the secret data embedded in VoIP streaming media.

Keywords: steganalysis, security, Fast Fourier Transform, streaming media

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Authors: Sophy Ann Xavier, Lakshmi A

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Gentrification is the process of altering a neighborhood's character through the influx of wealthier people and establishments. This idea has subsequently been expanded to encompass brand-new, high-status construction projects that involve regenerating brownfield sites or demolishing and rebuilding residential neighborhoods. Inequality is made worse by Gentrification in ways that go beyond socioeconomic position. The elderly, members of racial and ethnic minorities, individuals with disabilities, and mental health all suffer disproportionately when they are displaced. Cities must cultivate openness, diversity, and inclusion in their collaborations, as well as cooperation on objectives and results. The papers compiled in this issue concentrate on the new gentrification discussions, the rising residential allure of central cities, and the indices to measure this process according to its various varieties. The study makes an effort to fill the research gap in the area of gentrification studies, which is the absence of a set of indices for measuring Gentrification in a specific area. Studies on Gentrification that contain maps of historical change highlight trends that will aid in the production of displacement risk maps, which will guide future interventions by allowing residents and policymakers to extrapolate into the future. Additionally, these maps give locals a glimpse into the future of their communities and serve as a political call to action in areas where residents are expected to be displaced. This study intends to pinpoint metrics and approaches for measuring Gentrification that can then be applied to create a spatiotemporal map of a region and tactics for its inclusive planning. An understanding of various approaches will enable planners and policymakers to select the best approach and create the appropriate plans.

Keywords: gentrification, indices, methods, quantification

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Authors: Shahzad Hassan, Kamran Saeed

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People are always in search of Wi-Fi hotspots because Internet is a major demand nowadays. But like all other technologies, there is still room for improvement in the Wi-Fi technology with regards to the speed and quality of connectivity. In order to address these aspects, Harald Haas, a professor at the University of Edinburgh, proposed what we know as the Li-Fi (Light Fidelity). Li-Fi is a new technology in the field of wireless communication to provide connectivity within a network environment. It is a two-way mode of wireless communication using light. Basically, the data is transmitted through Light Emitting Diodes which can vary the intensity of light very fast, even faster than the blink of an eye. From the research and experiments conducted so far, it can be said that Li-Fi can increase the speed and reliability of the transfer of data. This paper pays particular attention on the assessment of the performance of this technology. In other words, it is a 5G technology which uses LED as the medium of data transfer. For coverage within the buildings, Wi-Fi is good but Li-Fi can be considered favorable in situations where large amounts of data are to be transferred in areas with electromagnetic interferences. It brings a lot of data related qualities such as efficiency, security as well as large throughputs to the table of wireless communication. All in all, it can be said that Li-Fi is going to be a future phenomenon where the presence of light will mean access to the Internet as well as speedy data transfer.

Keywords: communication, LED, Li-Fi, Wi-Fi

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Authors: Helen S. Ghali, Haidy S. Ghali, Salma Ibrahim, Ossama Hosny, Hatem S. Elbehairy

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Infrastructure systems are essential assets in any community; accordingly, authorities aim to maximize its life span while minimizing the life cycle cost. This requires studying the asset conditions throughout its operation and forming a cost-efficient maintenance strategy plan. The objective of this study is to develop a highway management system that provides medium-term maintenance plans with the minimum life cycle cost subject to budget constraints. The model is applied to data collected for the highway network in India with the aim to output a 5-year maintenance plan strategy from 2019 till 2023. The main element considered is the surface coarse, either rigid or flexible pavement. The model outputs a 5-year maintenance plan for each segment given the budget constraint while maximizing the new pavement condition rating and minimizing its life cycle cost.

Keywords: infrastructure, asset management, optimization, maintenance plan

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Authors: V. V. Lakshmi, Y. V. S. Annapurna

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Urinary tract infection (UTI) is one of the most common infectious diseases seen in the community. Susceptible individuals experience multiple episodes, and progress to acute pyelonephritis or uro-sepsis or develop asymptomatic bacteriuria (ABU). Ability to cause extraintestinal infections depends on several virulence factors required for survival at extraintestinal sites. Presence of virulence phenotypes enhances the pathogenicity of these otherwise commensal organisms and thus augments its ability to cause extraintestinal infections, the most frequent in urinary tract infections(UTI). The present study focuses on detection of the virulence characters exhibited by the uropathogenic organism and most common factors exhibited in the local pathogens. A total of 700 isolates of E.coli and Klebsiella spp were included in the study.These were isolated from patients from local hospitals reported to be suffering with UTI over a period of three years. Isolation and identification was done based on Gram character and IMVIC reactions. Antibiotic sensitivity profile was carried out by disc diffusion method and multi drug resistant strains with MAR index of 0.7 were further selected. Virulence features examined included their ability to produce exopolysaccharides, protease- gelatinase production, hemolysin production, haemagglutination and hydrophobicity test. Exopolysaccharide production was most predominant virulence feature among the isolates when checked by congo red method. The biofilms production examined by microtitre plates using ELISA reader confirmed that this is the major factor contributing to virulencity of the pathogens followed by hemolysin production.

Keywords: Escherichia coli, Klebsiella spp, Uropathogens, virulence features

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Authors: David Nantes, George Gilbert

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There are a lot of risks that might crop up as a tunneling project develops, and it's crucial to be aware of them. Due to the unexpected nature of tunneling projects and the interconnectedness of risk occurrences, the risk assessment approach presents a significant challenge. The purpose of this study is to provide a hybrid FDEMATEL-ANP model to help prioritize risks during tunnel construction projects. The ambiguity in expert judgments and the relative severity of interdependencies across risk occurrences are both taken into consideration by this model, thanks to the Fuzzy Decision-Making Trial and Evaluation Laboratory (FDEMATEL). The Analytic Network Process (ANP) method is used to rank priorities and assess project risks. The authors provide a case study of a subway tunneling construction project to back up the validity of their methodology. The results showed that the proposed method successfully isolated key risk factors and elucidated their interplay in the case study. The proposed method has the potential to become a helpful resource for evaluating dangers associated with tunnel construction projects.

Keywords: risk, prioritization, FDEMATEL, ANP, tunneling construction projects

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Authors: N. Ploysook, R. Rugsaj, C. Suvanjumrat

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The characteristic requirement for producing rectangular shape bottles was a uniform thickness of the plastic bottle wall. Die shaping was a good technique which controlled the wall thickness of bottles. An advance technology which was the finite element method (FEM) for blowing parison to be a rectangular shape bottle was conducted to reduce waste plastic from a trial and error method of a die shaping and parison control method. The artificial intelligent (AI) comprised of artificial neural network and genetic algorithm was selected to optimize the die gap shape from the FEM results. The application of AI technique could optimize the suitable die gap shape for the parison blow molding which did not depend on the parison control method to produce rectangular bottles with the uniform wall. Particularly, this application can be used with cheap blow molding machines without a parison controller therefore it will reduce cost of production in the bottle blow molding process.

Keywords: AI, bottle, die shaping, FEM

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Authors: Atiq Zaman

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The high contamination rate in the recycling waste stream is one of the major problems in Australia. In addition, a lack of reliable waste data makes it even more difficult for designing and implementing an effective waste management plan. This article conceptualizes the opportunity to improve resource productivity by integrating smart resource tracking system (SRTS) into the Australian household waste management system. The application of the smart resource tracking system will be implemented through the following ways: (i) mobile application-based resource tracking system used to measure the household’s material flow; (ii) RFID, smart image and weighing system used to track waste generation, recycling and contamination; (iii) informing and motivating manufacturer and retailers to improve their problematic products’ packaging; and (iv) ensure quality and reliable data through open-sourced cloud data for public use. The smart mobile application, imaging, radio-frequency identification (RFID) and weighing technologies are not new, but the very straightforward idea of using these technologies in the household resource consumption, waste bins and collection trucks will open up a new era of accurately measuring and effectively managing our waste. The idea will bring the most urgently needed reliable, data and clarity on household consumption, recycling behaviour and waste management practices in the context of available local infrastructure and policies. Therefore, the findings of this study would be very important for decision makers to improve resource productivity in the waste industry by using smart resource tracking system.

Keywords: smart devices, mobile application, smart sensors, resource tracking, waste management, resource productivity

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Authors: Abdul M. Khan, Ayesha Iqbal

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In this paper, new dental remains of Merycopotamus (Anthracotheriidae) are described. The specimens were collected during field work by the authors from the well dated fossiliferous locality 'Hasnot' belonging to the Dhok Pathan Formation, and from 'Tatrot' village belonging to Tatrot Formation of the Potwar Plateau, Pakistan. The stratigraphic age of the Neogene deposits around Hasnot is 7 - 5 Ma; whereas the age of the Tatrot Formation is from 3.4 - 2.6 Ma. The newly discovered material when compared with the previous records of the genus Merycopotamus from the Siwaliks led us to identify all the three reported species of this genus from the Siwaliks of Pakistan. As the sample comprises only the dental remains so the identification of the specimens is solely based upon the morpho-metric analysis. The occlusal pattern of the upper molar in Merycopotamus dissimilis is different from Merycopotamus medioximus and Merycopotamus nanus in having a mesostyle fully divided, forming two prominent cusps, while mesostyle in M. medioximus is partly divided and small lateral crests are present on the mesostyle. A continuous loop like mesostyle is present in Merycopotamus nanus. The entoconid fold is present in Merycopotamus dissimilis on the lower molars whereas it is absent in Merycopotamus medioximus and Merycopotamus nanus. The hypoconulid in M. dissimilis is relatively simple but a loop like hypoconulid is present in M. medioximus and M. nanus. The results of the present findings are in line with the previous records of the genus Merycopotamus, with M. nanus, M. medioximus and M. dissimilis in the Late Miocene – Early Pliocene Dhok Pathan Formation, and M. dissimilis in the Late Pliocene Tatrot sediments of Pakistan.

Keywords: Dhok Pathan, late miocene, merycopotamus, pliocene, Tatrot

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Authors: Ambalika Ekka

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In today’s world, the growing demand for urban built forms has resulted in the production and consumption of building materials i.e. embodied energy in building construction, leading to pollution and greenhouse gas (GHG) emissions. Therefore, new buildings will offer a unique opportunity to implement more energy efficient building without compromising on building performance of the building. Embodied energy of building materials forms major contribution to embodied energy in buildings. The paper results in an approach towards designing an energy efficient apartment building through embodied energy assessment. This paper discusses the trend of residential development in Rourkela, which includes three case studies of the contemporary houses, followed by architectural elements, number of storeys, predominant material use and plot sizes using primary data. It results in identification of predominant material used and other characteristics in urban area. Further, the embodied energy coefficients of various dominant building materials and alternative materials manufactured in Indian Industry is taken in consideration from secondary source i.e. literature study. The paper analyses the embodied energy by estimating materials and operational energy of proposed building followed by altering the specifications of the materials based on the building components i.e. walls, flooring, windows, insulation and roof through res build India software and comparison of different options is assessed with consideration of sustainable parameters. This paper results that autoclaved aerated concrete block only reaches the energy performance Index benchmark i.e. 69.35 kWh/m² yr i.e. by saving 4% of operational energy and as embodied energy has no particular index, out of all materials it has the highest EE 23206202.43  MJ.

Keywords: energy efficient, embodied energy, EPI, building materials

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Authors: Nihal Murali, Kunal Gupta, Surekha Bhanot

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Training of artificial neural networks (ANNs) using reinforcement learning (RL) techniques is being widely discussed in the robot learning literature. The high model complexity of ANNs along with the model-free nature of RL algorithms provides a desirable combination for many robotics applications. There is a huge need for algorithms that generalize using raw sensory inputs, such as vision, without any hand-engineered features or domain heuristics. In this paper, the standard control problem of line following robot was used as a test-bed, and an ANN controller for the robot was trained on images from a live video feed using Q-learning. A virtual agent was first trained in simulation environment and then deployed onto a robot’s hardware. The robot successfully learns to traverse a wide range of curves and displays excellent generalization ability. Qualitative analysis of the evolution of policies, performance and weights of the network provide insights into the nature and convergence of the learning algorithm.

Keywords: artificial neural networks, q-learning, reinforcement learning, robot learning

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Authors: Deepika Sudevan, Patrick Rozycki, Laurent Gornet

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This paper presents the experimental identification of the fatigue limit for pristine and impacted Carbon Fiber Reinforced Epoxy polymer (CFRP) woven composites based on the relatively new self-heating methodology for composites. CFRP composites of [0/90]8 and quasi isotropic configurations prepared using hand-layup technique are subjected to low energy impacts (20 J energy) simulating a barely visible impact damage (BVID). Runway debris strike, tool drop or hailstone impact can cause a BVID on an aircraft fuselage made of carbon composites and hence understanding the post-impact fatigue response of CFRP laminates is of immense importance to the aerospace community. The BVID zone on the specimens is characterized using X-ray Tomography technique. Both pristine and impacted specimens are subjected to several blocks of constant amplitude (CA) fatigue loading keeping R-ratio a constant but with increments in the mean loading stress after each block. The number of loading cycles in each block is a subjective parameter and it varies for pristine and impacted CFRP specimens. To monitor the temperature evolution during fatigue loading, thermocouples are pasted on the CFRP specimens at specific locations. The fatigue limit is determined by two strategies, first is by considering the stabilized temperature in every block and second is by considering the change in the temperature slope per block. The results show that both strategies can be adopted to determine the fatigue limit in both pristine and impacted CFRP composites.

Keywords: CFRP, fatigue limit, low energy impact, self-heating, WRM

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Authors: Youping Huang, Yang Liu

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Mountainous cities have unique landscape relationship, topography and urban spatial pattern different from plain cities, which put forward different requirements for greenway system planning strategy. Taking the greenway planning of Chengkou County in Chongqing as an example, this paper discusses the greenway system planning strategy of mountainous cities based on urban and rural green space, urban landscape resources, human resources and other factors. Through multi-angle maintenance of landscape pattern, multi-objective integration of urban resources, multi-level construction of greenway network, and multi-interactive development control, the sustainable development of mountain city landscape resources is realized, the new urban ecology is constructed, and the quality of life of urban and rural residents is improved.

Keywords: greenway planning, mountain city, landscape pattern, cultural resources, chongqing

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Authors: Md. Ahsan Ayub, Kazi A. Kalpoma, Humaira Tasnim Proma, Syed Mehrab Kabir, Rakib Ibna Hamid Chowdhury

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Constraint Satisfaction Problem (CSP) is observed in various applications, i.e., scheduling problems, timetabling problems, assignment problems, etc. Researchers adopt a CSP technique to tackle a certain problem; however, each technique follows different approaches and ways to solve a problem network. In our exhaustive study, it has been possible to visualize the processes of essential CSP algorithms from a very concrete constraint satisfaction example, NQueens Problem, in order to possess a deep understanding about how a particular constraint satisfaction problem will be dealt with by our studied and implemented techniques. Besides, benchmark results - time vs. value of N in N-Queens - have been generated from our implemented approaches, which help understand at what factor each algorithm produces solutions; especially, in N-Queens puzzle. Thus, extended decisions can be made to instantiate a real life problem within CSP’s framework.

Keywords: arc consistency (AC), backjumping algorithm (BJ), backtracking algorithm (BT), constraint satisfaction problem (CSP), forward checking (FC), least constrained values (LCV), maintaining arc consistency (MAC), minimum remaining values (MRV), N-Queens problem

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Authors: Mukul R. Gupta, Rajkumar Gandhi, Rajitha Sachan, Naveen K. Khare

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The field of glycoscience has burgeoned in the last several decades, leading to the identification of many glycosides which could serve critical roles in a wide range of biological processes. This has prompted a resurgence in synthetic interest, with a particular focus on new approaches to construct the selective glycosidic bond. Despite the numerous elegant strategies and methods developed for the formation of glycosidic bonds, stereoselective construction of glycosides remains challenging. Here, we have recently developed the novel Hexafluoroisopropanol (HFIP) catalyzed stereoselective glycosylation methods by using KDN imidate glycosyl donor and a variety of alcohols in excellent yield. This method is broadly applicable to a wide range of substrates and with excellent selectivity of glycoside. Also, herein we are reporting the functionalization of the unbiased side of newly formed glycosides by dual-catalytic transition metal systems (Ru- or Fe-). We are using the innovative Reverse & Catalyst strategy, i.e., a reversible activation reaction by one catalyst with a functionalization reaction by another catalyst, together with enabling functionalization of substrates at their inherently unreactive sites. As well, we are targeting the diSia derivative synthesis by Wittig reaction. This synthetic method is applicable in mild conditions, functional group tolerance of the dual-catalytic systems and also highlights the potential of the multicatalytic approach to address challenging transformations to avoid multistep procedures in carbohydrate synthesis.

Keywords: KDN, stereoselective glycosylation, dual-catalytic functionalization, Wittig reaction

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Authors: The Danh Phan

Abstract:

House price forecasting is a main topic in the real estate market research. Effective house price prediction models could not only allow home buyers and real estate agents to make better data-driven decisions but may also be beneficial for the property policymaking process. This study investigates the housing market by using machine learning techniques to analyze real historical house sale transactions in Australia. It seeks useful models which could be deployed as an application for house buyers and sellers. Data analytics show a high discrepancy between the house price in the most expensive suburbs and the most affordable suburbs in the city of Melbourne. In addition, experiments demonstrate that the combination of Stepwise and Support Vector Machine (SVM), based on the Mean Squared Error (MSE) measurement, consistently outperforms other models in terms of prediction accuracy.

Keywords: house price prediction, regression trees, neural network, support vector machine, stepwise

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Authors: Pavan K. Rallabandi, Kailash C. Patidar

Abstract:

In this paper, we present an optimization technique or a learning algorithm using the hybrid architecture by combining the most popular sequence recognition models such as Recurrent Neural Networks (RNNs) and Hidden Markov models (HMMs). In order to improve the sequence or pattern recognition/ classification performance by applying a hybrid/neural symbolic approach, a gradient descent learning algorithm is developed using the Real Time Recurrent Learning of Recurrent Neural Network for processing the knowledge represented in trained Hidden Markov Models. The developed hybrid algorithm is implemented on automata theory as a sample test beds and the performance of the designed algorithm is demonstrated and evaluated on learning the deterministic finite state automata.

Keywords: hybrid systems, hidden markov models, recurrent neural networks, deterministic finite state automata

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Authors: Khalid Hussein, Waleed Abdalati, Pakorn Petchprayoon, Khaula Alkaabi

Abstract:

In this study, we integrated ASTER thermal data with an area-based spatial insolation model to identify and delineate geothermally active areas in Yellowstone National Park (YNP). Two pairs of L1B ASTER day- and nighttime scenes were used to calculate land surface temperature. We employed the Emissivity Normalization Algorithm which separates temperature from emissivity to calculate surface temperature. We calculated the incoming solar radiation for the area covered by each of the four ASTER scenes using an insolation model and used this information to compute temperature due to solar radiation. We then identified the statistical thermal anomalies using land surface temperature and the residuals calculated from modeled temperatures and ASTER-derived surface temperatures. Areas that had temperatures or temperature residuals greater than 2σ and between 1σ and 2σ were considered ASTER-modeled thermal anomalies. The areas identified as thermal anomalies were in strong agreement with the thermal areas obtained from the YNP GIS database. Also the YNP hot springs and geysers were located within areas identified as anomalous thermal areas. The consistency between our results and known geothermally active areas indicate that thermal remote sensing data, integrated with a spatial-based insolation model, provides an effective means for identifying and locating areas of geothermal activities over large areas and rough terrain.

Keywords: thermal remote sensing, insolation model, land surface temperature, geothermal anomalies

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Authors: Jingsi Li, Neil S. Ferguson

Abstract:

Time pressure could have an influence on the productivity, quality of decision making, and the efficiency of problem-solving. This has been mostly stemmed from cognitive research or psychological literature. However, a salient scarce discussion has been held for transport adjacent fields. It is conceivable that in many activity-travel contexts, time pressure is a potentially important factor since an excessive amount of decision time may incur the risk of late arrival to the next activity. The activity-travel rescheduling behavior is commonly explained by costs and benefits of factors such as activity engagements, personal intentions, social requirements, etc. This paper hypothesizes that an additional factor of perceived time pressure could affect travelers’ rescheduling behavior, thus leading to an impact on travel demand management. Time pressure may arise from different ways and is assumed here to be essentially incurred due to travelers planning their schedules without an expectation of unforeseen elements, e.g., transport disruption. In addition to a linear-additive utility-maximization model, the less computationally compensatory heuristic models are considered as an alternative to simulate travelers’ responses. The paper will contribute to travel behavior modeling research by investigating the following questions: how to measure the time pressure properly in an activity-travel day plan context? How do travelers reschedule their plans to cope with the time pressure? How would the importance of the activity affect travelers’ rescheduling behavior? What will the behavioral model be identified to describe the process of making activity-travel rescheduling decisions? How do these identified coping strategies affect the transport network? In this paper, a Mixed Heuristic Model (MHM) is employed to identify the presence of different choice heuristics through a latent class approach. The data about travelers’ activity-travel rescheduling behavior is collected via a web-based interactive survey where a fictitious scenario is created comprising multiple uncertain events on the activity or travel. The experiments are conducted in order to gain a real picture of activity-travel reschedule, considering the factor of time pressure. The identified behavioral models are then integrated into a multi-agent transport simulation model to investigate the effect of the rescheduling strategy on the transport network. The results show that an increased proportion of travelers use simpler, non-compensatory choice strategies instead of compensatory methods to cope with time pressure. Specifically, satisfying - one of the heuristic decision-making strategies - is adopted commonly since travelers tend to abandon the less important activities and keep the important ones. Furthermore, the importance of the activity is found to increase the weight of negative information when making trip-related decisions, especially route choices. When incorporating the identified non-compensatory decision-making heuristic models into the agent-based transport model, the simulation results imply that neglecting the effect of perceived time pressure may result in an inaccurate forecast of choice probability and overestimate the affectability to the policy changes.

Keywords: activity-travel rescheduling, decision making under uncertainty, mixed heuristic model, perceived time pressure, travel demand management

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Authors: Muhammad Sohail Sajid, Muhammad Abdullah Malik, Muhammad Saqib, Faiz Ahmad Raza, Waseem Akram

Abstract:

Aedes (Ae.) aegypti, the vector of pathogens of one health significance, has gained currency over the last decade. The present study reports the prevalence of A. aegypti larvae in indoor and outdoor niches from the three districts of different agro-geo-climatic zones of Punjab, including Chakwal (north), Faisalabad (central), and Dera Ghazi Khan (south). Mosquito larvae were collected, preserved, and transferred for identification. The relevant data were collected on a predesigned questionnaire. Stegomyia indices, including House Index (HI), Breteau Index (BI), and Container Index (CI), were calculated. The association of different breeding containers with the prevalence of Ae. aegypti larvae were estimated through Chi-square analysis. The highest Stegomyia indices were calculated in Chakwal (HI = 46.61%, BI = 91.67%, and CI = 15.28%) as compared to Faisalabad (HI = 34.11%, BI = 68.75% and, CI = 13.04%) and DG Khan (HI = 28.39%, BI = 68.23% and, CI = 11.29%), respectively. Irrespective of the geographical area, earthen jars, water tanks, and tree holes were found to be significantly associated (p < 0.05) with the abundance of Ae. aegypti larvae. However, tires and plastic bottles in Faisalabad and DG Khan while flower tubs and plastic buckets in Faisalabad and Chakwal were found to be significantly associated (p < 0.05) with the larval abundance. The results are a maiden attempt to correlate the magnitude of Ae. aegypti larvae in various microclimatic niches of Punjab, Pakistan, which might help in policy-making for preventive management of the menace.

Keywords: Aedes aegypti, ecology, breeding habitats, Stegomyia indices, breeding containers

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