Search results for: alarm filtering

Authors: Siddharth Sarma, Ayush Majumdar, Nidhi Sabu, Mufaddal Jiruwaala, Shilpa Paygude

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Digital Elevation Models (DEMs) are digital representations of the Earth’s topography, which include information about the elevation, slope, aspect, and other terrain attributes. DEMs play a crucial role in various applications, including terrain analysis, urban planning, and environmental modeling. In this paper, TerraEnhance is proposed, a distinct approach for high-resolution DEM generation using Generative Adversarial Networks (GANs) combined with Real-ESRGANs. By learning from a dataset of low-resolution DEMs, the GANs are trained to upscale the data by 10 times, resulting in significantly enhanced DEMs with improved resolution and finer details. The integration of Real-ESRGANs further enhances visual quality, leading to more accurate representations of the terrain. A post-processing layer is introduced, employing high-pass filtering to refine the generated DEMs, preserving important details while reducing noise and artifacts. The results demonstrate that TerraEnhance outperforms existing methods, producing high-fidelity DEMs with intricate terrain features and exceptional accuracy. These advancements make TerraEnhance suitable for various applications, such as terrain analysis and precise environmental modeling.

Keywords: DEM, ESRGAN, image upscaling, super resolution, computer vision

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Authors: Aarnav Singh, Jatin Moolchandani

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The proposed research work aims to build a query-based AI chatbot that can answer any question related to any topic. A chatbot is software that converses with users via text messages. In the proposed system, we aim to build a chatbot that generates a response based on the user’s query. For this, we use natural language processing to analyze the query and some set of texts to form a concise answer. The texts are obtained through web-scrapping and filtering all the credible sources from a web search. The objective of this project is to provide a chatbot that is able to provide simple and accurate answers without the user having to read through a large number of articles and websites. Creating an AI chatbot that can answer a variety of user questions on a variety of topics is the goal of the proposed research project. This chatbot uses natural language processing to comprehend user inquiries and provides succinct responses by examining a collection of writings that were scraped from the internet. The texts are carefully selected from reliable websites that are found via internet searches. This project aims to provide users with a chatbot that provides clear and precise responses, removing the need to go through several articles and web pages in great detail. In addition to exploring the reasons for their broad acceptance and their usefulness across many industries, this article offers an overview of the interest in chatbots throughout the world.

Keywords: Chatbot, Artificial Intelligence, natural language processing, web scrapping

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Authors: Almalki M., Alajmi M., Qadrouh Y., Alzahrani E., Sulaiman A., Aleid M., Albaiji A., Alfaifi H., Alhadadi A., Almotairy H., Alrasheed R., Alhafedh Y.

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High-resolution marine seismic survey is a well-established technique that commonly used to characterize near-surface sediments and geological structures at shallow water. We conduct single channel seismic survey to provide high quality seismic images for near-surface sediments upto 100m depth at Jubal costal area, Arabian Gulf. Eight hydrophones streamer has been used to collect stacked seismic traces alone 5km seismic line. To reach the required depth, we have used spark system that discharges energies above 5000 J with expected frequency output span the range from 200 to 2000 Hz. A suitable processing flow implemented to enhance the signal-to-noise ratio of the seismic profile. We have found that shallow sedimentary layers at the study site have complex pattern of reflectivity, which decay significantly due to amount of source energy used as well as the multiples associated to seafloor. In fact, the results reveal that single channel marine seismic at shallow water is a cost-effective technique that can be easily repeated to observe any possibly changes in the wave physical properties at the near surface layers

Keywords: shallow marine single-channel data, high resolution, frequency filtering, shallow water

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Authors: Plessen Mogens Graf

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Within the context of multivariate time series segmentation, this paper proposes a method inspired by a posteriori optimal trading. After a normalization step, time series are treated channelwise as surrogate stock prices that can be traded optimally a posteriori in a virtual portfolio holding either stock or cash. Linear transaction costs are interpreted as hyperparameters for noise filtering. Trading signals, as well as trading signals obtained on the reversed time series, are used for unsupervised channelwise labeling before a consensus over all channels is reached that determines the final segmentation time instants. The method is model-free such that no model prescriptions for segments are made. Benefits of proposed approach include simplicity, computational efficiency, and adaptability to a wide range of different shapes of time series. Performance is demonstrated on synthetic and real-world data, including a large-scale dataset comprising a multivariate time series of dimension 1000 and length 2709. Proposed method is compared to a popular model-based bottom-up approach fitting piecewise affine models and to a recent model-based top-down approach fitting Gaussian models and found to be consistently faster while producing more intuitive results in the sense of segmenting time series at peaks and valleys.

Keywords: time series segmentation, model-free, trading-inspired, multivariate data

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Authors: Nyimas Annissa Mutiara Andini

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There are 325,000 children younger than age 15 in the U.S. have epilepsy. In Indonesia, 40% of 3,5 millions cases of epilepsy happens in children. The most common type of epilepsy, which affects 6 out of 10 people with the disorder, is called idiopathic epilepsy and which has no identifiable cause. One of the most commonly used medications in the treatment of this childhood epilepsy is sodium valproate. Administration of sodium valproat in children has a problem to fail. Nearly 60% of pediatric patients known were mildly, moderately, or severely non-adherent with therapy during the first six months of treatment. Many parents or caregiver took far less medication than prescribed, and the treatment-adherence pattern for the majority of patients was established during the first month of treatment. 42% of the patients were almost always given their medications as prescribed but 13% had very poor adherence even in the early weeks and months of treatment. About 7% of patients initially gave the medication correctly 90% of the time, but adherence dropped to around 20% within six months of starting treatment. Over the six months of observation, the total missing of administration is about four out of 14 doses in any given week. This fail can cause the epilepsy to relapse. Whereas, current reported epilepsy disorder were significantly more likely than those never diagnosed to experience depression (8% vs 2%), anxiety (17% vs 3%), attention-deficit/hyperactivity disorder (23% vs 6%), developmental delay (51% vs 3%), autism/autism spectrum disorder (16% vs 1%), and headaches (14% vs 5%) (all P< 0.05). They had a greater risk of limitation in the ability to do things (relative risk: 9.22; 95% CI: 7.56–11.24), repeating a school grade (relative risk: 2.59; CI: 1.52–4.40), and potentially having unmet medical and mental health needs. In the other side, technology can help to make our life easier. One of the technology, that we can use is a mobile application. A mobile app is a software program we can download and access directly using our phone. Indonesians are highly mobile centric. They use, on average, 6.7 applications over a 30 day period. This paper is aimed to describe an application that could help to control a sodium valproat administration in children; we call it as D-Epi app. D-Epi app is a downloadable application that can help parents or caregiver alert by a timer-related application to warn whether it is the time to administer the sodium valproat. It works not only as a standard alarm, but also inform important information about the drug and emergency stuffs to do to children with epilepsy. This application could help parents and caregiver to take care a child with epilepsy in Indonesia.

Keywords: application, children, D-Epi, epilepsy

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Authors: Nuraddeen Usman, Khiruddin Abdullah, Mohd Nawawi, Amin Khalil Ismail

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A magnetic survey is carried out in order to locate the remains of construction items, specifically concrete pillars. The conventional Euler deconvolution technique can perform the task but it requires the use of fixed structural index (SI) and the construction items are made of materials with different shapes which require different SI (unknown). A Euler deconvolution technique that estimate background, horizontal coordinate (xo and yo), depth and structural index (SI) simultaneously is prepared and used for this task. The synthetic model study carried indicated the new methodology can give a good estimate of location and does not depend on magnetic latitude. For field data, both the total magnetic field and gradiometer reading had been collected simultaneously. The computed vertical derivatives and gradiometer readings are compared and they have shown good correlation signifying the effectiveness of the method. The filtering is carried out using automated procedure, analytic signal and other traditional techniques. The clustered depth solutions coincided with the high amplitude/values of analytic signal and these are the possible target positions of the concrete pillars being sought. The targets under investigation are interpreted to be located at the depth between 2.8 to 9.4 meters. More follow up survey is recommended as this mark the preliminary stage of the work.

Keywords: concrete pillar, magnetic survey, geotechnical investigation, Euler Deconvolution

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Authors: Sofia M. Karadimitriou, Kostas Triantafyllopoulos, Timothy Heaton

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Reduced dimension Dynamic Spatio-Temporal Models (DSTMs) jointly describe the spatial and temporal evolution of a function observed subject to noise. A basic state space model is adopted for the discrete temporal variation, while a continuous autoregressive structure describes the continuous spatial evolution. Application of such a DSTM relies upon the pre-selection of a suitable reduced set of basic functions and this can present a challenge in practice. In this talk, we propose an online estimation method for high dimensional spatio-temporal data based upon DSTM and we attempt to resolve this issue by allowing the basis to adapt to the observed data. Specifically, we present a wavelet decomposition in order to obtain a parsimonious approximation of the spatial continuous process. This parsimony can be achieved by placing a Laplace prior distribution on the wavelet coefficients. The aim of using the Laplace prior, is to filter wavelet coefficients with low contribution, and thus achieve the dimension reduction with significant computation savings. We then propose a Hierarchical Bayesian State Space model, for the estimation of which we offer an appropriate particle filter algorithm. The proposed methodology is illustrated using real environmental data.

Keywords: multidimensional Laplace prior, particle filtering, spatio-temporal modelling, wavelets

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Authors: David P. Tantua, Abdulkader Helwan

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Biometrics has been recently used for the human identification systems using the biological traits such as the fingerprints and iris scanning. Identification systems based biometrics show great efficiency and accuracy in such human identification applications. However, these types of systems are so far based on some image processing techniques only, which may decrease the efficiency of such applications. Thus, this paper aims to develop a human palmprint identification system using multi-layer perceptron neural network which has the capability to learn using a backpropagation learning algorithms. The developed system uses images obtained from a public database available on the internet (CASIA). The processing system is as follows: image filtering using median filter, image adjustment, image skeletonizing, edge detection using canny operator to extract features, clear unwanted components of the image. The second phase is to feed those processed images into a neural network classifier which will adaptively learn and create a class for each different image. 100 different images are used for training the system. Since this is an identification system, it should be tested with the same images. Therefore, the same 100 images are used for testing it, and any image out of the training set should be unrecognized. The experimental results shows that this developed system has a great accuracy 100% and it can be implemented in real life applications.

Keywords: biometrics, biological traits, multi-layer perceptron neural network, image skeletonizing, edge detection using canny operator

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Authors: Rivindu Nethmin Bandara Menik Hitihamy Mudiyanselage, Matthias Hank Haeusler, Ben Doherty

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Investors and clients in the Architectural, Engineering and Construction industry find it difficult to understand complex datasets and reports with little to no graphic representation. The stakeholders examined in this paper include designers, design clients and end-users. Communicating embodied carbon information graphically and concisely can aid with decision support early in a building's life cycle. It is essential to create a common visualisation approach as the level of knowledge about embodied carbon varies between stakeholders. The tool, designed in conjunction with Bates Smart, condenses Tally Life Cycle Assessment data to a carbon hot-spotting visualisation, highlighting the sections with the highest amounts of embodied carbon. This allows stakeholders at every stage of a given project to have a better understanding of the carbon implications with minimal effort. It further allows stakeholders to differentiate building elements by their carbon values, which enables the evaluation of the cost-effectiveness of the selected materials at an early stage. To examine and build a decision-support tool, an action-design research methodology of cycles of iterations was used along with precedents of embodied carbon visualising tools. Accordingly, the importance of visualisation and Building Information Modelling are also explored to understand the best format for relaying these results.

Keywords: embodied carbon, visualisation, summarisation, data filtering, early-stage decision-making, materiality

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Authors: Patrick Cummings, Laura Cassani, Deirdre Kelliher

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In this paper we present findings from a research effort to apply a hybrid collaborative-context approach for a system focused on Marine Corps civil affairs data collection, aggregation, and analysis called the Marine Civil Information Management System (MARCIMS). The goal of this effort is to provide operators with information to make sense of the interconnectedness of entities and relationships in their area of operation and discover existing data to support civil military operations. Our approach to build a recommendation engine was designed to overcome several technical challenges, including 1) ensuring models were robust to the relatively small amount of data collected by the Marine Corps civil affairs community; 2) finding methods to recommend novel data for which there are no interactions captured; and 3) overcoming confirmation bias by ensuring content was recommended that was relevant for the mission despite being obscure or less well known. We solve this by implementing a combination of collective matrix factorization (CMF) and graph-based random walks to provide recommendations to civil military operations users. We also present a method to resolve the challenge of computation complexity inherent from highly connected nodes through a precomputed process.

Keywords: Recommendation engine, collaborative filtering, context based recommendation, graph analysis, coverage, civil affairs operations, Marine Corps

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Authors: Waled A. Dawoud, Abdelazim M. Negm, Nasser M. Saleh

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Offshore piling generates underwater sound at level high enough to cause physical damage or hearing impairment to the marine mammals. Several methods can be used to mitigate the effect of underwater noise from offshore pile driving on marine mammals which can be divided into three main approaches. The first approach is to keep the mammal out of the high-risk area by using aversive sound waves produced by acoustic mitigation devices such as playing-back of mammal's natural predator vocalization, alarm or distress sounds, and anthropogenic sound. The second approach is to reduce the amount of underwater noise from pile driving using noise mitigation techniques such as bubble curtains, isolation casing, and hydro-sound dampers. The third approach is to eliminate the overlap of underwater waves by using prolonged construction process. To investigate the effectiveness of different noise mitigation methods; a pile driven with 235 kJ rated energy diesel hammer near Jeddah Coast, Kingdom of Saudi Arabia was used. Using empirical sound exposure model based on Red Sea characteristics and limits of National Oceanic and Atmospheric Administration; it was found that the aversive sound waves should extend to 1.8 km around the pile location. Bubble curtains can reduce the behavioral disturbance area up to 28%; temporary threshold shift up to 36%; permanent threshold shift up to 50%; and physical injury up to 70%. Isolation casing can reduce the behavioral disturbance range up to 12%; temporary threshold shift up to 21%; permanent threshold shift up to 29%; and physical injury up to 46%. Hydro-sound dampers efficiency depends mainly on the used technology and it can reduce the behavioral disturbance range from 10% to 33%; temporary threshold shift from 18% to 25%; permanent threshold shift from 32% to 50%; and physical injury from 46% to 60%. To prolong the construction process, it was found that the single pile construction, use of soft start, and keep time between two successive hammer strikes more than 3 seconds are the most effective techniques.

Keywords: offshore pile driving, sound propagation models, noise effects on marine mammals, Underwater noise mitigation

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Authors: Idowu Olugbenga Adewumi, Foluke Iyabo Oluwatoyinbo

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Presently, there are several discussions on the food security with increase in yield of arable crop throughout the world. This article, briefly present research efforts to create digital interfaces to nature, in particular to area of crop production in agriculture with increase in yield with interest on pervasive computing. The approach goes beyond the use of sensor networks for environmental monitoring but also by emphasizing the development of a system architecture that detect intruder (Intrusion Process) which reduce the yield of the farmer at the end of the planting/harvesting period. The objective of the work is to set a model for setting up the hand held or portable device for increasing the quality and quantity of arable crop. This process incorporates the use of infrared motion image sensor with security alarm system which can send a noise signal to intruder on the farm. This model of the portable image sensing device in monitoring or scaring human, rodent, birds and even pests activities will reduce post harvest loss which will increase the yield on farm. The nano intelligence technology was proposed to combat and minimize intrusion process that usually leads to low quality and quantity of produce from farm. Intranet system will be in place with wireless radio (WLAN), router, server, and client computer system or hand held device e.g PDAs or mobile phone. This approach enables the development of hybrid systems which will be effective as a security measure on farm. Since, precision agriculture has developed with the computerization of agricultural production systems and the networking of computerized control systems. In the intelligent plant production system of controlled greenhouses, information on plant responses, measured by sensors, is used to optimize the system. Further work must be carry out on modeling using pervasive computing environment to solve problems of agriculture, as the use of electronics in agriculture will attracts more youth involvement in the industry.

Keywords: pervasive computing, intrusion detection, precision agriculture, security, arable crop

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Authors: Duangduen L. Bhanthumnavin, Duchduen E. Bhanthumnavin

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Widening gap between new academic knowledge in all areas and habit of exploring and exploiting this precious information by students causes an alarm and need for urgent prevention. At present, all advanced nations are committed to WHO’s Sustainable Development Goals (SDGs), which require some objective achievements by the year 2030 and further. The responsibility has been enforced on university lecturers, in addition to the higher education learning outcomes (HELO). The two groups of goals (SDGs and HELO) can be realized if most university instructors are capable of inculcating some important psychological characteristics and behavioral change in the new generations. Thus, this study aimed at pinpointing the significant factors for additional teaching skills of instructors regardless of the area of study. University lecturers from various parts of Thailand, with the total of 540 persons, participated in this cross-sectional study. Based on interactionism model of behavior antecedents, it covers psychological situational factors, as well as their interaction. Most measuring instruments were summated rating with 10 or more items, each accompanied by a six-point rating scale. All these measures were constructed with acceptable standards. Most of the respondents were volunteers who gave their written responses in a meeting room or conference hall. By applying Multiple Regression Analysis in the total sample as well as in the subsamples of these university instructors, about 70 to 73 predictive percentages with 4 to 6 significant predictors were found. The major dependent variable was instructor’s teaching behavior for inculcating the psycho-moral strength for academic exploration and knowledge application. By performing ANOVA, the less-active instructors were identified as the ones with lower education (Master’s level or lower), the minimal research producers, and the ones with less in-service trainings. The preventive factors for these three groups of instructors were intention to increase the students’ psychological development as well as moral development in their regular teaching classes. In addition, social support from their supervisors and coworkers was also necessary. Recommendations for further research and training are offered and welcomed.

Keywords: psychological inculcation, at-risk instructors, preventive measures, undergraduate teaching

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Authors: Arunava Chakrabarti

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A one-dimensional chain of magnetic atoms, representative of a quantum gas in an artificial quasi-periodic potential and modeled by the well-known Aubry-Andre function and its variants are studied in respect of its capability of working as a spin filter for arbitrary spins. The basic formulation is explained in terms of a perfectly periodic chain first, where it is shown that a definite correlation between the spin S of the incoming particles and the magnetic moment h of the substrate atoms can open up a gap in the energy spectrum. This is crucial for a spin filtering action. The simple one-dimensional chain is shown to be equivalent to a 2S+1 strand ladder network. This equivalence is exploited to work out the condition for the opening of gaps. The formulation is then applied for a one-dimensional chain with quasi-periodic variation in the site potentials, the magnetic moments and their orientations following an Aubry-Andre modulation and its variants. In addition, we show that a certain correlation between the system parameters can generate absolutely continuous bands in such systems populated by Bloch like extended wave functions only, signaling the possibility of a metal-insulator transition. This is a case of correlated disorder (a deterministic one), and the results provide a non-trivial variation to the famous Anderson localization problem. We have worked within a tight binding formalism and have presented explicit results for the spin half, spin one, three halves and spin five half particles incident on the magnetic chain to explain our scheme and the central results.

Keywords: Aubry-Andre model, correlated disorder, localization, spin filter

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Authors: Jack R. McKenzie, Peter A. Appleby, Thomas House, Neil Walton

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Cold-start is a notoriously difficult problem which can occur in recommendation systems, and arises when there is insufficient information to draw inferences for users or items. To address this challenge, a contextual bandit algorithm – the Fast Approximate Bayesian Contextual Cold Start Learning algorithm (FAB-COST) – is proposed, which is designed to provide improved accuracy compared to the traditionally used Laplace approximation in the logistic contextual bandit, while controlling both algorithmic complexity and computational cost. To this end, FAB-COST uses a combination of two moment projection variational methods: Expectation Propagation (EP), which performs well at the cold start, but becomes slow as the amount of data increases; and Assumed Density Filtering (ADF), which has slower growth of computational cost with data size but requires more data to obtain an acceptable level of accuracy. By switching from EP to ADF when the dataset becomes large, it is able to exploit their complementary strengths. The empirical justification for FAB-COST is presented, and systematically compared to other approaches on simulated data. In a benchmark against the Laplace approximation on real data consisting of over 670, 000 impressions from autotrader.co.uk, FAB-COST demonstrates at one point increase of over 16% in user clicks. On the basis of these results, it is argued that FAB-COST is likely to be an attractive approach to cold-start recommendation systems in a variety of contexts.

Keywords: cold-start learning, expectation propagation, multi-armed bandits, Thompson Sampling, variational inference

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Authors: Divyani Redhu, Manisha Rathaur

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India has emerged as a very lucrative market for the smartphones in a very short span of time. The number of smartphone users here is growing massively with each passing day. Also, the expansion of internet services to far corners of the nation has also given a push to the smartphone revolution in India. Millennial, also known as Generation Y or the Net Generation is the generation born between the early 1980s and mid-1990s (some definitions extending further to early 2000s). Spanning roughly over 15 years, different social classes, cultures, and continents; it is irrational to imagine that millennial have a unified identity. But still, it cannot be denied that the growing millennial population is not only young but is highly tech-savvy too. It is not just the appearance of the device that today; we call it ‘smart’. Rather, it is the numerous tasks and functions that it can perform which has led its name to evolve as that of a ‘smartphone’. From usual tasks that were earlier performed by a simple mobile phone like making calls, sending messages, clicking photographs, recording videos etc.; today, the time has come where most of our day – to – day tasks are being taken care of by our all-time companion, i.e. smartphones. From being our alarm clock to being our note-maker, from our watch to our radio, our book-reader to our reminder, smartphones are present everywhere. Smartphone has now become an essential device for particularly the millennial to communicate not only with their friends but also with their family, colleagues, and teachers. The study by the researchers would be quantitative in nature. For the same, a survey would be conducted in particularly the capital of India, i.e. Delhi and the National Capital Region (NCR), which is the metropolitan area covering the entire National Capital Territory of Delhi and urban areas covering states of Haryana, Uttarakhand, Uttar Pradesh and Rajasthan. The tool of the survey would be a questionnaire and the number of respondents would be 200. The results derived from the study would primarily focus on the increasing reach of smartphones in India, smartphones as technological innovation and convergent tools, smartphone usage pattern of millennial in India, most used applications by the millennial, the average time spent by them, the impact of smartphones on the personal interactions of millennial etc. Thus, talking about the smartphone technology and the millennial in India, it would not be wrong to say that the growth, as well as the potential of the smartphones in India, is still immense. Also, very few technologies have made it possible to give a global exposure to the users and smartphone, if not the only one is certainly an immensely effective one that comes to the mind in this case.

Keywords: Delhi – NCR, India, millennial, smartphone

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Authors: Jaturong Som-ard

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The heavy rainfall from 3rd to 22th January 2017 had swamped much area of Ranot district in southern Thailand. Due to heavy rainfall, the district was flooded which had a lot of effects on economy and social loss. The major objective of this study is to detect flooding extent using Sentinel-1A data and identify a number of damaged buildings over there. The data were collected in two stages as pre-flooding and during flood event. Calibration, speckle filtering, geometric correction, and histogram thresholding were performed with the data, based on intensity spectral values to classify thematic maps. The maps were used to identify flooding extent using change detection, along with the buildings digitized and collected on JOSM desktop. The numbers of damaged buildings were counted within the flooding extent with respect to building data. The total flooded areas were observed as 181.45 sq.km. These areas were mostly occurred at Ban khao, Ranot, Takhria, and Phang Yang sub-districts, respectively. The Ban khao sub-district had more occurrence than the others because this area is located at lower altitude and close to Thale Noi and Thale Luang lakes than others. The numbers of damaged buildings were high in Khlong Daen (726 features), Tha Bon (645 features), and Ranot sub-district (604 features), respectively. The final flood extent map might be very useful for the plan, prevention and management of flood occurrence area. The map of building damage can be used for the quick response, recovery and mitigation to the affected areas for different concern organization.

Keywords: flooding extent, Sentinel-1A data, JOSM desktop, damaged buildings

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Authors: Jeyarajan Sivapathasundram

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Knowledge management has been recognised as an emerging factor for being competitive among institutions and performances in firms. As such, being recognised as knowledge rich institution, higher education institutes have to be recognised knowledge management based resources for achieving competitive advantages. Present research picked result out of postgraduate research conducted in knowledge management at non-state higher educational institutes of Sri Lanka. Besides, the present research aimed to discover knowledge management for competition and firm performances of higher educational institutes out of the result produced by the postgraduate study. Besides, the results are found in a pair that developed out of knowledge management practices and the reason behind the existence of the practices. As such, the present research has developed a filter to pick the pairs that satisfy its condition of competition and performance of the firm. As such, the pair, such as benchmarking is practised to be ethically competing through conducting courses. As the postgraduate research tested results of foreign researches in a qualitative paradigm, the finding of the present research are generalise fact for knowledge management for competitiveness and performances in higher educational institutes. Further, the presented research method used attributes which explain competition and performance in its filter to discover the pairs relevant to competition and performances. As such, the fact in regards to knowledge management for competition and performances in higher educational institutes are presented in the publication that the presentation is out of the generalised result. Therefore, knowledge management for competition and performance in higher educational institutes are generalised.

Keywords: competition in and among higher educational institutes, performances of higher educational institutes, noun based filtering, production out of generalisation of a research

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Authors: Muhammed Rabiu, Moses S. Oluyomi, Joshua Olorundare

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Quarry activities are important to modern day life and the socio-economic development of local communities. Unfortunately, this industry is usually associated with air pollution. To assess the impact of quarry dust on plant biodiversity and agriculture, PM2.5, PM10 and some meteorological parameters were measured using Gas analyzer, handheld thermometer and Multifunction Anemometer (PCE-EM 888) as well as taking a social survey. High amount of particulate matters that exceeded the international standard were recorded at the study locations which include the Julius Berger Quarry and 1km away from the quarry site which serve as the base for the farmlands. The correlation coefficient between the particulate matters with the meteorological parameters of the locations all show a strong relationship with temperature recording a stronger value of 0.952 and 0.931 for PM2.5 and PM10 respectively. Similarly, the coefficient of determination 0.906 and 0.866 shows that temperature has the highest meteorological percentage variation on PM2.5 and PM10. Furthermore, a notable negative impact of quarrying on plant biodiversity and local farm crops are also revealed based on respondents’ results where wide range of local plants were affected with Maize and Azadiracta indica (Neem) been the most with respondent of 31.5% and 27.5%. According to the obtained results, it is highly recommended to develop green belt surrounding the quarrying using pollutant-tolerant trees (usually with broad leaves) in order to restrict spreading of quarrying dust via intercepting, filtering and absorbing pollutants.

Keywords: agriculture, air pollution, biodiversity, quarry

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Authors: Elena Krelja Kurelović, Jasminka Tomljanović, Vlatka Davidović

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The development of web technologies and mobile devices makes creating, accessing, using and sharing information or communicating with each other simpler every day. However, while the amount of information constantly increasing it is becoming harder to effectively organize and find quality information despite the availability of web search engines, filtering and indexing tools. Although digital technologies have overall positive impact on students’ lives, frequent use of these technologies and digital media enriched with dynamic hypertext and hypermedia content, as well as multitasking, distractions caused by notifications, calls or messages; can decrease the attention span, make thinking, memorizing and learning more difficult, which can lead to stress and mental exhaustion. This is referred to as “information overload”, “information glut” or “information anxiety”. Objective of this study is to determine whether students show signs of information overload and to identify the possible predictors. Research was conducted using a questionnaire developed for the purpose of this study. The results show that students frequently use technology (computers, gadgets and digital media), while they show moderate level of information literacy. They have sometimes experienced symptoms of information overload. According to the statistical analysis, higher frequency of technology use and lower level of information literacy are correlated with larger information overload. The multiple regression analysis has confirmed that the combination of these two independent variables has statistically significant predictive capacity for information overload. Therefore, the information science teachers should pay attention to improving the level of students’ information literacy and educate them about the risks of excessive technology use.

Keywords: information overload, computers, mobile devices, digital media, information literacy, students

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Authors: Paiboon Jeamponk, Tasanee Ponglaa, Patchapon Srisanguan

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The aim of this research paper was based on an examination of sources of water supply and water quality for local consumption, conducted at eco-tourism villages of Suan Luang Sub- District Municipality of Amphawa District, Samut Songkram Province. The study incorporated both questionnaire and field work of water testing as the research tool and method. The sample size of 288 households was based on the population of the district, whereas the selected sample water sources were from 60 households: 30 samples were ground water and another 30 were surface water. Degree of heavy metal contamination in the water including copper, iron, manganese, zinc, cadmium and lead was investigated utilizing the Atomic Absorption- Direct Aspiration method. The findings unveiled that 96.0 percent of household water consumption was based on water supply, while the rest on canal, river and rain water. The household behaviour of consumption revealed that 47.2 percent of people routinely consumed water without boiling or filtering prior to consumption. The investigation of water supply quality found that the degree of heavy metal contamination including metal, lead, iron, copper, manganese and cadmium met the standards of the Department of Health.

Keywords: sources of water supply, water quality, water supply, Thailand

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Authors: J. S. Dhillon, K. K. Dhaliwal

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In almost all the digital filtering applications the digital infinite impulse response (IIR) filters are preferred over finite impulse response (FIR) filters because they provide much better performance, less computational cost and have smaller memory requirements for similar magnitude specifications. However, the digital IIR filters are generally multimodal with respect to the filter coefficients and therefore, reliable methods that can provide global optimal solutions are required. The artificial bee colony (ABC) algorithm is one such recently introduced meta-heuristic optimization algorithm. But in some cases it shows insufficiency while searching the solution space resulting in a weak exchange of information and hence is not able to return better solutions. To overcome this deficiency, the opposition based learning strategy is incorporated in ABC and hence a modified version called oppositional artificial bee colony (OABC) algorithm is proposed in this paper. Duplication of members is avoided during the run which also augments the exploration ability. The developed algorithm is then applied for the design of optimal and stable digital IIR filter structure where design of low-pass (LP) and high-pass (HP) filters is carried out. Fuzzy theory is applied to achieve maximize satisfaction of minimum magnitude error and stability constraints. To check the effectiveness of OABC, the results are compared with some well established filter design techniques and it is observed that in most cases OABC returns better or atleast comparable results.

Keywords: digital infinite impulse response filter, artificial bee colony optimization, opposition based learning, digital filter design, multi-parameter optimization

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Authors: Carlos G. Santos, Frederico A. Genezini, A. P. Dos Santos, H. Yorivaz, P. T. D. Siqueira

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The Prompt-Gamma Activation Analysis (PGAA) is a valuable technique for investigating the elemental composition of various samples. However, the installation of a PGAA system entails specific conditions such as filtering the neutron beam according to the target and providing adequate shielding for both users and detectors. These requirements incur substantial costs, exceeding $100,000, including manpower. Nevertheless, a cost-effective approach involves leveraging an existing neutron beam facility to create a hybrid system integrating PGAA and Neutron Tomography (NT). The IEA-R1 nuclear reactor at IPEN/USP possesses an NT facility with suitable conditions for adapting and implementing a PGAA device. The NT facility offers a thermal flux slightly colder and provides shielding for user protection. The key additional requirement involves designing detector shielding to mitigate high gamma ray background and safeguard the HPGe detector from neutron-induced damage. This study employs Monte Carlo simulations with the MCNP6 code to optimize the collimator plug for PGAA within the IEA-R1 NT facility. Three collimator models are proposed and simulated to assess their effectiveness in shielding gamma and neutron radiation from nucleon fission. The aim is to achieve a focused prompt-gamma signal while shielding ambient gamma radiation. The simulation results indicate that one of the proposed designs is particularly suitable for the PGAA-NT hybrid system.

Keywords: MCNP6.1, neutron, prompt-gamma ray, prompt-gamma activation analysis

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Authors: Sozon, Pok Wei Fong, Sia Bee Chuan, Omar Hamdan Mohammad

Abstract:

Owing to the widespread phenomenon of plagiarism and cheating in higher education institutions (HEIs), it is now difficult to ensure academic integrity and quality education. Moreover, the COVID-19 pandemic has intensified the issue by shifting educational institutions into virtual teaching and assessment mode. Thus, there is a need to carry out an extensive and holistic systematic review of the literature to highlight plagiarism and cheating in both prevalence and form among HEIs. This paper systematically reviews the literature concerning academic plagiarism and cheating in HEIs to determine the most common forms and suggest strategies for resolution and boosting the academic integrity of students. The review included 45 articles and publications for the period from February 12, 2018, to September 12, 2022, in the Scopus database aligned with the Systematic Review and Meta-Analysis (PRISMA) guidelines in the selection, filtering, and reporting of the papers for review from which a conclusion can be drawn. Based on the results, out of the studies reviewed, 48% of the quantitative results of students were plagiarized and obtained through cheating, with 84% coming from the fields of Humanities. Moreover, Psychology and Social Sciences studies accumulated 9% and 7% articles respectively. Based on the results, individual factors, institutional factors, and social and cultural factors have contributed to plagiarism and cheating cases in HEIs. The resolution of this issue can be the establishment of ethical and moral development initiatives and modern academic policies and guidelines supported by technological strategies of testing.

Keywords: plagiarism, cheating, systematic review, academic integrity

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Authors: Montree Bunruangses, Sonath Bhattacharyya, Somchat Sonasang, Preecha Yupapin

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A two-level system is manipulated by a microstrip add-drop circuit configured as an atom like system for wave-particle behavior investigation when its traveling speed along the circuit perimeter is the speed of light. The entangled pair formed by the upper and lower sideband peaks is bound by the angular displacement, which is given by 0≤θ≤π/2. The control signals associated with 3-peak signal frequencies are applied by the external inputs via the microstrip add-drop multiplexer ports, where they are time functions without the space term involved. When a system satisfies the speed of light conditions, the mass term has been changed to energy based on the relativistic limit described by the Lorentz factor and Einstein equation. The different applied frequencies can be utilized to form the 3-phase torques that can be applied for quantum engines. The experiment will use the two-level system circuit and be conducted in the laboratory. The 3-phase torques will be recorded and investigated for quantum engine driving purpose. The obtained results will be compared to the simulation. The optimum amplification of torque can be obtained by the resonant successive filtering operation. Torque will be vanished when the system is balanced at the stopped position, where |Time|=0, which is required to be a system stability condition. It will be discussed for future applications. A larger device may be tested in the future for realistic use. A synchronous and asynchronous driven motor is also discussed for the warp drive use.

Keywords: quantum engine, relativistic motor, 3-phase torque, atomic engine

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Authors: Magdalena Igras, Joanna Grzybowska, Mariusz Ziółko

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The study of emotions expressed in emergency phone call is presented, covering both statistical analysis of emotions configurations and an attempt to automatically classify emotions. An emergency call is a situation usually accompanied by intense, authentic emotions. They influence (and may inhibit) the communication between caller and responder. In order to support responders in their responsible and psychically exhaustive work, we studied when and in which combinations emotions appeared in calls. A corpus of 45 hours of conversations (about 3300 calls) from emergency call center was collected. Each recording was manually tagged with labels of emotions valence (positive, negative or neutral), type (sadness, tiredness, anxiety, surprise, stress, anger, fury, calm, relief, compassion, satisfaction, amusement, joy) and arousal (weak, typical, varying, high) on the basis of perceptual judgment of two annotators. As we concluded, basic emotions tend to appear in specific configurations depending on the overall situational context and attitude of speaker. After performing statistical analysis we distinguished four main types of emotional behavior of callers: worry/helplessness (sadness, tiredness, compassion), alarm (anxiety, intense stress), mistake or neutral request for information (calm, surprise, sometimes with amusement) and pretension/insisting (anger, fury). The frequency of profiles was respectively: 51%, 21%, 18% and 8% of recordings. A model of presenting the complex emotional profiles on the two-dimensional (tension-insecurity) plane was introduced. In the stage of acoustic analysis, a set of prosodic parameters, as well as Mel-Frequency Cepstral Coefficients (MFCC) were used. Using these parameters, complex emotional states were modeled with machine learning techniques including Gaussian mixture models, decision trees and discriminant analysis. Results of classification with several methods will be presented and compared with the state of the art results obtained for classification of basic emotions. Future work will include optimization of the algorithm to perform in real time in order to track changes of emotions during a conversation.

Keywords: acoustic analysis, complex emotions, emotion recognition, machine learning

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Authors: Kayode Festus Oyedele, Sunday Oladele, Adaora Chibundu Nduka

Abstract:

The subsurface of a proposed site for building development in Mowe, Nigeria, using Standard Penetration Test (SPT) and Cone Penetrometer Test (CPT) supplemented with Horizontal Electrical Profiling (HEP) was investigated with the aim of evaluating the suitability of the strata for foundation materials. Four SPT and CPT were implemented using 10 tonnes hammer. HEP utilizing Wenner array were performed with inter-electrode spacing of 10 – 60 m along four traverses coincident with each of the SPT and CPT. The HEP data were processed using DIPRO software and textural filtering of the resulting resistivity sections was implemented to enable delineation of hidden layers. Sandy lateritic clay, silty lateritic clay, clay, clayey sand and sand horizons were delineated. The SPT “N” value defined very soft to soft sandy lateritic (<4), stiff silty lateritic clay (7 – 12), very stiff silty clay (12 - 15), clayey sand (15- 20) and sand (27 – 37). Sandy lateritic clay (5-40 kg/cm2) and silty lateritic clay (25 - 65 kg/cm2) were defined from the CPT response. Sandy lateritic clay (220-750 Ωm), clay (< 50 Ωm) and sand (415-5359 Ωm) were delineated from the resistivity sections with two thin layers of silty lateritic clay and clayey sand defined in the texturally filtered resistivity sections. This study concluded that the presence of incompetent thick clayey materials (18 m) beneath the study area makes it unsuitable for shallow foundation. Deep foundation involving piling through the clayey layers to the competent sand at 20 m depth was recommended.

Keywords: cone penetrometer, foundation, lithologic texture, resistivity section, standard penetration test

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Authors: Daniel Adjei, Mesfin Getachew Ayele, Przemyslaw Wachulak, Andrzej Bartnik, Luděk Vyšín, Henryk Fiedorowicz, Inam Ul Ahad, Lukasz Wegrzynski, Anna Wiechecka, Janusz Lekki, Wojciech M. Kwiatek

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Laser produced plasma light sources, emitting high intensity pulses of X-rays, delivering high doses are useful to understand the mechanisms of high dose effects on biological samples. In this study, a desk-top laser plasma soft X-ray source, developed for radio biology research, is presented. The source is based on a double-stream gas puff target, irradiated with a commercial Nd:YAG laser (EKSPLA), which generates laser pulses of 4 ns time duration and energy up to 800 mJ at 10 Hz repetition rate. The source has been optimized for maximum emission in the “water window” wavelength range from 2.3 nm to 4.4 nm by using pure gas (argon, nitrogen and krypton) and spectral filtering. Results of the source characterization measurements and dosimetry of the produced soft X-ray radiation are shown and discussed. The high brightness of the laser produced plasma soft X-ray source and the low penetration depth of the produced X-ray radiation in biological specimen allows a high dose rate to be delivered to the specimen of over 28 Gy/shot; and 280 Gy/s at the maximum repetition rate of the laser system. The source has a unique capability for irradiation of cells with high pulse dose both in vacuum and He-environment. Demonstration of the source to induce DNA double- and single strand breaks will be discussed.

Keywords: laser produced plasma, soft X-rays, radio biology experiments, dosimetry

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Authors: Vabya Kumar Pandit, Mudit Mittal, N. Prahlad Rao, Ramnath Babu

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TeamIndus is the only Indian team competing for the Google Lunar XPRIZE(GLXP). The GLXP is a global competition to challenge the private entities to soft land a rover on the moon, travel minimum 500 meters and transmit high definition images and videos to Earth. Towards this goal, the TeamIndus strategy is to design and developed lunar lander that will deliver a rover onto the surface of the moon which will accomplish GLXP mission objectives. This paper showcases the various system level noise control techniques adopted by Electrical Distribution System (EDS), to achieve the required Electromagnetic Compatibility (EMC) of the spacecraft. The design guidelines followed to control Electromagnetic Interference by proper electronic package design, grounding, shielding, filtering, and cable routing within the stipulated mass budget, are explained. The paper also deals with the challenges of achieving Electromagnetic Cleanliness in presence of various Commercial Off-The-Shelf (COTS) and In-House developed components. The methods of minimizing Electrostatic Discharge (ESD) by identifying the potential noise sources, susceptible areas for charge accumulation and the methodology to prevent arcing inside spacecraft are explained. The paper then provides the EMC requirements matrix derived from the mission requirements to meet the overall Electromagnetic compatibility of the Spacecraft.

Keywords: electromagnetic compatibility, electrostatic discharge, electrical distribution systems, grounding schemes, light weight harnessing

Procedia PDF Downloads 293

Authors: Shao Bo Cheng, Yong-Jin Han, Se Young Park, Seong-Bae Park

Abstract:

Consumer-to-Consumer (C2C) E-commerce has been growing at a very high speed in recent years. Since identical or nearly-same kinds of products compete one another by relying on keyword search in C2C E-commerce, some sellers describe their products with spam keywords that are popular but are not related to their products. Though such products get more chances to be retrieved and selected by consumers than those without spam keywords, the spam keywords mislead the consumers and waste their time. This problem has been reported in many commercial services like e-bay and taobao, but there have been little research to solve this problem. As a solution to this problem, this paper proposes a method to classify whether keywords of a product are spam or not. The proposed method assumes that a keyword for a given product is more reliable if the keyword is observed commonly in specifications of products which are the same or the same kind as the given product. This is because that a hierarchical category of a product in general determined precisely by a seller of the product and so is the specification of the product. Since higher layers of the hierarchical category represent more general kinds of products, a reliable degree is differently determined according to the layers. Hence, reliable degrees from different layers of a hierarchical category become features for keywords and they are used together with features only from specifications for classification of the keywords. Support Vector Machines are adopted as a basic classifier using the features, since it is powerful, and widely used in many classification tasks. In the experiments, the proposed method is evaluated with a golden standard dataset from Yi-han-wang, a Chinese C2C e-commerce, and is compared with a baseline method that does not consider the hierarchical category. The experimental results show that the proposed method outperforms the baseline in F1-measure, which proves that spam keywords are effectively identified by a hierarchical category in C2C e-commerce.

Keywords: spam keyword, e-commerce, keyword features, spam filtering

Procedia PDF Downloads 294