Search results for: evolution algorithm

Authors: Bokkasam Sasidhar, Ibrahim Aljasser

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The problem of finding optimal schedules for each equipment in a production process is considered, which consists of a single stage of manufacturing and which can handle different types of products, where changeover for handling one type of product to the other type incurs certain costs. The machine capacity is determined by the upper limit for the quantity that can be processed for each of the products in a set up. The changeover costs increase with the number of set ups and hence to minimize the costs associated with the product changeover, the planning should be such that similar types of products should be processed successively so that the total number of changeovers and in turn the associated set up costs are minimized. The problem of cost minimization is equivalent to the problem of minimizing the number of set ups or equivalently maximizing the capacity utilization in between every set up or maximizing the total capacity utilization. Further, the production is usually planned against customers’ orders, and generally different customers’ orders are assigned one of the two priorities – “normal” or “priority” order. The problem of production planning in such a situation can be formulated into a Multiple Arc Network (MAN) model and can be solved sequentially using the algorithm for maximizing flow along a MAN and the algorithm for maximizing flow along a MAN with priority arcs. The model aims to provide optimal production schedule with an objective of maximizing capacity utilization, so that the customer-wise delivery schedules are fulfilled, keeping in view the customer priorities. Algorithms have been presented for solving the MAN formulation of the production planning with customer priorities. The application of the model is demonstrated through numerical examples.

Keywords: scheduling, maximal flow problem, multiple arc network model, optimization

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Authors: Salam Saudagar, Ankit Kamboj, Niraj Mohan, Satgounda Patil, Nilesh Powar

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Task Assignment and Scheduling is a challenging Operations Research problem when there is a limited number of resources and comparatively higher number of tasks. The Cost Management team at Cummins needs to assign tasks based on a deadline and must prioritize some of the tasks as per business requirements. Moreover, there is a constraint on the resources that assignment of tasks should be done based on an individual skill level, that may vary for different tasks. Another constraint is for scheduling the tasks that should be evenly distributed in terms of number of working hours, which adds further complexity to this problem. The proposed greedy approach to solve assignment and scheduling problem first assigns the task based on management priority and then by the closest deadline. This is followed by an iterative selection of an available resource with the least allocated total working hours for a task, i.e. finding the local optimal choice for each task with the goal of determining the global optimum. The greedy approach task allocation is compared with a variant of Hungarian Algorithm, and it is observed that the proposed approach gives an equal allocation of working hours among the resources. The comparative study of the proposed approach is also done with manual task allocation and it is noted that the visibility of the task timeline has increased from 2 months to 6 months. An interactive dashboard app is created for the greedy assignment and scheduling approach and the tasks with more than 2 months horizon that were waiting in a queue without a delivery date initially are now analyzed effectively by the business with expected timelines for completion.

Keywords: assignment, deadline, greedy approach, Hungarian algorithm, operations research, scheduling

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Authors: A. K. Borah, A. K. Singh

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In this paper we deal building blocks of the computer simulation of the multiphase flows. Whole simulation procedure can be viewed as two super procedures; The implementation of VOF method and the solution of Navier Stoke’s Equation. Moreover, a sequential code for a Navier Stoke’s solver has been studied.

Keywords: Bi-conjugate gradient stabilized (Bi-CGSTAB), ILUT function, krylov subspace, multifluid flows preconditioner, simple algorithm

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Authors: Imen Amari, Kaouther Gasmi, Asma Rebaya, Salem Hasnaoui

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The problem of scheduling and mapping data flow applications on multi-core architectures is notoriously difficult. This difficulty is related to the rapid evaluation of Telecommunication and multimedia systems accompanied by a rapid increase of user requirements in terms of latency, execution time, consumption, energy, etc. Having an optimal scheduling on multi-cores DSP (Digital signal Processors) platforms is a challenging task. In this context, we present a novel technic and algorithm in order to find a valid schedule that optimizes the key performance metrics particularly the Latency. Our contribution is based on Satisfiability Modulo Theories (SMT) solving technologies which is strongly driven by the industrial applications and needs. This paper, describe a scheduling module integrated in our proposed Workflow which is advised to be a successful approach for programming the applications based on NoC-DSP platforms. This workflow transform automatically a Simulink model to a synchronous dataflow (SDF) model. The automatic transformation followed by SMT solver scheduling aim to minimize the final latency and other software/hardware metrics in terms of an optimal schedule. Also, finding the optimal numbers of cores to be used. In fact, our proposed workflow taking as entry point a Simulink file (.mdl or .slx) derived from embedded Matlab functions. We use an approach which is based on the synchronous and hierarchical behavior of both Simulink and SDF. Whence, results of running the scheduler which exist in the Workflow mentioned above using our proposed SMT solver algorithm refinements produce the best possible scheduling in terms of latency and numbers of cores.

Keywords: multi-cores DSP, scheduling, SMT solver, workflow

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Authors: Shafait Hussain Ali

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Since its outbreak in China, the Covid_19 19 disease has been caused by the corona virus SARS N coyote 2. Italy was the first Western country to be severely affected, and the first country to take drastic measures to control the disease. In start of December 2019, the sudden outbreaks of the Coronary Virus Disease was caused by a new Corona 2 virus (SARS-CO2) of acute respiratory syndrome in china city Wuhan. The World Health Organization declared the epidemic a public health emergency of international concern on January 30, 2020,. On February 14, 2020, 49,053 laboratory-confirmed deaths and 1481 deaths have been reported worldwide. The threat of the disease has forced most of the governments to implement various control measures. Therefore it becomes necessary to analyze the Italian data very carefully, in particular to investigates and to find out the present condition and the number of infected persons in the form of positive cases, death, hospitalized or some other features of infected persons will clear in simple form. So used such a model that will clearly shows the real facts and figures and also understandable to every readable person which can get some real benefit after reading it. The model used must includes(total positive cases, current positive cases, hospitalized patients, death, recovered peoples frequency rates ) all features that explains and clear the wide range facts in very simple form and helpful to administration of that country.

Keywords: machine learning tools and techniques, rapid miner tool, Naive-Bayes algorithm, predictions

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Authors: Mubashir Hussain, Mu Lv, Xiaohan Dong, Zhiyang Li, Bin Liu, Nongyue He

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Detection and classification of microbes have a vast range of applications in biomedical engineering especially in detection, characterization, and quantification of bacterial contaminants. For identification of pathogens, different techniques are emerging in the field of biomedical engineering. Latest technology uses light scattering, capable of identifying different pathogens without any need for biochemical processing. Bacterial Pathogens Identification System (BPIS) which uses a laser beam, passes through the sample and light scatters off. An assembly of photodetectors surrounded by the sample at different angles to detect the scattering of light. The algorithm of the system consists of two parts: (a) Library files, and (b) Comparator. Library files contain data of known species of bacterial microbes in the form of binned plots, while comparator compares data of unknown sample with library files. Using collected data of unknown bacterial species, highest voltage values stored in the form of peaks and arranged in 3D histograms to find the frequency of occurrence. Resulting data compared with library files of known bacterial species. If sample data matching with any library file of known bacterial species, sample identified as a matched microbe. An experiment performed to identify three different bacteria particles: Enterococcus faecalis, Pseudomonas aeruginosa, and Escherichia coli. By applying algorithm using library files of given samples, results were compromising. This system is potentially applicable to several biomedical areas, especially those related to cell morphology.

Keywords: microbial identification, laser scattering, peak identification, binned plots classification

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Authors: Anandhi Santhosh

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In order to describe various real-world problems in physical and engineering sciences subject to abrupt changes at certain instants during the evolution process, impulsive differential equations has been used to describe the system model. In this article, the problem of approximate controllability for nonlinear impulsive integrodifferential equations with state-dependent delay is investigated. We study the approximate controllability for nonlinear impulsive integrodifferential system under the assumption that the corresponding linear control system is approximately controllable. Using methods of functional analysis and semigroup theory, sufficient conditions are formulated and proved. Finally, an example is provided to illustrate the proposed theory.

Keywords: approximate controllability, impulsive differential system, fixed point theorem, state-dependent delay

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Authors: Adam Kurnicki, Bartłomiej Stanczyk, Bartosz Kania

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This paper presents development of the light-weight manipulator with series elastic actuation for medical telediagnostics (USG examination). General structure of realized impedance control algorithm was shown. It was described how to perform force measurements based mainly on elasticity of manipulator links.

Keywords: telediagnostics, elastic manipulator, impedance control, force measurement

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Authors: Gary Miller, Andriy Didenko, David Allison

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The boundary of a region in the plane shrinks according to its curvature. A simple algorithm based upon this motion by curvature performed by a spreadsheet simulates the evaporation/dissipation behavior of oil spill boundaries.

Keywords: mathematical modeling, oil, evaporation, dissipation, boundary

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Authors: Rino Gubiani, Gianfranco Pergher

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The work focused on the statistical analysis of accidents in the forestry sector (2000-2020) in Friuli-Venezia Giulia region, located in the North-East of Italy. The aim of the work was to analyse the evolution of the casualties throughout time and to evaluate possible improvements in the sector. It was shown that even nowadays the rate of accidents in forestry work is higher compared with all the other sectors, including agriculture; moreover, it was highlighted that some accidents remained present throughout the whole analysed range, such as slipping on the soil, being hit by trees and falling down from the plants. The results showed that an increase in forestry exploitation could even increase the total number of accidents, if advanced technological machines, such as cable cranes, would not implemented, given the fact that there is also a significant number of old people (above 50 years old) working in the sector.

Keywords: safety, forestry work, accidents, risk analysis, casualties, statistical analysis

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Authors: Ehsan Soleymaninejadian

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As the field of immunology is growing day by day, and its chaotic system amazes more people, greed of research in this area is growing; however dealing with human or mammalian cells such as mice make the research expensive. Although there are some differences between higher animals with insects, importance of innate immunity during evolution made it untouched. So, for understanding the innate immunity insects can be good models. They are cheap; reproduction is fast and in the case genetics, less complicated. In this review, we tried to briefly tackle with important factors in insects’ innate immunity such as melanization, encapsulation, JAK-STAT, IMD, and Toll pathways. At the end, we explained how hormones and nerve system also can impact on immune system and make it more beautiful. In concluding remarks, the possibility of taking help from insect immune system to fight against diseases such as cancer has been considered.

Keywords: insects, innate immunity, melanization, intracellular pathways, hormones

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Authors: S. Jalaja, A. M. Vijaya Prakash

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Recursive combination of an algorithm based on Karatsuba multiplication is exploited to design a generalized transpose and parallel Finite Impulse Response (FIR) Filter. Mid-range Karatsuba multiplication and Carry Save adder based on Karatsuba multiplication reduce time complexity for higher order multiplication implemented up to n-bit. As a result, we design modified N-tap Transpose and Parallel Symmetric FIR Filter Structure using Karatsuba algorithm. The mathematical formulation of the FFA Filter is derived. The proposed architecture involves significantly less area delay product (APD) then the existing block implementation. By adopting retiming technique, hardware cost is reduced further. The filter architecture is designed by using 90 nm technology library and is implemented by using cadence EDA Tool. The synthesized result shows better performance for different word length and block size. The design achieves switching activity reduction and low power consumption by applying with and without retiming for different combination of the circuit. The proposed structure achieves more than a half of the power reduction by adopting with and without retiming techniques compared to the earlier design structure. As a proof of the concept for block size 16 and filter length 64 for CKA method, it achieves a 51% as well as 70% less power by applying retiming technique, and for CSA method it achieves a 57% as well as 77% less power by applying retiming technique compared to the previously proposed design.

Keywords: carry save adder Karatsuba multiplication, mid range Karatsuba multiplication, modified FFA and transposed filter, retiming

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Authors: Theodore Halnon, Martin Bojowald

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In relativity, time is relative between reference frames. However, quantum mechanics requires a specific time coordinate in order to write an evolution equation for wave functions. This difference between the two theories leads to the problem of time in quantum gravity. One method to study quantum relativity is to interpret the dynamics of a matter field as a clock. In order to test the relationship between different reference frames, an isotropic cosmological model with two matter ingredients is introduced. One is given by a scalar field and one by vacuum energy or a cosmological constant. There are two matter fields, and thus two different Hamiltonians are derived from the respective clock rates. Semi-classical solutions are found for these equations and a comparison is made of the physical predictions that they imply.

Keywords: cosmology, deparameterization, general relativity, quantum mechanics

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Authors: Sheheryar Khan, Weidong Li, Fanqian Meng

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The Urban Heat Island (UHI) effect is one of the foremost problems out of other ecological and socioeconomic issues in urbanization. Due to this phenomenon that human-made urban areas have replaced the rural landscape with the surface that increases thermal conductivity and urban warmth; as a result, the temperature in the city is higher than in the surrounding rural areas. To affect the evidence of this phenomenon in the Zhengzhou city area, an observation of the temperature variations in the urban area is done through a scientific method that has been followed. Landsat 8 satellite images were taken from 2013 to 2015 to calculate the effect of Urban Heat Island (UHI) along with the NPP-VRRIS night-time remote sensing data to analyze the result for a better understanding of the center of the built-up area. To further support the evidence, the correlation between land surface temperatures and the normalized difference vegetation index (NDVI) was calculated using the Red band 4 and Near-infrared band 5 of the Landsat 8 data. Mono-window algorithm was applied to retrieve the land surface temperature (LST) distribution from the Landsat 8 data using Band 10 and 11 accordingly to convert the top-of-atmosphere radiance (TOA) and to convert the satellite brightness temperature. Along with Landsat 8 data, NPP-VIIRS night-light data is preprocessed to get the research area data. The analysis between Landsat 8 data and NPP night-light data was taken to compare the output center of the Built-up area of Zhengzhou city.

Keywords: built-up area, land surface temperature, mono-window algorithm, NDVI, remote sensing, threshold method, Zhengzhou

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Authors: Yohanes Chekol Malede

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σ-phase has negative effects on the corrosion responses and the mechanical properties of steels. The growth of σ-phase in the austenite matrix of AISI 347H FG steel was simulated using DICTRA software using CALPHAD method. The simulation work included the influence of both volume diffusion and grain boundary diffusion. The simulation results showed a good agreement with the experimental findings. The simulation results revealed a Cr-depleted and a Ni-enriched σ-phase/austenite interface. Effects of temperature, grain size, and composition of alloying elements on the growth kinetics of σ-phase were assessed. The simulated results were fitted to the JMAK equation and a good correlation was obtained.

Keywords: AISI 347H FG austenitic steel, CALPHAD, sigma phase, microstructure evolution

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Authors: Agostinho Antunes

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The completion of the human genome sequencing in 2003 opened a new perspective into the importance of whole genome sequencing projects, and currently multiple species are having their genomes completed sequenced, from simple organisms, such as bacteria, to more complex taxa, such as mammals. This voluminous sequencing data generated across multiple organisms provides also the framework to better understand the genetic makeup of such species and related ones, allowing to explore the genetic changes underlining the evolution of diverse phenotypic traits. Here, recent results from our group retrieved from comparative evolutionary genomic analyses of selected marine animal species will be considered to exemplify how gene novelty and gene enhancement by positive selection might have been determinant in the success of adaptive radiations into diverse habitats and lifestyles.

Keywords: marine genomics, evolutionary bioinformatics, human genome sequencing, genomic analyses

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Authors: Alsu F. Saifitdinova, Alexey S. Komissarov, Svetlana A. Galkina, Elena I. Koshel, Maria M. Kulak, Stephen J. O'Brien, Elena R. Gaginskaya

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The mystery of sex determination is one of the most ancient and still not solved until the end so far. In many species, sex determination is genetic and often accompanied by the presence of dimorphic sex chromosomes in the karyotype. Genomic sequencing gave the information about the gene content of sex chromosomes which allowed to reveal their origin from ordinary autosomes and to trace their evolutionary history. Female-specific W chromosome in birds as well as mammalian male-specific Y chromosome is characterized by the degeneration of gene content and the accumulation of repetitive DNA. Tandem repeats complicate the analysis of genomic data. Despite the best efforts chicken W chromosome assembly includes only 1.2 Mb from expected 55 Mb. Supplementing the information on the sex chromosome composition not only helps to complete the assembly of genomes but also moves us in the direction of understanding of the sex-determination systems evolution. A whole-genome survey to the assembly Gallus_gallus WASHUC 2.60 was applied for repeats search in assembled genome and performed search and assembly of high copy number repeats in unassembled reads of SRR867748 short reads datasets. For cytogenetic analysis conventional methods of fluorescent in situ hybridization was used for previously cloned W specific satellites and specifically designed directly labeled synthetic oligonucleotide DNA probe was used for bioinformatically identified repetitive sequence. Hybridization was performed with mitotic chicken chromosomes and manually isolated giant meiotic lampbrush chromosomes from growing oocytes. A novel chicken W specific satellite (GGAAA)n which is not co-localizes with any previously described classes of W specific repeats was identified and mapped with high resolution. In the composition of autosomes this repeat units was found as a part of upstream regions of gonad specific protein coding sequences. These findings may contribute to the understanding of the role of tandem repeats in sex specific differentiation regulation in birds and sex chromosome evolution. This work was supported by the postdoctoral fellowships from St. Petersburg State University (#1.50.1623.2013 and #1.50.1043.2014), the grant for Leading Scientific Schools (#3553.2014.4) and the grant from Russian foundation for basic researches (#15-04-05684). The equipment and software of Research Resource Center “Chromas” and Theodosius Dobzhansky Center for Genome Bioinformatics of Saint Petersburg State University were used.

Keywords: birds, lampbrush chromosomes, sex chromosomes, tandem repeats

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Authors: Mahmoud Reza Hosseini

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The universe is in a continuous expansion process, resulting in the reduction of its density and temperature. Also, by extrapolating back from its current state, the universe at its early times is studied, known as the big bang theory. According to this theory, moments after creation, the universe was an extremely hot and dense environment. However, its rapid expansion due to nuclear fusion led to a reduction in its temperature and density. This is evidenced through the cosmic microwave background and the universe structure at a large scale. However, extrapolating back further from this early state reaches singularity, which cannot be explained by modern physics, and the big bang theory is no longer valid. In addition, one can expect a nonuniform energy distribution across the universe from a sudden expansion. However, highly accurate measurements reveal an equal temperature mapping across the universe, which is contradictory to the big bang principles. To resolve this issue, it is believed that cosmic inflation occurred at the very early stages of the birth of the universe. According to the cosmic inflation theory, the elements which formed the universe underwent a phase of exponential growth due to the existence of a large cosmological constant. The inflation phase allows the uniform distribution of energy so that an equal maximum temperature can be achieved across the early universe. Also, the evidence of quantum fluctuations of this stage provides a means for studying the types of imperfections the universe would begin with. Although well-established theories such as cosmic inflation and the big bang together provide a comprehensive picture of the early universe and how it evolved into its current state, they are unable to address the singularity paradox at the time of universe creation. Therefore, a practical model capable of describing how the universe was initiated is needed. This research series aims at addressing the singularity issue by introducing a state of energy called a "neutral state," possessing an energy level that is referred to as the "base energy." The governing principles of base energy are discussed in detail in our second paper in the series "A Conceptual Study for Addressing the Singularity of the Emerging Universe," which is discussed in detail. To establish a complete picture, the origin of the base energy should be identified and studied. In this research paper, the mechanism which led to the emergence of this natural state and its corresponding base energy is proposed. In addition, the effect of the base energy in the space-time fabric is discussed. Finally, the possible role of the base energy in quantization and energy exchange is investigated. Therefore, the proposed concept in this research series provides a road map for enhancing our understating of the universe's creation from nothing and its evolution and discusses the possibility of base energy as one of the main building blocks of this universe.

Keywords: big bang, cosmic inflation, birth of universe, energy creation, universe evolution

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Authors: Sylvain Perrin, Thomas Saillour

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The Grande-Motte port and seafront development project on the French Mediterranean coastline entailed evaluating wave impact loads (pressures and forces) on the new beach seawall and comparing the resulting scour potential at the base of the existing and new seawall. A physical model was built at ARTELIA’s hydraulics laboratory in Grenoble (France) to provide insight into the evolution of scouring overtime at the front of the wall, quasi-static and impulsive wave force intensity and distribution on the wall, and water and sand overtopping discharges over the wall. The beach was constituted of fine sand and approximately 50 m wide above mean sea level (MSL). Seabed slopes were in the range of 0.5% offshore to 1.5% closer to the beach. A smooth concrete structure will replace the existing concrete seawall with an elevated curved crown wall. Prior the start of breaking (at -7 m MSL contour), storm-driven maximum spectral significant wave heights of 2.8 m and 3.2 m were estimated for the benchmark historical storm event dated of 1997 and the 50-year return period storms respectively, resulting in 1 m high waves at the beach. For the wave load assessment, a tensor scale measured wave forces and moments and five piezo / piezo-resistive pressure sensors were placed on the wall. Light-weight sediment physical model and pressure and force measurements were performed with scale 1:18. The polyvinyl chloride light-weight particles used to model the prototype silty sand had a density of approximately 1 400 kg/m3 and a median diameter (d50) of 0.3 mm. Quantitative assessments of the seabed evolution were made using a measuring rod and also a laser scan survey. Testing demonstrated the occurrence of numerous impulsive wave impacts on the reflector (22%), induced not by direct wave breaking but mostly by wave run-up slamming on the top curved part of the wall. Wave forces of up to 264 kilonewtons and impulsive pressure spikes of up to 127 kilonewtons were measured. Maximum scour of -0.9 m was measured for the new seawall versus -0.6 m for the existing seawall, which is imputable to increased wave reflection (coefficient was 25.7 - 30.4% vs 23.4 - 28.6%). This paper presents a methodology for the setup and operation of a physical model in order to assess the hydrodynamic and morphodynamic processes at a beach seawall during storms events. It discusses the pros and cons of such methodology versus others, notably regarding structures peculiarities and model effects.

Keywords: beach, impacts, scour, seawall, waves

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Authors: Michael Karnes, Alper Yilmaz

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This paper presents the application of the omni-modeler towards pedestrian redetection. The pedestrian redetection task creates several challenges when applying deep neural networks (DNN) due to the variety of pedestrian appearance with camera position, the variety of environmental conditions, and the specificity required to recognize one pedestrian from another. DNNs require significant training sets and are not easily adapted for changes in class appearances or changes in the set of classes held in its knowledge domain. Pedestrian redetection requires an algorithm that can actively manage its knowledge domain as individuals move in and out of the scene, as well as learn individual appearances from a few frames of a video. The Omni-Modeler is a dynamically learning few-shot visual recognition algorithm developed for tasks with limited training data availability. The Omni-Modeler adapts the knowledge domain of pre-trained deep neural networks to novel concepts with a calculated localized language encoder. The Omni-Modeler knowledge domain is generated by creating a dynamic dictionary of concept definitions, which are directly updatable as new information becomes available. Query images are identified through nearest neighbor comparison to the learned object definitions. The study presented in this paper evaluates its performance in re-identifying individuals as they move through a scene in both single-camera and multi-camera tracking applications. The results demonstrate that the Omni-Modeler shows potential for across-camera view pedestrian redetection and is highly effective for single-camera redetection with a 93% accuracy across 30 individuals using 64 example images for each individual.

Keywords: dynamic learning, few-shot learning, pedestrian redetection, visual recognition

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Authors: A. Rong, P. B. Luh, R. Lahdelma

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High penetration of intermittent renewable energy sources (RES) such as solar power and wind power into the energy system has caused temporal and spatial imbalance between electric power supply and demand for some countries and regions. This brings about the critical need for coordinating power production and power exchange for different regions. As compared with the power-only systems, the combined heat and power (CHP) systems can provide additional flexibility of utilizing RES by exploiting the interdependence of power and heat production in the CHP plant. In the CHP system, power production can be influenced by adjusting heat production level and electric power can be used to satisfy heat demand by electric boiler or heat pump in conjunction with heat storage, which is much cheaper than electric storage. This paper addresses multi-site CHP systems without considering RES, which lay foundation for handling penetration of RES. The problem under study is the unit commitment (UC) of the transmission-constrained multi-site CHP systems. We solve the problem by combining linear relaxation of ON/OFF states and sequential dynamic programming (DP) techniques, where relaxed states are used to reduce the dimension of the UC problem and DP for improving the solution quality. Numerical results for daily scheduling with realistic models and data show that DP-based algorithm is from a few to a few hundred times faster than CPLEX (standard commercial optimization software) with good solution accuracy (less than 1% relative gap from the optimal solution on the average).

Keywords: dynamic programming, multi-site combined heat and power system, relaxed states, transmission-constrained generation unit commitment

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Authors: Eileen Kim

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As socioeconomic disparities grew in New York during the 1970s, artists represented new values that came with the times. Street art, in particular, was birthed from a distinctly urban, fringe setting to ultimately become one of the most lucrative forms of art today. Examining the economic and psychological reasons behind the rise of street art, this paper delves into the development of the art market as a parallel insight into human behaviors and economic models such as supply and demand. The purpose of this study is to show the role of the increasingly divided socioeconomic classes and the rise of art collecting as an asset-building form. This study concludes that the iconography and market value of street art represented distinct values that came from a series of intertwined social matters such as racial tensions and revolutions in industrial innovation.

Keywords: art industry, cultural representation, ethnicity, markets, public property, social classes, street art

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Authors: Seungchul Lee, Minjeong Kim, Iman Janghorban Esfahani, Jeong Tai Kim, ChangKyoo Yoo

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It is hard to maintain the effluent quality of the wastewater treatment plants (WWTPs) under with fixed types of operational control because of continuously changed influent flow rate and pollutant load. The aims of this study is development of multi-loop multi-objective control (ML-MOC) strategy in plant-wide scope targeting four objectives: 1) maximization of nutrient removal efficiency, 2) minimization of operational cost, 3) maximization of CH4 production in anaerobic digestion (AD) for CH4 reuse as a heat source and energy source, and 4) minimization of N2O gas emission to cope with global warming. First, benchmark simulation mode is modified to describe N2O dynamic in biological process, namely benchmark simulation model for greenhouse gases (BSM2G). Then, three types of single-loop proportional-integral (PI) controllers for DO controller, NO3 controller, and CH4 controller are implemented. Their optimal set-points of the controllers are found by using multi-objective genetic algorithm (MOGA). Finally, multi loop-MOC in BSM2G is implemented and evaluated in BSM2G. Compared with the reference case, the ML-MOC with the optimal set-points showed best control performances than references with improved performances of 34%, 5% and 79% of effluent quality, CH4 productivity, and N2O emission respectively, with the decrease of 65% in operational cost.

Keywords: Benchmark simulation model for greenhouse gas, multi-loop multi-objective controller, multi-objective genetic algorithm, wastewater treatment plant

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Authors: Dachuan Shi, M. Hecht, Y. Ye

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With the trend of digitalization in railway freight transport, a large number of freight wagons in Germany have been equipped with telematics devices, commonly placed on the wagon body. A telematics device contains a GPS module for tracking and a 3-axis accelerometer for shock detection. Besides these basic functions, it is desired to use the integrated accelerometer for condition monitoring without any additional sensors. Wheel flats as a common type of failure on wheel tread cause large impacts on wagons and infrastructure as well as impulsive noise. A large wheel flat may even cause safety issues such as derailments. In this sense, this paper proposes a machine learning approach for wheel flat detection by using car body accelerations. Due to suspension systems, impulsive signals caused by wheel flats are damped significantly and thus could be buried in signal noise and disturbances. Therefore, it is very challenging to detect wheel flats using car body accelerations. The proposed algorithm considers the envelope spectrum of car body accelerations to eliminate the effect of noise and disturbances. Subsequently, a 1-D convolutional neural network (CNN), which is well known as a deep learning method, is constructed to automatically extract features in the envelope-frequency domain and conduct classification. The constructed CNN is trained and tested on field test data, which are measured on the underframe of a tank wagon with a wheel flat of 20 mm length in the operational condition. The test results demonstrate the good performance of the proposed algorithm for real-time fault detection.

Keywords: fault detection, wheel flat, convolutional neural network, machine learning

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Authors: Ju-Hong Lee, Yi-Lin Shieh

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Two-dimensional (2-D) quadrature mirror filter (QMF) banks have been widely considered for high-quality coding of image and video data at low bit rates. Without implementing subband coding, a 2-D QMF bank is required to have an exactly linear-phase response without magnitude distortion, i.e., the perfect reconstruction (PR) characteristics. The design problem of 2-D QMF banks with the PR characteristics has been considered in the literature for many years. This paper presents a transformation approach for designing 2-D two-channel QMF banks. Under a suitable one-dimensional (1-D) to two-dimensional (2-D) transformation with a specified decimation/interpolation matrix, the analysis and synthesis filters of the QMF bank are composed of 1-D causal and stable digital allpass filters (DAFs) and possess the 2-D doubly complementary half-band (DC-HB) property. This facilitates the design problem of the two-channel QMF banks by finding the real coefficients of the 1-D recursive DAFs. The design problem is formulated based on the minimax phase approximation for the 1-D DAFs. A novel objective function is then derived to obtain an optimization for 1-D minimax phase approximation. As a result, the problem of minimizing the objective function can be simply solved by using the well-known weighted least-squares (WLS) algorithm in the minimax (L∞) optimal sense. The novelty of the proposed design method is that the design procedure is very simple and the designed 2-D QMF bank achieves perfect magnitude response and possesses satisfactory phase response. Simulation results show that the proposed design method provides much better design performance and much less design complexity as compared with the existing techniques.

Keywords: Quincunx QMF bank, doubly complementary filter, digital allpass filter, WLS algorithm

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Authors: Muna Alghabshi, Edmana Krishnan

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A nonlinear Schrodinger equation has been considered for solving by mapping methods in terms of Jacobi elliptic functions (JEFs). The equation under consideration has a linear evolution term, linear and nonlinear dispersion terms, the Kerr law nonlinearity term and three terms representing the contribution of meta materials. This equation which has applications in optical fibers is found to have soliton solutions, shock wave solutions, and singular wave solutions when the modulus of the JEFs approach 1 which is the infinite period limit. The equation with special values of the parameters has also been solved using the tanh method.

Keywords: Jacobi elliptic function, mapping methods, nonlinear Schrodinger Equation, tanh method

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Authors: Sani M. Lawal, Idris Musa, Aliyu D. Usman

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The Pareto approach of optimal solutions in a search space that evolved in multi-objective optimization problems is adopted in this paper, which stands for a set of solutions in the search space. This paper aims at presenting an optimal placement of Distributed Generation (DG) in radial distribution networks with an optimal size for minimization of power loss and voltage deviation as well as maximizing voltage profile of the networks. And these problems are formulated using particle swarm optimization (PSO) as a constraint nonlinear optimization problem with both locations and sizes of DG being continuous. The objective functions adopted are the total active power loss function and voltage deviation function. The multiple nature of the problem, made it necessary to form a multi-objective function in search of the solution that consists of both the DG location and size. The proposed PSO algorithm is used to determine optimal placement and size of DG in a distribution network. The output indicates that PSO algorithm technique shows an edge over other types of search methods due to its effectiveness and computational efficiency. The proposed method is tested on the standard IEEE 34-bus and validated with 33-bus test systems distribution networks. Results indicate that the sizing and location of DG are system dependent and should be optimally selected before installing the distributed generators in the system and also an improvement in the voltage profile and power loss reduction have been achieved.

Keywords: distributed generation, pareto, particle swarm optimization, power loss, voltage deviation

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Authors: Ahmad Haidar

Abstract:

The rapid adoption of Artificial Intelligence (AI) technology holds unforeseen risks like privacy violation, unemployment, and algorithmic bias, triggering research institutions, governments, and companies to develop principles of AI ethics. The extensive and diverse literature on AI lacks an analysis of the evolution of principles developed in recent years. There are two fundamental purposes of this paper. The first is to provide insights into how the principles of AI ethics have been changed recently, including concepts like risk management and public participation. In doing so, a NOISE (Needs, Opportunities, Improvements, Strengths, & Exceptions) analysis will be presented. Second, offering a framework for building Ethical AI linked to sustainability. This research adopts an explorative approach, more specifically, an inductive approach to address the theoretical gap. Consequently, this paper tracks the different efforts to have “trustworthy AI” and “ethical AI,” concluding a list of 12 documents released from 2017 to 2022. The analysis of this list unifies the different approaches toward trustworthy AI in two steps. First, splitting the principles into two categories, technical and net benefit, and second, testing the frequency of each principle, providing the different technical principles that may be useful for stakeholders considering the lifecycle of AI, or what is known as sustainable AI. Sustainable AI is the third wave of AI ethics and a movement to drive change throughout the entire lifecycle of AI products (i.e., idea generation, training, re-tuning, implementation, and governance) in the direction of greater ecological integrity and social fairness. In this vein, results suggest transparency, privacy, fairness, safety, autonomy, and accountability as recommended technical principles to include in the lifecycle of AI. Another contribution is to capture the different basis that aid the process of AI for sustainability (e.g., towards sustainable development goals). The results indicate data governance, do no harm, human well-being, and risk management as crucial AI for sustainability principles. This study’s last contribution clarifies how the principles evolved. To illustrate, in 2018, the Montreal declaration mentioned eight principles well-being, autonomy, privacy, solidarity, democratic participation, equity, and diversity. In 2021, notions emerged from the European Commission proposal, including public trust, public participation, scientific integrity, risk assessment, flexibility, benefit and cost, and interagency coordination. The study design will strengthen the validity of previous studies. Yet, we advance knowledge in trustworthy AI by considering recent documents, linking principles with sustainable AI and AI for sustainability, and shedding light on the evolution of guidelines over time.

Keywords: artificial intelligence, AI for sustainability, declarations, framework, regulations, risks, sustainable AI

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Authors: Abdelrahman Elsehsah, Hany Madkour, Khalid Farah

Abstract:

This article presents a 3-D modified non-linear elastic model in the strain space. The Helmholtz free energy function is introduced with the existence of a dissipation potential surface in the space of thermodynamic conjugate forces. The constitutive equation and the damage evolution were derived as well. The modified damage has been examined to model the nonlinear behavior of reinforced concrete (RC) slabs with an opening. A parametric study with RC was carried out to investigate the impact of different factors on the behavior of RC slabs. These factors are the opening area, the opening shape, the place of opening, and the thickness of the slabs. And the numerical results have been compared with the experimental data from literature. Finally, the model showed its ability to be applied to the structural analysis of RC slabs.

Keywords: damage mechanics, 3-D numerical analysis, RC, slab with opening

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Authors: Priyanka Tamta, Sukanya Sharma

Abstract:

The Kamakhya Temple in Assam plays a very important role in the development of Assam as not only a historical place but also as an archaeologically important site. Temple building activity on the site began in 5th century AD when a cave temple dedicated to Lord Balabhadraswami was constructed here by King Maharajadhiraja Sri Surendra Varman. In the history of Assam, the name of this king is not found and neither the name of this form of Vishnu is known in this region. But this inscription sanctified the place as it recorded the first ever temple building activity in this region. The fifteen hundred years habitation history of the Kamakhya temple sites shows a gradual progression of the site from a religious site to an archaeological site and finally as a historical landmark. Here, in this paper, our main objective is to understand the evolution of Kamakhya temple site as a historical landscape and as an important landmark in the history of Assam. The central theme of the paper is the gradual development of the religious site to a historical landmark. From epigraphical records, it is known that the site received patronage from all ruling dynasties of Assam and its adjoining regions. Royal households of Kashmir, Nepal, Bengal, Orissa, Bihar, etc. have left their footprints on the site. According to records they donated wealth, constructed or renovated temples and participated in the overall maintenance of the deity. This made Kamakhya temple a ground of interaction of faiths, communities, and royalties of the region. Since the 5th century AD, there was a continuous struggle between different beliefs, faiths, and power on the site to become the dominant authority of the site. In the process, powerful beliefs system subsumed minor ones into a larger doctrine of beliefs. This can be seen in the case of the evolution of the Kamakhya temple site as one of the important Shakta temples in India. Today, it is cultural identity marker of the state of Assam within which it is located. Its diverse faiths and beliefs have been appropriated by powerful legends to the dominant faith of the land. The temple has evolved from a cave temple to a complex of seventeen temples. The faith has evolved from the worship of water, an element of nature to the worship of the ten different forms of the goddess with their five male consorts or Bhairavas. Today, it represents and symbolizes the relationship of power and control out of which it has emerged. During different periods of occupation certain architectural and iconographical characters developed which indicated diffusion and cultural adaptation. Using this as sources and the epigraphical records this paper will analyze the interactive and dynamic processes which operated in the building of this cultural marker, the archaeological site of Kamakhya.

Keywords: cultural adaptation and diffusion, cultural and historical landscape, Kamakhya, Saktism, temple art and architecture, historiography

Procedia PDF Downloads 237