Search results for: real time simulator

Authors: Pradip Kumar Das

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India is a developing country and is also one of the most industrialized developing countries of the world. In post-independence period, industry has grown rapidly in India and with industrialization corporate sector in the country has been growing day after day. Nowadays, the investment is not limited to be shareholders alone, apart from the shareholders the common people of the society have also started investing in shares of the corporate sectors. Thus, the responsibilities of the corporate sectors have increased much. Corporate financial reporting refers to a system which provides valuable information to different types of users in the society for taking resourceful decisions with regards to investment policy, organization credit worthiness, profitability, liquidity, provision of taxation etc. The quality of information available to different users fosters the efficient allocation of resources which are very urgent for economic development of a country like India. It is the responsibility of the management of the corporate sector to convey reliable and authentic information with the help of generally accepted accounting principles. Corporate sectors which disclose information through annual reports should be sufficient enough for the purpose of bringing out the salient features relating to business performances and other activities. However, the disclosures practices of the corporate sectors though annual reports have undergone several major changes from time to time. Many a time, these vital changes are in the fashion of presenting information in the annual reports and addition of so many non-statutory disclosures of the company. Very often managements of the corporate sectors are blamed for concealing true picture which is not desirable at all. The corporate financial reporting practice which in the current period has gained a place of prime importance suffers from certain limitations and invites question from the public about its reliability. Thus, the wide gap created by management between the exhibited picture and the real picture sometimes attains to such extent that the purpose of the reporting practice loses its importance. The requirement of full and adequate disclosure of information including information relating to human resources in the annual report in free trade economy of India helps the prospective investors to select the best portfolio of their investments. This paper is a reflection of a modest attempt of the author to highlight the corporate reporting practices followed in India. A cursory glance of the conceptual study shows limitations along with reliability of the reporting practices and suggests measures to overcome the shortcomings of the financial reporting practices.

Keywords: corporate enterprise, cursory glance, portfolio, yawning gap

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Authors: S. Abdulkadir, I. Y. Moh’d, S. U. Kunya, U. Nuruddeen

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The basis of any contract formation between the client and contractor is the budgeted cost and the estimated duration of projects. These variables are paramount important to project's sponsor in a construction projects and in assessing the success or viability of construction projects. Despite the availability of various techniques of cost and time control, many projects failed to achieve their initial estimated cost and time. The paper evaluate the inhibiting factors of cost and time control in Nigerian construction practice and comparing the result with the United Kingdom practice as identified by one researcher. The populations of the study are construction professionals within Bauchi and Gombe state, Nigeria, a judgmental sampling employed in determining the size of respondents. Descriptive statistics used in analyzing the data in SPSS. Design change, project fraud and corruption, financing and payment of completed work found to be common among the top five inhibiting factors of cost and time control in the study area. Furthermore, the result had shown some comprising with slight contrast as in the case of United Kingdom practice. Study recommend the adaptation of mitigation measures developed in the UK prior to assessing its effectiveness and so also developing a mitigating measure for other top factors that are not within the one developed in United Kingdom practice. Also, it recommends a wider assessing comparison on the modify inhibiting factors of cost and time control as revealed by the study to cover almost all part of Nigeria.

Keywords: comparison, cost, inhibiting factor, United Kingdom, time

Procedia PDF Downloads 427

Authors: Sunghoon Park, Hank Kim, Jinwon An, Sungzoon Cho

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Internet of Things allows one to collect data from facilities which are then used to monitor them and even predict malfunctions in advance. Conventional quality control methods focus on setting a normal range on a sensor value defined between a lower control limit and an upper control limit, and declaring as an anomaly anything falling outside it. However, interactions among sensor values are ignored, thus leading to suboptimal performance. We propose a multivariate approach which takes into account many sensor values at the same time. In particular Gaussian Mixture Model is used which is trained to maximize likelihood value using Expectation-Maximization algorithm. The number of Gaussian component distributions is determined by Bayesian Information Criterion. The negative Log likelihood value is used as an anomaly score. The actual usage scenario goes like a following. For each instance of sensor values from a facility, an anomaly score is computed. If it is larger than a threshold, an alarm will go off and a human expert intervenes and checks the system. A real world data from Building energy system was used to test the model.

Keywords: facility anomaly detection, gaussian mixture model, anomaly score, expectation maximization algorithm

Procedia PDF Downloads 261

Authors: Svilen Dimitrov, Manthan Pancholi, Norbert Schmitz, Didier Stricker

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This paper presents the end-to-end development of a wearable motion sensing harness consisting of computational unit and four inertial measurement units to control three smartphone therapeutic games for children. The inertial data is processed in real time to obtain lower body motion information like knee raises, feet taps and squads. By providing a Wi-Fi connection interface the sensor harness acts wireless remote control for smartphone applications. By performing various lower body movements the users provoke corresponding game state changes. In contrary to the current similar offers, like Nintendo Wii Remote, Xbox Kinect and Playstation Move, this product, consisting of the sensor harness and the applications on top of it, are fully wearable, which means they do not rely on the user to be bound to concrete soft- or hardwareequipped space.

Keywords: wearable harness, inertial measurement units, smartphone therapeutic games, motion tracking, lower-body activity monitoring

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Authors: Mohammed Saeed Jawad

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Metaverse involves the convergence of three major technologies trends of AI, VR, and AR. Together these three technologies can provide an entirely new channel for delivering healthcare with great potential to lower costs and improve patient outcomes on a larger scale. Telepresence is the technology that allows people to be together even if they are physically apart. Medical doctors can be symbolic as interactive avatars developed to have smart conversations and medical recommendations for patients at the different stages of the treatment. Medical digital assets such as Medical IoT for real-time remote healthcare monitoring as well as the symbolic doctors’ avatars as well as the hospital and clinical physical constructions and layout can be immersed in extended realities 3D metaverse environments where doctors, nurses, and patients can interact and socialized with the related digital assets that facilitate the data analytics of the sensed and collected personal medical data with visualized interaction of the digital twin of the patient’s body as well as the medical doctors' smart conversation and consultation or even in a guided remote-surgery operation.

Keywords: personal healthcare, metaverse, telemedicine, telepresence, avatar, medical consultation, remote-surgery

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Authors: Ather Saeed, Arif Khan, Jeffrey Gosper

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Sensor devices are prone to errors and sudden node failures, which are difficult to detect in a timely manner when deployed in real-time, hazardous, large-scale harsh environments and in medical emergencies. Therefore, the loss of data can be life-threatening when the sensed phenomenon is not disseminated due to sudden node failure, battery depletion or temporary malfunctioning. We introduce a set of partial differential equations for localizing faults, similar to Green’s and Maxwell’s equations used in Electrostatics and Electromagnetism. We introduce a node organization and clustering scheme for self-stabilizing sensor networks. Green’s theorem is applied to regions where the curve is closed and continuously differentiable to ensure network connectivity. Experimental results show that the proposed GTFD (Green’s Theorem fault-detection and Self-stabilization) protocol not only detects faulty nodes but also accurately generates network stability graphs where urgent intervention is required for dynamically self-stabilizing the network.

Keywords: Green’s Theorem, self-stabilization, fault-localization, RSSI, WSN, clustering

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Authors: Michael K. O. Ayomoh, Oyindamola A. Omotuyi

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Autonomous mobile robots deployed to explore or operate in a never explored or an abandoned sub-surface mine requires extreme effectiveness in coordination and communication. In a bid to transmit information from the depth of the mine to the external surface in real-time and amidst diverse physical, chemical and virtual impediments, the concept of unified cooperative robots is seen to be a proficient approach. This paper presents an effective [human → robot → task] coordination framework for effective exploration of an abandoned underground mine. The problem addressed in this research is basically the development of a globalized optimization model premised on time series differentiation and geometrical configurations for effective positioning of the two classes of robots in the cooperation namely the outermost stationary master (OSM) robots and the innermost dynamic task (IDT) robots for effective bi-directional signal transmission. In addition, the synchronization of a vision system and wireless communication system for both categories of robots, fiber optics system for the OSM robots in cases of highly sloppy or vertical mine channels and an autonomous battery recharging capability for the IDT robots further enhanced the proposed concept. The OSM robots are the master robots which are positioned at strategic locations starting from the mine open surface down to its base using a fiber-optic cable or a wireless communication medium all subject to the identified mine geometrical configuration. The OSM robots are usually stationary and function by coordinating the transmission of signals from the IDT robots at the base of the mine to the surface and in a reverse order based on human decisions at the surface control station. The proposed scheme also presents an optimized number of robots required to form the cooperation in a bid to reduce overall operational cost and system complexity.

Keywords: sub-surface mine, wireless communication, outermost stationary master robots, inner-most dynamic robots, fiber optic

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Authors: Md. Abu Sufian, Robiqul Islam, Imam Hossain Shajid, Mahesh Hanumanthu, Jarasree Varadarajan, Md. Sipon Miah, Mingbo Niu

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Coronary Heart Disease (CHD) remains a principal cause of global morbidity and mortality, characterized by atherosclerosis—the build-up of fatty deposits inside the arteries. The study introduces an innovative methodology that leverages cloud-based platforms like AWS Live Streaming and Artificial Intelligence (AI) to early detect and prevent CHD symptoms in web applications. By employing novel simulation processes and AI algorithms, this research aims to significantly mitigate the health and societal impacts of CHD. Methodology: This study introduces a novel simulation process alongside a multi-phased model development strategy. Initially, health-related data, including heart rate variability, blood pressure, lipid profiles, and ECG readings, were collected through user interactions with web-based applications as well as API Integration. The novel simulation process involved creating synthetic datasets that mimic early-stage CHD symptoms, allowing for the refinement and training of AI algorithms under controlled conditions without compromising patient privacy. AWS Live Streaming was utilized to capture real-time health data, which was then processed and analysed using advanced AI techniques. The novel aspect of our methodology lies in the simulation of CHD symptom progression, which provides a dynamic training environment for our AI models enhancing their predictive accuracy and robustness. Model Development: it developed a machine learning model trained on both real and simulated datasets. Incorporating a variety of algorithms including neural networks and ensemble learning model to identify early signs of CHD. The model's continuous learning mechanism allows it to evolve adapting to new data inputs and improving its predictive performance over time. Results and Findings: The deployment of our model yielded promising results. In the validation phase, it achieved an accuracy of 92% in predicting early CHD symptoms surpassing existing models. The precision and recall metrics stood at 89% and 91% respectively, indicating a high level of reliability in identifying at-risk individuals. These results underscore the effectiveness of combining live data streaming with AI in the early detection of CHD. Societal Implications: The implementation of cloud-based AI for CHD symptom detection represents a significant step forward in preventive healthcare. By facilitating early intervention, this approach has the potential to reduce the incidence of CHD-related complications, decrease healthcare costs, and improve patient outcomes. Moreover, the accessibility and scalability of cloud-based solutions democratize advanced health monitoring, making it available to a broader population. This study illustrates the transformative potential of integrating technology and healthcare, setting a new standard for the early detection and management of chronic diseases.

Keywords: coronary heart disease, cloud-based ai, machine learning, novel simulation techniques, early detection, preventive healthcare

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Authors: Cihat Aşan

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Istanbul Strait is a crucial and narrow waterway, not only having a role in linking two continents but also has a crossover mission for the petroleum, which is the biggest energy resource, between its supply and demand sources. Besides its substantial features, sensitivities like around 18 million populations in surroundings, military facilities, ports, oil lay down areas etc. also brings the high risk to use of Istanbul Strait. Based on the statistics of Turkish Ministry of Transportation, Maritime and Communication, although the number of vessel passage in Istanbul Strait is declining, tonnage of hazardous and flammable cargo like oil and chemical transportation is increasing and subsequently the risk of oil pollution, loss of life and property is also rising. Based on the mentioned above; it is crucial to be prepared for the initial and subsequent response to eventual ship sourced oil spill which may cause to block the Strait for an unbearable duration. In this study; preconditioned Istanbul Strait sensitive areas studies has been taken into account and possible oil spill scenario is loaded to PISCES 2 (Potential Incident Simulation Control and Evaluation System) decision support system for the determined specific sea area. Consequences of the simulation like oil expanding process, required number and types of assets to response, had in hand and evaluated.

Keywords: Istanbul strait, oil spill, PISCES simulator, initial response

Procedia PDF Downloads 328

Authors: Tao Ding, Danjia Yan, Jinye Li, Chao Ren, Xinhua Hu

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The paper based on the research background of the current situation of water shortage in China and intelligent management of water resources in the information era. And the paper adopts WebGIS technology, combining the mathematical model of water resources management to develop a WebGIS-based water environment capacity inquiry and polluted water emission planning. The research significance of the paper is that it can inquiry the water environment capacity of Jinhua City in real time and plan how to drain polluted water into the river, so as to realize the effective management of water resources. This system makes sewage planning more convenient and faster. For the planning of the discharge enterprise, the decision on the optimal location of the sewage outlet can be achieved through calculation of the Sewage discharge planning model in the river, without the need for site visits. The system can achieve effective management of water resources and has great application value.

Keywords: sewerage planning, water environment capacity, water resources management, WebGIS

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Authors: Amit Kumar Happy

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This paper is motivated by the importance of multi-sensor image fusion with a specific focus on infrared (IR) and visual image (VI) fusion for various applications, including military reconnaissance. Image fusion can be defined as the process of combining two or more source images into a single composite image with extended information content that improves visual perception or feature extraction. These images can be from different modalities like visible camera & IR thermal imager. While visible images are captured by reflected radiations in the visible spectrum, the thermal images are formed from thermal radiation (infrared) that may be reflected or self-emitted. A digital color camera captures the visible source image, and a thermal infrared camera acquires the thermal source image. In this paper, some image fusion algorithms based upon multi-scale transform (MST) and region-based selection rule with consistency verification have been proposed and presented. This research includes the implementation of the proposed image fusion algorithm in MATLAB along with a comparative analysis to decide the optimum number of levels for MST and the coefficient fusion rule. The results are presented, and several commonly used evaluation metrics are used to assess the suggested method's validity. Experiments show that the proposed approach is capable of producing good fusion results. While deploying our image fusion algorithm approaches, we observe several challenges from the popular image fusion methods. While high computational cost and complex processing steps of image fusion algorithms provide accurate fused results, they also make it hard to become deployed in systems and applications that require a real-time operation, high flexibility, and low computation ability. So, the methods presented in this paper offer good results with minimum time complexity.

Keywords: image fusion, IR thermal imager, multi-sensor, multi-scale transform

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Authors: Cesar Eduardo Hernández Curiel, Victor Hugo Benítez Baltazar, Jesús Horacio Pacheco Ramírez

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This paper is devoted to present the advances in the design of a prototype that is able to supervise the complex behavior of water quality parameters such as pH and temperature, via a real-time monitoring system. The current water quality tests that are performed in government water quality institutions in Mexico are carried out in problematic locations and they require taking manual samples. The water samples are then taken to the institution laboratory for examination. In order to automate this process, a water quality monitoring system based on wireless sensor networks is proposed. The system consists of a sensor node which contains one pH sensor, one temperature sensor, a microcontroller, and a ZigBee radio, and a base station composed by a ZigBee radio and a PC. The progress in this investigation shows the development of a water quality monitoring system. Due to recent events that affected water quality in Mexico, the main motivation of this study is to address water quality monitoring systems, so in the near future, a more robust, affordable, and reliable system can be deployed.

Keywords: pH measurement, water quality monitoring, wireless sensor networks, ZigBee

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Authors: N. Kaneva, A. Bojinova, K. Papazova

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Thin ZnO films are deposited on glass substrates via sol–gel method and dip-coating. The films are prepared from zinc acetate dehydrate as a starting reagent. After that the as-prepared ZnO sol is aged for different periods (0, 1, 3, 5, 10, 15, and 30 days). Nanocrystalline thin films are deposited from various sols. The effect ZnO sols aging time on the structural and photocatalytic properties of the films is studied. The films surface is studied by Scanning Electron Microscopy. The effect of the aging time of the starting solution is studied inrespect to photocatalytic degradation of Reactive Black 5 (RB5) by UV-vis spectroscopy. The experiments are conducted upon UV-light illumination and in complete darkness. The variation of the absorption spectra shows the degradation of RB5 dissolved in water, as a result of the reaction acurring on the surface of the films, and promoted by UV irradiation. The initial concentrations of dye (5, 10 and 20 ppm) and the effect of the aging time are varied during the experiments. The results show, that the increasing aging time of starting solution with respect to ZnO generally promotes photocatalytic activity. The thin films obtained from ZnO sol, which is aged 30 days have best photocatalytic degradation of the dye (97,22%) in comparison with the freshly prepared ones (65,92%). The samples and photocatalytic experimental results are reproducible. Nevertheless, all films exhibit a substantial activity in both UV light and darkness, which is promising for the development of new ZnO photocatalysts by sol-gel method.

Keywords: ZnO thin films, sol-gel, photocatalysis, aging time

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Authors: P. Jost, L. Muckova, M. Matula, J. Pejchal, D. Jun, R. Stetina

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Sulfur mustard (bis(2-chlorethyl) sulfide) is highly toxic, chemical warfare agent that has been used in the past in several armed conflicts. Except for the skin, respiratory tract is one of the important routes of exposure. The elucidation and understanding of the mechanism of toxicity of SM have been effort intensive research. The multiple targets character of SM caused cellular damage resulted in activation of many different mechanisms which contribute to cellular response and participate in the final cytopathology effect. In our present work, we compared time-dependent changes in sulfur mustard exposed adult human lung fibroblasts NHLF and lung epithelial alveolar cell line A-549. Cell viability (MTT assay, Calcein-AM assay, and xCELLigence - real-time cell analysis), apoptosis (flow cytometry), mitochondrial membrane potential (Δψm, flow cytometry), reactive oxygen species induction (DC and cell cycle distribution (flow cytometry) were studied. We observed significantly decreased mitochondrial membrane potential and subsequent induction of apoptosis correlating with decreased cellular viability in the sulfur mustard exposed cells. In low concentrations, sulfur mustard-induced S-phase cell cycle arrest, on the other hand, high concentrations, cell cycle phase distribution of sulfur mustard exposed cells resembled cell cycle phase distribution of control group, which implies nonspecific cell cycle inhibition. Epithelial cells A-549 was found as more sensible to sulfur mustard toxicity. Acknowledgements: This work was supported by a long-term organization development plan Medical Aspects of Weapons of Mass Destruction of the Faculty of Military Health Sciences, University of Defence.

Keywords: apoptosis, cell cycle, cytotoxicity, sulfur mustard

Procedia PDF Downloads 176

Authors: Paolo Pilloni, Fabrizio Mulas, Salvatore Carta

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Nowadays, several research studies point up that an active lifestyle is essential for physical and mental health benefits. Mobile phones have greatly influenced people’s habits and attitudes also in the way they exercise. Our research work is mainly focused on investigating how to exploit mobile technologies to favour people’s exertion experience. To this end, we developed an exertion framework users can exploit through a real world mobile application, called BLINDED, designed to act as a virtual personal trainer to support runners during their trainings. In this work, inspired by both previous findings in the field of interaction design for people with visual impairments, feedback gathered from real users of our framework, and positive results obtained from two experimentations, we present some new interaction facilities we designed to enhance the interaction experience during a training. The positive obtained results helped us to derive some interaction design recommendations we believe will be a valid support for designers of future mobile systems conceived to be used in circumstances where there are limited possibilities of interaction.

Keywords: human computer interaction, interaction design guidelines, persuasive mobile technologies for sport and health

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Authors: Emmanuel Uba, Lily Chimuanya, Maryam Tar

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Orthographic engineering is no longer the preserve of the Short Messaging Service (SMS), which is characterised by limited space. Such stylistic creativity or deviation is fast creeping into real-time messaging, popularly known as Instant Messaging (IM), despite the large number of characters allowed. This occurs at various linguistic levels: phonology, morphology, syntax, etc. Nigerians are not immune to this linguistic stylisation. This study investigates the phonological and meta-phonological conventions of the messages sent and received via WhatsApp by Nigerian graduates. This is ontological study of 250 instant messages collected from 98 graduates from different ethnic groups in Nigeria. The selection and analysis of the messages are based on figure and ground principle. The results reveal the use of accent stylisation, phoneme substitution, blending, consonantisation (a specialised form of deletion targeting vowels), numerophony (using a figure/number, usually 1-10, to represent a word or syllable that has the same sound) and phonetic respelling in the IMs sent by Nigerians. The study confirms the existence of linguistic creativity.

Keywords: figure and ground principle, instant messaging, linguistic stylisation, meta-phonology

Procedia PDF Downloads 380

Authors: Benjaporn Buranrat, Nootchanat Mairuae

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Cratoxylum formosum (Jack) Dyer (CF) has been used for the traditional medicines in South East Asian and Thailand. Normally, northeast Thai vegetables have proven cytotoxic to many cancer cells. Therefore, the present study aims to explore the molecular mechanisms underlying CF-induced cancer cell death and apoptosis on breast and liver cancer cells. The cytotoxicity and antiproliferative effects of CF on the human breast MCF-7 and liver HepG2 cancer cell lines were evaluated using sulforhodamine B assay and colony formation assay. Cell migration assay was measured using wound healing assay. The apoptosis induction mechanisms were investigated through reactive oxygen species formation, caspase 3 activity, and JC-1 activity. Gene expression by real-time PCR and apoptosis related protein levels by Western blot analysis. CF induced MCF-7 and HepG2 cell death by time- and dose-dependent manner. Furthermore, CF had the greater cytotoxic potency on MCF-7 more than HepG2 cells with IC50 values of 85.70+4.52 μM and 219.03±9.96 μM respectively, at 24 h. Treatment with CF also caused a dose-dependent decrease in colony forming ability and cell migration, especially on MCF-7 cells. CF induced ROS formation, increased caspase 3 activities, and decreased the mitochondrial membrane potential, and causing apoptotic body production and DNA fragmentation. CF significantly decreased expression of the cell cycle regulatory protein RAC1 and downstream proteins, cdk6. Additionally, CF enhanced p21 and reduced cyclin D1 protein levels. CF leaf extract induced cell death, apoptosis, antimigration in both of MCF-7 and HepG2 cells. CF could be useful for developing to anticancer drug candidate for breast and liver cancer therapy.

Keywords: cratoxylum formosum (jack) dyer, breast cancer, liver cancer, cell death

Procedia PDF Downloads 199

Authors: Hyeon-Seung Kim, Bit-Na Cho, Tae-Woon Jeong, Soo-Young Yoon, Leen-Seok Kang

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Recently, a construction project has been large in the size and complicated in the site work. The web-cameras are used to manage the construction site of such a large construction project. They can be used for monitoring the construction schedule as compared to the actual work image of the planned work schedule. Specially, because the 4D CAD system that the construction appearance is continually simulated in a 3D CAD object by work schedule is widely applied to the construction project, the comparison system between the real image of actual work appearance by web-camera and the simulated image of planned work appearance by 3D CAD object can be an intelligent construction schedule management system (ICON). The delayed activities comparing with the planned schedule can be simulated by red color in the ICON as a virtual reality object. This study developed the ICON and it was verified in a real bridge construction project in Korea. To verify the developed system, a web-camera was installed and operated in a case project for a month. Because the angle and zooming of the web-camera can be operated by Internet, a project manager can easily monitor and assume the corrective action.

Keywords: 4D CAD, web-camera, ICON (intelligent construction schedule management system), 3D object image

Procedia PDF Downloads 497

Authors: Watcharapan Sukkerd, Teeradej Wuttipornpun

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This paper aims to present non-population search algorithms called tabu search (TS), simulated annealing (SA) and variable neighborhood search (VNS) to minimize the total cost of capacitated MRP problem in multi-stage assembly flow shop with two alternative machines. There are three main steps for the algorithm. Firstly, an initial sequence of orders is constructed by a simple due date-based dispatching rule. Secondly, the sequence of orders is repeatedly improved to reduce the total cost by applying TS, SA and VNS separately. Finally, the total cost is further reduced by optimizing the start time of each operation using the linear programming (LP) model. Parameters of the algorithm are tuned by using real data from automotive companies. The result shows that VNS significantly outperforms TS, SA and the existing algorithm.

Keywords: capacitated MRP, tabu search, simulated annealing, variable neighborhood search, linear programming, assembly flow shop, application in industry

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Authors: Suha I. Al-Nassar, K. M. Adel, F. Zainab

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This work was devoted for producing ZnO nanoparticles by pulsed laser ablation (PLA) of Zn metal plate in the aqueous environment of cetyl trimethyl ammonium bromide (CTAB) using Q-Switched Nd:YAG pulsed laser with wavelength= 1064 nm, Rep. rate= 10 Hz, Pulse duration= 6 ns and laser energy 50 mJ. Solution of nanoparticles is found stable in the colloidal form for a long time. The effect of ablation time on the optical and structure of ZnO was studied is characterized by UV-visible absorption. UV-visible absorption spectrum has four peaks at 256, 259, 265, 322 nm for ablation time (5, 10, 15, and 20 sec) respectively, our results show that UV–vis spectra show a blue shift in the presence of CTAB with decrease the ablation time and blue shift indicated to get smaller size of nanoparticles. The blue shift in the absorption edge indicates the quantum confinement property of nanoparticles. Also, FTIR transmittance spectra of ZnO2 nanoparticles prepared in these states show a characteristic ZnO absorption at 435–445cm^−1.

Keywords: zinc oxide nanoparticles, CTAB solution, pulsed laser ablation technique, spectroscopic characterization

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Authors: Akash Verma, Sujit Kumar Samanta

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This study examines a discrete-time Geo/G/1 queueing-inventory system attached with (s, Q) inventory policy. Assume that the customers follow the Bernoulli process on arrival. Each customer demands a single item with arbitrarily distributed service time. The inventory is replenished by an outside supplier, and the lead time for the replenishment is determined by a geometric distribution. There is a single server and infinite waiting space in this facility. Demands must wait in the specified waiting area during a stock-out period. The customers are served on a first-come-first-served basis. With the help of the embedded Markov chain technique, we determine the joint probability distributions of the number of customers in the system and the number of items in stock at the post-departure epoch using the Matrix Analytic approach. We relate the system length distribution at post-departure and outside observer's epochs to determine the joint probability distribution at the outside observer's epoch. We use probability distributions at random epochs to determine the waiting time distribution. We obtain the performance measures to construct the cost function. The optimum values of the order quantity and reordering point are found numerically for the variety of model parameters.

Keywords: discrete-time queueing inventory model, matrix analytic method, waiting-time analysis, cost optimization

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Authors: Le Xuan Cau

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Flash flood is occurred in short time rainfall interval: from 1 hour to 12 hours in small and medium basins. Flash floods typically have two characteristics: large water flow and big flow velocity. Flash flood is occurred at hill valley site (strip of lowland of terrain) in a catchment with large enough distribution area, steep basin slope, and heavy rainfall. The risk of flash floods is determined through Gridded Basin Flash Flood Potential Index (GBFFPI). Flash Flood Potential Index (FFPI) is determined through terrain slope flash flood index, soil erosion flash flood index, land cover flash floods index, land use flash flood index, rainfall flash flood index. Determining GBFFPI, each cell in a map can be considered as outlet of a water accumulation basin. GBFFPI of the cell is determined as basin average value of FFPI of the corresponding water accumulation basin. Based on GIS, a tool is developed to compute GBFFPI using ArcObjects SDK for .NET. The maps of GBFFPI are built in two types: GBFFPI including rainfall flash flood index (real time flash flood warning) or GBFFPI excluding rainfall flash flood index. GBFFPI Tool can be used to determine a high flash flood potential site in a large region as quick as possible. The GBFFPI is improved from conventional FFPI. The advantage of GBFFPI is that GBFFPI is taking into account the basin response (interaction of cells) and determines more true flash flood site (strip of lowland of terrain) while conventional FFPI is taking into account single cell and does not consider the interaction between cells. The GBFFPI Map of QuangNam, QuangNgai, DaNang, Hue is built and exported to Google Earth. The obtained map proves scientific basis of GBFFPI.

Keywords: ArcObjects SDK for NET, basin average value of FFPI, gridded basin flash flood potential index, GBFFPI map

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Authors: V. B. Bastos, M. P. Lima, P. R. G. Kurka

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This paper applies to the creation of virtual 3D environments for the study and development of mobile robot image based navigation algorithms and techniques, which need to operate robustly and efficiently. The test of these algorithms can be performed in a physical way, from conducting experiments on a prototype, or by numerical simulations. Current simulation platforms for robotic applications do not have flexible and updated models for image rendering, being unable to reproduce complex light effects and materials. Thus, it is necessary to create a test platform that integrates sophisticated simulated applications of real environments for navigation, with data and image processing. This work proposes the development of a high-level platform for building 3D model’s environments and the test of image-based navigation algorithms for mobile robots. Techniques were used for applying texture and lighting effects in order to accurately represent the generation of rendered images regarding the real world version. The application will integrate image processing scripts, trajectory control, dynamic modeling and simulation techniques for physics representation and picture rendering with the open source 3D creation suite - Blender.

Keywords: simulation, visual navigation, mobile robot, data visualization

Procedia PDF Downloads 243

Authors: Amaladhithyan Krishnamoorthy, Ruvaitha Banu

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Vision is considered as the most important sense in humans, without which leading a normal can be often difficult. There are many existing smart canes for visually impaired with obstacle detection using ultrasonic transducer to help them navigate. Though the basic smart cane increases the safety of the users, it does not help in filling the void of visual loss. This paper introduces the concept of Digi-Buddy which is an evolved smart cane for visually impaired. The cane consists for several modules, apart from the basic obstacle detection features; the Digi-Buddy assists the user by capturing video/images and streams them to the server using a wide-angled camera, which then detects the objects using Deep Convolutional Neural Network. In addition to determining what the particular image/object is, the distance of the object is assessed by the ultrasonic transducer. The sound generation application, modelled with the help of Natural Language Processing is used to convert the processed images/object into audio. The object detected is signified by its name which is transmitted to the user with the help of Bluetooth hear phones. The object detection is extended to facial recognition which maps the faces of the person the user meets in the database of face images and alerts the user about the person. One of other crucial function consists of an automatic-intimation-alarm which is triggered when the user is in an emergency. If the user recovers within a set time, a button is provisioned in the cane to stop the alarm. Else an automatic intimation is sent to friends and family about the whereabouts of the user using GPS. In addition to safety and security by the existing smart canes, the proposed concept devices to be implemented as a prototype helping visually-impaired visualize their surroundings through audio more in an amicable way.

Keywords: artificial intelligence, facial recognition, natural language processing, internet of things

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Authors: Amit Kumar, Himanshu Singal, Arnav Bhavsar

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In this modern era of automation, most of the academic exams and competitive exams are Multiple Choice Questions (MCQ). The responses of these MCQ based exams are recorded in the Optical Mark Reader (OMR) sheet. Evaluation of the OMR sheet requires separate specialized machines for scanning and marking. The sheets used by these machines are special and costs more than a normal sheet. Available process is non-economical and dependent on paper thickness, scanning quality, paper orientation, special hardware and customized software. This study tries to tackle the problem of evaluating the OMR sheet without any special hardware and making the whole process economical. We propose an image processing based algorithm which can be used to read and evaluate the scanned OMR sheets with no special hardware required. It will eliminate the use of special OMR sheet. Responses recorded in normal sheet is enough for evaluation. The proposed system takes care of color, brightness, rotation, little imperfections in the OMR sheet images.

Keywords: OMR, image processing, hough circle trans-form, interpolation, detection, binary thresholding

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Authors: Lukas Reznak, Maria Reznakova

Abstract:

Recession of an economy has a profound negative effect on all involved stakeholders. It follows that timely prediction of recessions has been of utmost interest both in the theoretical research and in practical macroeconomic modelling. Current mainstream of recession prediction is based on standard OLS models of continuous GDP using macroeconomic data. This approach is not suitable for two reasons: the standard continuous models are proving to be obsolete and the macroeconomic data are unreliable, often revised many years retroactively. The aim of the paper is to explore a different branch of recession forecasting research theory and verify the findings on real data of the Czech Republic and Germany. In the paper, the authors present a family of discrete choice probit models with parameters estimated by the method of maximum likelihood. In the basic form, the probits model a univariate series of recessions and expansions in the economic cycle for a given country. The majority of the paper deals with more complex model structures, namely dynamic and bivariate extensions. The dynamic structure models the autoregressive nature of recessions, taking into consideration previous economic activity to predict the development in subsequent periods. Bivariate extensions utilize information from a foreign economy by incorporating correlation of error terms and thus modelling the dependencies of the two countries. Bivariate models predict a bivariate time series of economic states in both economies and thus enhance the predictive performance. A vital enabler of timely and successful recession forecasting are reliable and readily available data. Leading indicators, namely the yield curve and the stock market indices, represent an ideal data base, as the pieces of information is available in advance and do not undergo any retroactive revisions. As importantly, the combination of yield curve and stock market indices reflect a range of macroeconomic and financial market investors’ trends which influence the economic cycle. These theoretical approaches are applied on real data of Czech Republic and Germany. Two models for each country were identified – each for in-sample and out-of-sample predictive purposes. All four followed a bivariate structure, while three contained a dynamic component.

Keywords: bivariate probit, leading indicators, recession forecasting, Czech Republic, Germany

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Authors: Yunwei Zhang, Qiaochu Tang, Yao Zhang, Jiabin Wang, Ulrich Stimming, Alpha Lee

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Forecasting the state of health and remaining useful life of Li-ion batteries is an unsolved challenge that limits technologies such as consumer electronics and electric vehicles. Here we build an accurate battery forecasting system by combining electrochemical impedance spectroscopy (EIS) -- a real-time, non-invasive and information-rich measurement that is hitherto underused in battery diagnosis -- with Gaussian process machine learning. We collect over 20,000 EIS spectra of commercial Li-ion batteries at different states of health, states of charge and temperatures -- the largest dataset to our knowledge of its kind. Our Gaussian process model takes the entire spectrum as input, without further feature engineering, and automatically determines which spectral features predict degradation. Our model accurately predicts the remaining useful life, even without complete knowledge of past operating conditions of the battery. Our results demonstrate the value of EIS signals in battery management systems.

Keywords: battery degradation, machine learning method, electrochemical impedance spectroscopy, battery diagnosis

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Authors: Shathya Duobiene, Gediminas Račiukaitis

Abstract:

Solar-powered wireless sensor nodes work best when they operate continuously with minimal energy consumption. Wireless Sensor Networks (WSNs) are a new technology opens up wide studies, and advancements are expanding the prevalence of numerous monitoring applications and real-time aid for environments. The Selective Surface Activation Induced by Laser (SSAIL) technology is an exciting development that gives the design of WSNs more flexibility in terms of their shape, dimensions, and materials. This research work proposes a methodology for using SSAIL technology for forest ecosystem monitoring by wireless sensor networks. WSN monitoring the temperature and humidity were deployed, and their architectures are discussed. The paper presents the experimental outcomes of deploying newly built sensor nodes in forested areas. Finally, a practical method is offered to extend the WSN's lifespan and ensure its continued operation. When operational, the node is independent of the base station's power supply and uses only as much energy as necessary to sense and transmit data.

Keywords: internet of things (IoT), wireless sensor network, sensor nodes, SSAIL technology, forest ecosystem

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Authors: Torsten Hermanns, Thoufik Al Khawli, Wolfgang Schulz

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In laser cutting as well as in long pulsed laser drilling of metals, it can be demonstrated that the ablation shape (the shape of cut faces respectively the hole shape) that is formed approaches a so-called asymptotic shape such that it changes only slightly or not at all with further irradiation. These findings are already known from the ultrashort pulse (USP) ablation of dielectric and semiconducting materials. The explanation for the occurrence of an asymptotic shape in laser cutting and long pulse drilling of metals is identified, its underlying mechanism numerically implemented, tested and clearly confirmed by comparison with experimental data. In detail, there now is a model that allows the simulation of the temporal (pulse-resolved) evolution of the hole shape in laser drilling as well as the final (asymptotic) shape of the cut faces in laser cutting. This simulation especially requires much less in the way of resources, such that it can even run on common desktop PCs or laptops. Individual parameters can be adjusted using sliders – the simulation result appears in an adjacent window and changes in real time. This is made possible by an application-specific reduction of the underlying ablation model. Because this reduction dramatically decreases the complexity of calculation, it produces a result much more quickly. This means that the simulation can be carried out directly at the laser machine. Time-intensive experiments can be reduced and set-up processes can be completed much faster. The high speed of simulation also opens up a range of entirely different options, such as metamodeling. Suitable for complex applications with many parameters, metamodeling involves generating high-dimensional data sets with the parameters and several evaluation criteria for process and product quality. These sets can then be used to create individual process maps that show the dependency of individual parameter pairs. This advanced simulation makes it possible to find global and local extreme values through mathematical manipulation. Such simultaneous optimization of multiple parameters is scarcely possible by experimental means. This means that new methods in manufacturing such as self-optimization can be executed much faster. However, the software’s potential does not stop there; time-intensive calculations exist in many areas of industry. In laser welding or laser additive manufacturing, for example, the simulation of thermal induced residual stresses still uses up considerable computing capacity or is even not possible. Transferring the principle of reduced models promises substantial savings there, too.

Keywords: asymptotic ablation shape, interactive process simulation, laser drilling, laser cutting, metamodeling, reduced modeling

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Authors: Ying Su, Morgan C. Wang

Abstract:

Long-term time series forecasting is an important research area for automated machine learning (AutoML). Currently, forecasting based on either machine learning or statistical learning is usually built by experts, and it requires significant manual effort, from model construction, feature engineering, and hyper-parameter tuning to the construction of the time series model. Automation is not possible since there are too many human interventions. To overcome these limitations, this article proposed to use recurrent neural networks (RNN) through the memory state of RNN to perform long-term time series prediction. We have shown that this proposed approach is better than the traditional Autoregressive Integrated Moving Average (ARIMA). In addition, we also found it is better than other network systems, including Fully Connected Neural Networks (FNN), Convolutional Neural Networks (CNN), and Nonpooling Convolutional Neural Networks (NPCNN).

Keywords: automated machines learning, autoregressive integrated moving average, neural networks, time series analysis

Procedia PDF Downloads 83