Search results for: António Real

Authors: Margarida Plana

Abstract:

The end-users behavior has been identified in the last years as one of the main responsible for the success degree of the energy efficiency improvements. It is essential to create tools to limit their impact on the final consumption. This paper is focused on presenting the results of the analysis developed on the basis of real projects’ data in order to quantify the impact of end-users behavior. The analysis is focused on how the behavior of building’s occupants can vary the achievement of the energy savings targets and how they can be limited. The results obtained show that the management systems are one of the main tools available to control and limit the end-users interaction with the equipment operation. In fact, the results will present the management systems as ‘a must’ on any energy efficiency project.

Keywords: end-users impacts, energy efficiency, energy savings, management systems

Procedia PDF Downloads 247

Authors: Esmat Noroozi, Elahe Sarfi, Farha Hosseinzadeh Lotfi

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Examining the impacts of data modification is considered as sensitivity analysis. A lot of studies have considered the data modification of inputs and outputs in DEA. The issues which has not heretofore been considered in DEA sensitivity analysis is modification in the number of inputs and (or) outputs and determining the impacts of this modification in the status of efficiency of DMUs. This paper is going to present systems that show the impacts of adding one or multiple inputs or outputs on the status of efficiency of DMUs and furthermore a model is presented for recognizing the minimum number of inputs and (or) outputs from among specified inputs and outputs which can be added whereas an inefficient DMU will become efficient. Finally the presented systems and model have been utilized for a set of real data and the results have been reported.

Keywords: data envelopment analysis, efficiency, sensitivity analysis, input, out put

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Authors: Nadjiba Meziou-Chebouti, Amel Merabet, Yahia Chebouti, Nassima Behidj, Salahedine Doumandji

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Among the Anacardiaceae, the fruit (Pistacia vera L.) is the only species that produces edible fruits. The introduction of real pistachio was made in the early sixties by an FAO program in Algeria in several regions in the northern part of Algeria: Tlemcen, Sidi Bel Abbes, Batna, Bouira M'sila. Chemical analyzes of seeds pistachios were made on seeds from an orchard that localizes to Bechloul (Bouira) located in bioclimatic sub-humid temperate winter floor. Analyzes reveal dry matter content of 3.60±0.45%, the water rate is 7.21±0.36%. However, the fat content is 46.00±0.90%, in average blood sugar, it is 4.02±0.47%, the protein reached 29.88±0.76%. Given the very interesting that high-fat food nutritional values, culture pistachio must be considered for its extension in Algeria.

Keywords: pistachio, dry matter, fat, sugar, protein

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Authors: Serafino Di Rosario

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ReS is a sustainable hand-built temporary acoustic shell, developed since 2011 and built during the architectural workshop at Villa Pennisi in Musica in Acireale, Sicily, each year since 2012. The design concept aims to provide a portable structure by reducing the on-site construction problems and the skills required by the builders together with maximizing the acoustic performance for the audience and the musicians. The shell is built using only wood, recycled for the most part, and can be built and dismantled by non-specialized workers in just three days. This paper describes the research process, which spans over four years and presents the final results in form of acoustic simulations performed by acoustic modeling software and real world measurements. ReS is developed by the ReS team who has been presented with the Peter Lord Award in 2015 by the Institute of Acoustics in the UK.

Keywords: acoustic shell, outdoor natural amplification, computational design, room acoustics

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Authors: Americo Pereira, Ricardo Carvalho, Pedro Carvalho, Luis Corte-Real

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Generating 3D content is a task mostly done by hand. It requires specific knowledge not only on how to use the tools for the task but also on the fundamentals of a 3D environment. In this work, we show that automatic generation of content can be achieved, from a scene script, by leveraging existing tools so that non-experts can easily engage in a 3D content generation without requiring vast amounts of time in exploring and learning how to use specific tools. This proposal carries several benefits, including flexible scene synthesis with different levels of detail. Our preliminary results show that the automatically generated content is comparable to the content generated by users with low experience in 3D modeling while vastly reducing the amount of time required for the generation and adds support to implement flexible scenarios for visual scene visualization.

Keywords: 3D virtualization, multimedia, scene script, synthesis

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Authors: Anaelle Gabet, Helene Metivier, Christine De Brauer, Gilles Mailhot, Marcello Brigante

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The presence of micropollutants in surface waters has been widely reported around the world, particularly downstream from wastewater treatment plants (WWTPs). Rural WWTPs constitute more than 90 % of the total WWTPs in France. Like conventional ones, they are not able to fully remove micropollutants. Estrogens are excreted by human beings every day and several studies have highlighted their endocrine disruption properties on river wildlife. They are mainly estrone (E1), 17β-estradiol (E2) and 17α-ethinylestradiol (EE2). Rural WWTPs require cheap and robust tertiary processes. UVC activation of H₂O₂ for HO· generation, a very reactive molecule, has demonstrated its effectiveness. However, UVC rays are dangerous to manipulate and energy-consuming. This is why the ability of UVA rays was investigated in this study. Moreover, the use of S₂O₈²⁻ for SO₄·- generation as an alternative to HO· has emerged in the last few years. Such processes have been widely studied on a lab scale. However, pilot-scale works constitute fewer studies. This study was carried out on a 20-L pilot composed of a 1.12-L UV reactor equipped with a polychromatic UVA lamp or a monochromatic (254 nm) UVC lamp fed in recirculation. Degradation rates of a mixture of spiked E1, E2 and EE2 (5 µM each) were followed by HPLC-UV. Results are expressed in UV dose (mJ.cm-2) received by the compounds of interest to compare UVC and UVA. In every system, estrogen degradation rates followed pseudo-first-order rates. First, experiments were carried out in tap water. All estrogens underwent photolysis under UVC rays, although E1 photolysis is higher. However, only very weak photolysis was observed under UVA rays. Preliminary studies on both oxidants have shown that S₂O₈²⁻ photolysis constants are higher than H₂O₂ under both UVA and UVC rays. Therefore, estrogen degradation rates are about ten times higher in the presence of 1 mM of S₂O₈²⁻ than with one mM of H₂O₂ under both radiations. In the same conditions, the mixture of interest required about 40 times higher UV dose when using UVA rays compared to UVC. However, the UVA/S₂O₈²⁻ system only requires four times more UV dose than the conventional UVC/H₂O₂ system. Further studies were carried out in WWTP effluent with the UVC lamp. When comparing these results to the tap water ones, estrogen degradation rates were more inhibited in the S₂O₈²⁻ system than with H₂O₂. It seems that SO₄·- undergo higher quenching by a real effluent than HO·. Preliminary experiments have shown that natural organic matter is mainly responsible for the radical quenching and that HO and SO₄ both had similar second-order reaction rate constants with dissolved organic matter. However, E1, E2 and EE2 second-order reaction rate constants are about ten times lower with SO₄ than with HO. In conclusion, the UVA/S₂O₈²⁻ system showed encouraging results for the use of UVA rays but further studies in WWTP effluent have to be carried out to confirm this interest. The efficiency of other pollutants in the real matrix also needs to be investigated.

Keywords: AOPs, decontamination, estrogens, radicals, wastewater

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Authors: A. A. AlRasheed, A. Atkins, R. Campion

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This paper focuses on using knowledge management and visualisation concepts to improve the patients and hospitals employee’s workflow. Hospitals workflow is a complex and complicated process and poor patient flow can put both patients and a hospital’s reputation at risk, and can threaten the facility’s financial sustainability. Healthcare leaders are under increased pressure to reduce costs while maintaining or increasing patient care standards. In this paper, a framework is proposed to help improving patient experience, staff satisfaction, and operational efficiency across hospitals by using knowledge management based visualisation concepts. This framework is using real-time visibility to track and monitor location and status of patients, staff, rooms, and medical equipment.

Keywords: knowledge management, improvements, visualisation, workflow

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Authors: Madhu Jain, Rakesh Kumar Meena

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This paper investigates a finite M/G/1 fault tolerant multi-component machining system. The system incorporates the features such as standby support, threshold recovery and imperfect coverage make the study closer to real time systems. The performance prediction of M/G/1 fault tolerant system is carried out using recursive approach by treating remaining service time as a supplementary variable. The numerical results are presented to illustrate the computational tractability of analytical results by taking three different service time distributions viz. exponential, 3-stage Erlang and deterministic. Moreover, the cost function is constructed to determine the optimal choice of system descriptors to upgrading the system.

Keywords: fault tolerant, machine repair, threshold recovery policy, imperfect coverage, supplementary variable technique

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Authors: Priscila Ribeiro dos Santos, Luiz Antonio Daniel

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Inadequate access to clean water and sanitation has become one of the most widespread problems affecting people throughout the developing world, leading to an unceasing need for low-cost and sustainable wastewater treatment systems. The UASB technology has been widely employed as a suitable and economical option for the treatment of sewage in developing countries, which involves low initial investment, low energy requirements, low operation and maintenance costs, high loading capacity, short hydraulic retention times, long solids retention times and low sludge production. Whereas dissolved air flotation process is a good option for the post-treatment of anaerobic effluents, being capable of producing high quality effluents in terms of total suspended solids, chemical oxygen demand, phosphorus, and even pathogens. This work presents an evaluation and monitoring, over a period of 6 months, of one compact full-scale system with this configuration, UASB reactors followed by dissolved air flotation units (DAF), operating in Brazil. It was verified as a successful treatment system, and an issue of relevance since dissolved air flotation process treating UASB reactor effluents is not widely encompassed in the literature. The study covered the removal and behavior of several variables, such as turbidity, total suspend solids (TSS), chemical oxygen demand (COD), Escherichia coli, total coliforms and Clostridium perfringens. The physicochemical variables were analyzed according to the protocols established by the Standard Methods for Examination of Water and Wastewater. For microbiological variables, such as Escherichia coli and total coliforms, it was used the “pour plate” technique with Chromocult Coliform Agar (Merk Cat. No.1.10426) serving as the culture medium, while the microorganism Clostridium perfringens was analyzed through the filtering membrane technique, with the Ágar m-CP (Oxoid Ltda, England) serving as the culture medium. Approximately 74% of total COD was removed in the UASB reactor, and the complementary removal done during the flotation process resulted in 88% of COD removal from the raw sewage, thus the initial concentration of COD of 729 mg.L-1 decreased to 87 mg.L-1. Whereas, in terms of particulate COD, the overall removal efficiency for the whole system was about 94%, decreasing from 375 mg.L-1 in raw sewage to 29 mg.L-1 in final effluent. The UASB reactor removed on average 77% of the TSS from raw sewage. While the dissolved air flotation process did not work as expected, removing only 30% of TSS from the anaerobic effluent. The final effluent presented an average concentration of 38 mg.L-1 of TSS. The turbidity was significantly reduced, leading to an overall efficiency removal of 80% and a final turbidity of 28 NTU.The treated effluent still presented a high concentration of fecal pollution indicators (E. coli, total coliforms, and Clostridium perfringens), showing that the system did not present a good performance in removing pathogens. Clostridium perfringens was the organism which suffered the higher removal by the treatment system. The results can be considered satisfactory for the physicochemical variables, taking into account the simplicity of the system, besides that, it is necessary a post-treatment to improve the microbiological quality of the final effluent.

Keywords: dissolved air flotation, municipal sewage, UASB reactor, treatment

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Authors: Asmae Tafraouti, Yasmina Layouni

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The fabrication of cylindrical Tungsten micro-tools with a high aspect ratio is a real challenge because of several constraints that come into during their manufacture. In this paper, we will describe the process used to fabricate these micro-tools. It consists of using electrochemical etching. We will also present the optimal protocol that makes it possible to fabricate micro-tools with a high aspect ratio in a reproducible way. Next, we will show the limit of the experimental parameters chosen to manufacture micro-tools from a wire with an initial diameter of Φ_0=250µm. The protocol used allows obtaining an average diameter of Φ=88µm ±1 µm over a length of L=3.5mm.

Keywords: drop-off effect, electrochemical etching, micro-electrical discharge machining, tungsten micro-tools

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Authors: Ömer Aktaş, Olga A. Suvorova, Oleg Tretyakov

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The boundary value problem on non-canonical and arbitrary shaped contour is solved with a numerically effective method called Analytical Regularization Method (ARM) to calculate propagation parameters. As a result of regularization, the equation of first kind is reduced to the infinite system of the linear algebraic equations of the second kind in the space of L2. This equation can be solved numerically for desired accuracy by using truncation method. The parameters as cut-off wavenumber and cut-off frequency are used in waveguide evolutionary equations of electromagnetic theory in time-domain to illustrate the real-valued TM fields with lossy and lossless media.

Keywords: analytical regularization method, electromagnetic theory evolutionary equations of time-domain, TM Field

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Authors: Youssef Chahir, Messaoud Mostefai, Salah Khodja

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This paper presents the development of a 2D visual marker, derived from a recent patented work in the field of numbering systems. The proposed fiducial uses a group of projective invariant straight-line patterns, easily detectable and remotely recognizable. Based on an efficient data coding scheme, the developed marker enables producing a large panel of unique real time identifiers with highly distinguishable patterns. The proposed marker Incorporates simultaneously decimal and binary information, making it readable by both humans and machines. This important feature opens up new opportunities for the development of efficient visual human-machine communication and monitoring protocols. Extensive experiment tests validate the robustness of the marker against acquisition and geometric distortions.

Keywords: visual markers, projective invariants, distance map, level sets

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Authors: Masaki Sakai, Tsuyoshi Nakajima, Kazuya Takahashi

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In order to improve the productivity of a factory, it is often the case to create an inference model by collecting and analyzing operational data off-line and then to develop an edge application (EAP) that evaluates the quality of the products or diagnoses machine faults in real-time. To accelerate this development cycle, an edge application framework for the smart factory is proposed, which enables to create and modify EAPs based on prepared inference models. In the framework, the preprocessing component is the key part to make it work. This paper proposes a language for preprocessing of edge applications, called LaPEA, which can flexibly process several sensor data from machines into explanatory variables for an inference model, and proves that it meets the requirements for the preprocessing.

Keywords: edge application framework, edgecross, preprocessing language, smart factory

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Authors: Zheng Wang, Zhenhong Li, Jon Mills

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Ground-based synthetic aperture radar (GBSAR) represents a powerful remote sensing tool for deformation monitoring towards various geohazards, e.g. landslides, mudflows, avalanches, infrastructure failures, and the subsidence of residential areas. Unlike spaceborne SAR with a fixed revisit period, GBSAR data can be acquired with an adjustable temporal resolution through either continuous or discontinuous operation. However, challenges arise from processing high temporal-resolution continuous GBSAR data, including the extreme cost of computational random-access-memory (RAM), the delay of displacement maps, and the loss of temporal evolution. Moreover, repositioning errors between discontinuous campaigns impede the accurate measurement of surface displacements. Therefore, a versatile package with two complete chains is developed in this study in order to process both continuous and discontinuous GBSAR data and address the aforementioned issues. The first chain is based on a small-baseline subset concept and it processes continuous GBSAR images unit by unit. Images within a window form a basic unit. By taking this strategy, the RAM requirement is reduced to only one unit of images and the chain can theoretically process an infinite number of images. The evolution of surface displacements can be detected as it keeps temporarily-coherent pixels which are present only in some certain units but not in the whole observation period. The chain supports real-time processing of the continuous data and the delay of creating displacement maps can be shortened without waiting for the entire dataset. The other chain aims to measure deformation between discontinuous campaigns. Temporal averaging is carried out on a stack of images in a single campaign in order to improve the signal-to-noise ratio of discontinuous data and minimise the loss of coherence. The temporal-averaged images are then processed by a particular interferometry procedure integrated with advanced interferometric SAR algorithms such as robust coherence estimation, non-local filtering, and selection of partially-coherent pixels. Experiments are conducted using both synthetic and real-world GBSAR data. Displacement time series at the level of a few sub-millimetres are achieved in several applications (e.g. a coastal cliff, a sand dune, a bridge, and a residential area), indicating the feasibility of the developed GBSAR data processing package for deformation monitoring of a wide range of scientific and practical applications.

Keywords: ground-based synthetic aperture radar, interferometry, small baseline subset algorithm, deformation monitoring

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Authors: Purnima Dhall, Rita Kumar

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Introduction: River Yamuna, in the national capital territory (NCT), and also the primary source of drinking water for the city. Delhi discharges about 3,684 MLD of sewage through its 18 drains in to the Yamuna. Water quality monitoring is an important aspect of water management concerning to the pollution control. Public concern and legislation are now a day’s demanding better environmental control. Conventional method for estimating BOD5 has various drawbacks as they are expensive, time-consuming, and require the use of highly trained personnel. Stringent forthcoming regulations on the wastewater have necessitated the urge to develop analytical system, which contribute to greater process efficiency. Biosensors offer the possibility of real time analysis. Methodology: In the present study, a novel rapid method for the determination of biochemical oxygen demand (BOD) has been developed. Using the developed method, the BOD of a sample can be determined within 2 hours as compared to 3-5 days with the standard BOD3-5day assay. Moreover, the test is based on specified consortia instead of undefined seeding material therefore it minimizes the variability among the results. The device is coupled to software which automatically calculates the dilution required, so, the prior dilution of the sample is not required before BOD estimation. The developed BOD-Biosensor makes use of immobilized microorganisms to sense the biochemical oxygen demand of industrial wastewaters having low–moderate–high biodegradability. The method is quick, robust, online and less time consuming. Findings: The results of extensive testing of the developed biosensor on drains demonstrate that the BOD values obtained by the device correlated with conventional BOD values the observed R2 value was 0.995. The reproducibility of the measurements with the BOD biosensor was within a percentage deviation of ±10%. Advantages of developed BOD biosensor • Determines the water pollution quickly in 2 hours of time; • Determines the water pollution of all types of waste water; • Has prolonged shelf life of more than 400 days; • Enhanced repeatability and reproducibility values; • Elimination of COD estimation. Distinctiveness of Technology: • Bio-component: can determine BOD load of all types of waste water; • Immobilization: increased shelf life > 400 days, extended stability and viability; • Software: Reduces manual errors, reduction in estimation time. Conclusion: BiosensorBOD can be used to measure the BOD value of the real wastewater samples. The BOD biosensor showed good reproducibility in the results. This technology is useful in deciding treatment strategies well ahead and so facilitating discharge of properly treated water to common water bodies. The developed technology has been transferred to M/s Forbes Marshall Pvt Ltd, Pune.

Keywords: biosensor, biochemical oxygen demand, immobilized, monitoring, Yamuna

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Authors: Haitham S. Hamza, Mohamed Maher, Shourok Alaa, Aya Khattab, Hadeal Ismail, Kamilia Hosny

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Radio Frequency Identification (RFID) has become a key technology in the margining concept of Internet of Things (IoT). Naturally, business applications would require the deployment of various RFID systems that are developed by different vendors and use various data formats. This heterogeneity poses a real challenge in developing large-scale IoT systems with RFID as integration is becoming very complex and challenging. Semantic integration is a key approach to deal with this challenge. To do so, ontology for RFID systems need to be developed in order to annotated semantically RFID systems, and hence, facilitate their integration. Accordingly, in this paper, we propose ontology for RFID systems. The proposed ontology can be used to semantically enrich RFID systems, and hence, improve their usage and reasoning. The usage of the proposed ontology is explained through a simple scenario in the health care domain.

Keywords: RFID, semantic technology, ontology, sparql query language, heterogeneity

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Authors: Rim Messaoudi, Nogaye-Gueye Gning, François Azelart

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Automatic text classification applies mostly natural language processing (NLP) and other AI-guided techniques to automatically classify text in a faster and more accurate manner. This paper discusses the subject of using predictive maintenance to manage incident tickets inside the sociality. It focuses on proposing a tool that treats and analyses comments and notes written by administrators after resolving an incident ticket. The goal here is to increase the quality of these comments. Additionally, this tool is based on NLP and machine learning techniques to realize the textual analytics of the extracted data. This approach was tested using real data taken from the French National Railways (SNCF) company and was given a high-quality result.

Keywords: machine learning, text classification, NLP techniques, semantic representation

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Authors: Umang Varshney, Amit Karamchandani, Rohit Kapoor

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Practitioners and researchers have realized that Blockchain is not limited to currency. Blockchain as a distributed ledger can ensure a transparent and traceable supply chain. Due to Blockchain-enabled IoTs, a firm’s information management system can now take inputs from other supply chain partners in real-time. This study aims to provide empirical evidence of dimensions responsible for blockchain implemented firm’s growth and highlight how sector (manufacturing or service), state's regulatory environment, and choice of blockchain network affect the blockchain's usefulness. This post-adoption study seeks to validate the findings of pre-adoption studies done on the blockchain. Data will be collected through a survey of managers working in blockchain implemented firms and analyzed through PLS-SEM.

Keywords: blockchain, information management system, PLS-SEM, firm's growth

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Authors: Adilah Abdul Ghapor, Yong Zulina Zubairi, Rahmatullah Imon

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Missing value problem is common in statistics and has been of interest for years. This article considers two modern techniques in handling missing data for linear functional relationship model (LFRM) namely the Expectation-Maximization (EM) algorithm and Expectation-Maximization with Bootstrapping (EMB) algorithm using three performance indicators; namely the mean absolute error (MAE), root mean square error (RMSE) and estimated biased (EB). In this study, we applied the methods of imputing missing values in the LFRM. Results of the simulation study suggest that EMB algorithm performs much better than EM algorithm in both models. We also illustrate the applicability of the approach in a real data set.

Keywords: expectation-maximization, expectation-maximization with bootstrapping, linear functional relationship model, performance indicators

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Authors: M. V. Manoj Kumar, Likewin Thomas, Annappa

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Process mining research discipline bridges the gap between data mining and business process modeling and analysis, it offers the process-centric and end-to-end methods/techniques for analyzing information of real-world process detailed in operational event-logs. In this paper, we have proposed a notation called trace logo for graphically representing control-flow perspective (order of execution of activities) of process. A trace logo consists of a stack of activity names at each position, sizes of the activity name indicates their frequency in the traces and the total height of the activity depicts the information content of the position. A trace logo created from a set of aligned traces generated using Multiple Trace Alignment technique.

Keywords: consensus trace, process mining, multiple trace alignment, trace logo

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Authors: Chinedu Peter, Dashrath Singh

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Membrane computing is a computability model which abstracts its structures and functions from the biological cell. The main ingredient of membrane computing is the notion of a membrane structure, which consists of several cell-like membranes recurrently placed inside a unique skin membrane. The emergence of several variants of membrane computing gives rise to the notion of a P system. The paper presents a variant of P systems for arithmetic operations on non-negative integers based on the weak priorities for rule application. Consequently, we obtain deterministic P systems. Two membranes suffice. There are at most four objects for multiplication and five objects for division throughout the computation processes. The model is simple and has a potential for possible extension to non-negative integers and real numbers in general.

Keywords: P system, binary operation, determinism, weak rule priority

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Authors: Andreas Aceranti, Simonetta Vernocchi, Marco Colorato, Kaoutar Filahi

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This study was inspired by the necessity of giving forensic linguistics and phonetics more and more importance and the intention to explore those topics in an attempt to understand what the role of these disciplines really is in investigations of any nature. The goal is to analyze what are the achievements that those subjects have been able to reach, and what contribution they gave to the legal world; the analysis and study of those topics are supported by the recounting of real cases that have included forensic and phonetic linguistics. One of the most relevant cases is that of the Unabomber, an investigation that brought to light the importance and highlighted the importance this matter can have in difficult and time-consuming cases such as the one we have here. We also focus on the areas of expertise of those new branches of applied linguistics, focusing on what is the use of this new discipline in Italy and abroad and showing what could be the possible improvements that the Italian state could apply in order to be able to catch up with countries like Great Britain.

Keywords: forensic linguistic, forensic phonetics, investigation, criminalistics

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Authors: Ahmad Almajid

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The idea of unifying quantum mechanics with general relativity is still a dream for many researchers, as physics has only two paths, no more. Einstein's path, which is mainly based on particle mechanics, and the path of Paul Dirac and others, which is based on wave mechanics, the incompatibility of the two approaches is due to the radical difference in the initial assumptions and the mathematical nature of each approach. Logical thinking in modern physics leads us to two problems: - In quantum mechanics, despite its success, the problem of measurement and the problem of wave function interpretation is still obscure. - In special relativity, despite the success of the equivalence of rest-mass and energy, but at the speed of light, the fact that the energy becomes infinite is contrary to logic because the speed of light is not infinite, and the mass of the particle is not infinite too. These contradictions arise from the overlap of relativistic and quantum mechanics in the neighborhood of the speed of light, and in order to solve these problems, one must understand well how to move from relativistic mechanics to quantum mechanics, or rather, to unify them in a way different from Dirac's method, in order to go along with God or Nature, since, as Einstein said, "God doesn't play dice." From De Broglie's hypothesis about wave-particle duality, Léon Brillouin's definition of the new proper time was deduced, and thus the quantum Lorentz factor was obtained. Finally, using the Euler-Lagrange equation, we come up with new equations in quantum mechanics. In this paper, the two problems in modern physics mentioned above are solved; it can be said that this new approach to quantum mechanics will enable us to unify it with general relativity quite simply. If the experiments prove the validity of the results of this research, we will be able in the future to transport the matter at speed close to the speed of light. Finally, this research yielded three important results: 1- Lorentz quantum factor. 2- Planck energy is a limited case of Einstein energy. 3- Real quantum mechanics, in which new equations for quantum mechanics match and exceed Dirac's equations, these equations have been reached in a completely different way from Dirac's method. These equations show that quantum mechanics is a limited case of relativistic mechanics. At the Solvay Conference in 1927, the debate about quantum mechanics between Bohr, Einstein, and others reached its climax, while Bohr suggested that if particles are not observed, they are in a probabilistic state, then Einstein said his famous claim ("God does not play dice"). Thus, Einstein was right, especially when he didn't accept the principle of indeterminacy in quantum theory, although experiments support quantum mechanics. However, the results of our research indicate that God really does not play dice; when the electron disappears, it turns into amicable particles or an elastic medium, according to the above obvious equations. Likewise, Bohr was right also, when he indicated that there must be a science like quantum mechanics to monitor and study the motion of subatomic particles, but the picture in front of him was blurry and not clear, so he resorted to the probabilistic interpretation.

Keywords: lorentz quantum factor, new, planck’s energy as a limiting case of einstein’s energy, real quantum mechanics, new equations for quantum mechanics

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Authors: Margarida Plana

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One of the most important energy challenge of the European policies is the transition to a Net Zero Energy Building (NZEB) model. A NZEB is a new concept of building that has the aim of reducing both the energy consumption and the carbon emissions to nearly zero of the course of a year. To achieve this nearly zero consumption, apart from being buildings with high efficiency levels, the energy consumed by the building has to be produced on-site. This paper is focused on presenting the results of the analysis developed on basis of real projects’ data in order to quantify the impact of end-users behavior. The analysis is focused on how the behavior of building’s occupants can vary the achievement of the energy savings targets and how they can be limited. The results obtained show that on this kind of project, with very high energy performance, is required to limit the end-users interaction with the system operation to be able to reach the targets fixed.

Keywords: end-users impacts, energy efficiency, energy savings, NZEB model

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Authors: Abebayehu Yohannes, Hsiu-Ling Chen, Chiu-Chen Chang

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Mathematics reading and spatial ability are important learning components in mathematics education. However, many students struggle to understand real-world problems and lack the spatial ability to form internal imagery. To cope with this problem, in this study, an interactive e-book was developed. The result indicated that both groups had a significant increase in the mathematics reading ability test, and a significant difference was observed in the overall mathematics reading score in favor of the experimental group. In addition, the interactive e-book learning mode had significant impacts on students’ spatial ability. It was also found that the richness of content with visual and interactive elements provided in the interactive e-book enhanced students’ satisfaction with the teaching material.

Keywords: interactive e-books, spatial ability, mathematics reading, satisfaction, three view

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Authors: Yong-Kyu Jung

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The fast growth in information technology has led to de-mands to access/process data. CPSs heavily depend on the time of hardware/software operations and communication over the network (i.e., real-time/parallel operations in CPSs (e.g., autonomous vehicles). Since data processing is an im-portant means to overcome the issue confronting data management, reducing the gap between the technological-growth and the data-complexity and channel-bandwidth. An adaptive perpetual data approximation method is intro-duced to manage the actual entropy of the digital spectrum. An ADAC implemented as an accelerator and/or apps for servers/smart-connected devices adaptively rescales digital contents (avg.62.8%), data processing/access time/energy, encryption/decryption overheads in AI/ML applications (facial ID/recognition).

Keywords: adaptive codec, AI, ML, HPC, cyber-physical, cybersecurity

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Authors: Skyler Kim

Abstract:

An early diagnosis of leukemia has always been a challenge to doctors and hematologists. On a worldwide basis, it was reported that there were approximately 350,000 new cases in 2012, and diagnosing leukemia was time-consuming and inefficient because of an endemic shortage of flow cytometry equipment in current clinical practice. As the number of medical diagnosis tools increased and a large volume of high-quality data was produced, there was an urgent need for more advanced data analysis methods. One of these methods was the AI approach. This approach has become a major trend in recent years, and several research groups have been working on developing these diagnostic models. However, designing and implementing a leukemia diagnostic system in real clinical environments based on a deep learning approach with larger sets remains complex. Leukemia is a major hematological malignancy that results in mortality and morbidity throughout different ages. We decided to select acute lymphocytic leukemia to develop our diagnostic system since acute lymphocytic leukemia is the most common type of leukemia, accounting for 74% of all children diagnosed with leukemia. The results from this development work can be applied to all other types of leukemia. To develop our model, the Kaggle dataset was used, which consists of 15135 total images, 8491 of these are images of abnormal cells, and 5398 images are normal. In this paper, we design and implement a leukemia diagnostic system in a real clinical environment based on deep learning approaches with larger sets. The proposed diagnostic system has the function of detecting and classifying leukemia. Different from other AI approaches, we explore hybrid architectures to improve the current performance. First, we developed two independent convolutional neural network models: VGG19 and ResNet50. Then, using both VGG19 and ResNet50, we developed a hybrid deep learning architecture employing transfer learning techniques to extract features from each input image. In our approach, fusing the features from specific abstraction layers can be deemed as auxiliary features and lead to further improvement of the classification accuracy. In this approach, features extracted from the lower levels are combined into higher dimension feature maps to help improve the discriminative capability of intermediate features and also overcome the problem of network gradient vanishing or exploding. By comparing VGG19 and ResNet50 and the proposed hybrid model, we concluded that the hybrid model had a significant advantage in accuracy. The detailed results of each model’s performance and their pros and cons will be presented in the conference.

Keywords: acute lymphoblastic leukemia, hybrid model, leukemia diagnostic system, machine learning

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Authors: P. Azimi, B. Behtoiy, A. A. Najafi, H. R. Charmchi

Abstract:

According to the previous studies, one of the most famous techniques which affect the efficiency of a production line is the assembly line balancing (ALB) technique. This paper examines the balancing effect of a whole production line of a real auto glass manufacturer in three steps. In the first step, processing time of each activity in the workstations is generated according to a practical approach. In the second step, the whole production process is simulated and the bottleneck stations have been identified, and finally in the third step, several improvement scenarios are generated to optimize the system throughput, and the best one is proposed. The main contribution of the current research is the proposed framework which combines two famous approaches including Assembly Line Balancing and Optimization via Simulation technique (OvS). The results show that the proposed framework could be applied in practical environments, easily.

Keywords: assembly line balancing problem, optimization via simulation, production planning

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Authors: Yu-Hsiu Lin, Wen-Chun Lin, Yen-Chang Cheng, Chia-Ju Yeh, Yu-Chuan Chen, Tai-You Li

Abstract:

Demand-Side Management (DSM) has the potential to reduce electricity costs and carbon emission, which are associated with electricity used in the modern society. A home Energy Management System (EMS) commonly used by residential consumers in a down-stream sector of a smart grid to monitor, control, and optimize energy efficiency to domestic appliances is a system of computer-aided functionalities as an energy audit for residential DSM. Implementing fault detection and classification to domestic appliances monitored, controlled, and optimized is one of the most important steps to realize preventive maintenance, such as residential air conditioning and heating preventative maintenance in residential/industrial DSM. In this study, a cloud intelligence-based green EMS that comes up with an Internet of Things (IoT) technology stack for residential DSM is developed. In the EMS, Arduino MEGA Ethernet communication-based smart sockets that module a Real Time Clock chip to keep track of current time as timestamps via Network Time Protocol are designed and implemented for readings of load phenomena reflecting on voltage and current signals sensed. Also, a Network-Attached Storage providing data access to a heterogeneous group of IoT clients via Hypertext Transfer Protocol (HTTP) methods is configured to data stores of parsed sensor readings. Lastly, a desktop computer with a WAMP software bundle (the Microsoft® Windows operating system, Apache HTTP Server, MySQL relational database management system, and PHP programming language) serves as a data science analytics engine for dynamic Web APP/REpresentational State Transfer-ful web service of the residential DSM having globally-Advanced Internet of Artificial Intelligence (AI)/Computational Intelligence. Where, an abstract computing machine, Java Virtual Machine, enables the desktop computer to run Java programs, and a mash-up of Java, R language, and Python is well-suited and -configured for AI in this study. Having the ability of sending real-time push notifications to IoT clients, the desktop computer implements Google-maintained Firebase Cloud Messaging to engage IoT clients across Android/iOS devices and provide mobile notification service to residential/industrial DSM. In this study, in order to realize edge intelligence that edge devices avoiding network latency and much-needed connectivity of Internet connections for Internet of Services can support secure access to data stores and provide immediate analytical and real-time actionable insights at the edge of the network, we upgrade the designed and implemented smart sockets to be embedded AI Arduino ones (called embedded AIduino). With the realization of edge analytics by the proposed embedded AIduino for data analytics, an Arduino Ethernet shield WizNet W5100 having a micro SD card connector is conducted and used. The SD library is included for reading parsed data from and writing parsed data to an SD card. And, an Artificial Neural Network library, ArduinoANN, for Arduino MEGA is imported and used for locally-embedded AI implementation. The embedded AIduino in this study can be developed for further applications in manufacturing industry energy management and sustainable energy management, wherein in sustainable energy management rotating machinery diagnostics works to identify energy loss from gross misalignment and unbalance of rotating machines in power plants as an example.

Keywords: demand-side management, edge intelligence, energy management system, fault detection and classification

Procedia PDF Downloads 239

Authors: Claire Tranter, Coral Dando

Abstract:

Gathering information from others is a fundamental goal for those concerned with investigating crime, and protecting national and international security. Persuading an individual to move from an opposing to converging viewpoint, and an understanding on the cognitive style behind this change can serve to increase understanding of traditional face-to-face interactions, as well as synthetic environments (SEs) often used for communication across varying geographical locations. SEs are growing in usage, and with this increase comes an increase in crime being undertaken online. Communication technologies can allow people to mask their real identities, supporting anonymous communication which can raise significant challenges for investigators when monitoring and managing these conversations inside SEs. To date, the psychological literature concerning how to maximise information-gain in SEs for real-world interviewing purposes is sparse, and as such this aspect of social cognition is not well understood. Here, we introduce an overview of a novel programme of PhD research which seeks to enhance understanding of cross-cultural and cross-gender communication in SEs for maximising information gain. Utilising a dyadic jury paradigm, participants interacted with a confederate who attempted to persuade them to the opposing verdict across three distinct environments: face-to-face, instant messaging, and a novel virtual reality environment utilising avatars. Participants discussed a criminal scenario, acting as a two-person (male; female) jury. Persuasion was manipulated by the confederate claiming an opposing viewpoint (guilty v. not guilty) to the naïve participants from the outset. Pre and post discussion data, and observational digital recordings (voice and video) of participant’ discussion performance was collected. Information regarding cognitive style was also collected to ascertain participants need for cognitive closure and biases towards jumping to conclusions. Findings revealed that individuals communicating via an avatar in a virtual reality environment reacted in a similar way, and thus equally persuasive, when compared to individuals communicating face-to-face. Anonymous instant messaging however created a resistance to persuasion in participants, with males showing a significant decline in persuasive outcomes compared to face to face. The findings reveal new insights particularly regarding the interplay of persuasion on gender and modality, with anonymous instant messaging enhancing resistance to persuasion attempts. This study illuminates how varying SE can support new theoretical and applied understandings of how judgments are formed and modified in response to advocacy.

Keywords: applied cognition, persuasion, social media, virtual reality

Procedia PDF Downloads 134