Search results for: parallel and distributed computing
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3975

Search results for: parallel and distributed computing

2085 Hybrid Wind Solar Gas Reliability Optimization Using Harmony Search under Performance and Budget Constraints

Authors: Meziane Rachid, Boufala Seddik, Hamzi Amar, Amara Mohamed

Abstract:

Today’s energy industry seeks maximum benefit with maximum reliability. In order to achieve this goal, design engineers depend on reliability optimization techniques. This work uses a harmony search algorithm (HS) meta-heuristic optimization method to solve the problem of wind-Solar-Gas power systems design optimization. We consider the case where redundant electrical components are chosen to achieve a desirable level of reliability. The electrical power components of the system are characterized by their cost, capacity and reliability. The reliability is considered in this work as the ability to satisfy the consumer demand which is represented as a piecewise cumulative load curve. This definition of the reliability index is widely used for power systems. The proposed meta-heuristic seeks for the optimal design of series-parallel power systems in which a multiple choice of wind generators, transformers and lines are allowed from a list of product available in the market. Our approach has the advantage to allow electrical power components with different parameters to be allocated in electrical power systems. To allow fast reliability estimation, a universal moment generating function (UMGF) method is applied. A computer program has been developed to implement the UMGF and the HS algorithm. An illustrative example is presented.

Keywords: reliability optimization, harmony search optimization (HSA), universal generating function (UMGF)

Procedia PDF Downloads 576
2084 Waste Prevention and Economic Policy: Policy Tools for Increasing Resource Efficiency and Savings

Authors: Sylvia Graczka

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Waste related environmental problems are not only exploding but are also spotlighted for capacity shortages in recycling, as China announced its ban on waste imports. According to the waste hierarchy, prevention is the primary solution for waste, and also the cheapest. Waste related environmental pollution as externality puts an ever-growing burden on communities bearing the social costs. Economic policies often claim to be pro-environment, this often appears only theoretically, or at the level of principles. There are few concrete occurrences of tools in economic policies, such as green taxes, that are truly effective in stimulating the shift towards waste reduction. The paper presents theoretical economic policy tools based on literature review, and case studies on applied economic policy tools by analyzing policy papers, strategies in force, in line with ‘polluter pays’ and ‘extended producer responsibility’ principles. The study also emphasizes the differences between the broader notion of waste reduction and that of waste minimization, parallel to the difference between resource efficiency and resource savings. It also puts the issue in the context of neoclassical environmental economics and ecological economics, to present alternatives in approach. The research concludes in identifying effective economic policy tools that support the reduction of material use, and the prevention of waste. Consumer and producer awareness of waste problems and consciousness related to their choices are inevitable to make economic policy tools work effectively.

Keywords: economic policy, producer responsibility, resource efficiency, waste prevention

Procedia PDF Downloads 149
2083 A Joint Possibilistic-Probabilistic Tool for Load Flow Uncertainty Assessment-Part I: Formulation

Authors: Morteza Aien, Masoud Rashidinejad, Mahmud Fotuhi-Firuzabad

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As energetic and environmental issues are getting more and more attention all around the world, the penetration of distributed energy resources (DERs) mainly those harvesting renewable energies (REs) ascends with an unprecedented rate. This matter causes more uncertainties to appear in the power system context; ergo, the uncertainty analysis of the system performance is an obligation. The uncertainties of any system can be represented probabilistically or possibilistically. Since sufficient historical data about all the system variables is not available, therefore, they do not have a probability density function (PDF) and must be represented possibilistiacally. When some of system uncertain variables are probabilistic and some are possibilistic, neither the conventional pure probabilistic nor pure possibilistic methods can be implemented. Hence, a combined solution is appealed. The first of this two-paper series formulates a new possibilistic-probabilistic tool for the load flow uncertainty assessment. The proposed methodology is based on the evidence theory and joint propagation of possibilistic and probabilistic uncertainties. This possibilistic- probabilistic formulation is solved in the second companion paper in an uncertain load flow (ULF) study problem.

Keywords: probabilistic uncertainty modeling, possibilistic uncertainty modeling, uncertain load flow, wind turbine generator

Procedia PDF Downloads 562
2082 Impact of Similarity Ratings on Human Judgement

Authors: Ian A. McCulloh, Madelaine Zinser, Jesse Patsolic, Michael Ramos

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Recommender systems are a common artificial intelligence (AI) application. For any given input, a search system will return a rank-ordered list of similar items. As users review returned items, they must decide when to halt the search and either revise search terms or conclude their requirement is novel with no similar items in the database. We present a statistically designed experiment that investigates the impact of similarity ratings on human judgement to conclude a search item is novel and halt the search. 450 participants were recruited from Amazon Mechanical Turk to render judgement across 12 decision tasks. We find the inclusion of ratings increases the human perception that items are novel. Percent similarity increases novelty discernment when compared with star-rated similarity or the absence of a rating. Ratings reduce the time to decide and improve decision confidence. This suggests the inclusion of similarity ratings can aid human decision-makers in knowledge search tasks.

Keywords: ratings, rankings, crowdsourcing, empirical studies, user studies, similarity measures, human-centered computing, novelty in information retrieval

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2081 Identification and Quantification of Phenolic Compounds In Cassia tora Collected from Three Different Locations Using Ultra High Performance Liquid Chromatography – Electro Spray Ionization – Mass Spectrometry (UHPLC-ESI-MS-MS)

Authors: Shipra Shukla, Gaurav Chaudhary, S. K. Tewari, Mahesh Pal, D. K. Upreti

Abstract:

Cassia tora L. is widely distributed in tropical Asian countries, commonly known as sickle pod. Various parts of the plant are reported for their medicinal value due to presence of anthraquinones, phenolic compounds, emodin, β-sitosterol, and chrysophanol. Therefore a sensitive analytical procedure using UHPLC-ESI-MS/MS was developed and validated for simultaneous quantification of five phenolic compounds in leaf, stem and root extracts of Cassia tora. Rapid chromatographic separation of compounds was achieved on Acquity UHPLC BEH C18 column (50 mm×2.1 mm id, 1.7µm) column in 2.5 min. Quantification was carried out using negative electrospray ionization in multiple-reaction monitoring mode. The method was validated as per ICH guidelines and showed good linearity (r2 ≥ 0.9985) over the concentration range of 0.5-200 ng/mL. The intra- and inter-day precisions and accuracy were within RSDs ≤ 1.93% and ≤ 1.90%, respectively. The developed method was applied to investigate variation of five phenolic compounds in the three geographical collections. Results indicated significant variation among analyzed samples collected from different locations in India.

Keywords: Cassia tora, phenolic compounds, quantification, UHPLC-ESI-MS/MS

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2080 Correction of Frequent English Writing Errors by Using Coded Indirect Corrective Feedback and Error Treatment: The Case of Reading and Writing English for Academic Purposes II

Authors: Chaiwat Tantarangsee

Abstract:

The purposes of this study are 1) to study the frequent English writing errors of students registering the course: Reading and Writing English for Academic Purposes II, and 2) to find out the results of writing error correction by using coded indirect corrective feedback and writing error treatments. Samples include 28 2nd year English Major students, Faculty of Education, Suan Sunandha Rajabhat University. Tool for experimental study includes the lesson plan of the course; Reading and Writing English for Academic Purposes II, and tool for data collection includes 4 writing tests of short texts. The research findings disclose that frequent English writing errors found in this course comprise 7 types of grammatical errors, namely Fragment sentence, Subject-verb agreement, Wrong form of verb tense, Singular or plural noun endings, Run-ons sentence, Wrong form of verb pattern and Lack of parallel structure. Moreover, it is found that the results of writing error correction by using coded indirect corrective feedback and error treatment reveal the overall reduction of the frequent English writing errors and the increase of students’ achievement in the writing of short texts with the significance at .05.

Keywords: coded indirect corrective feedback, error correction, error treatment, English writing

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2079 Evaluation of Urban Land Development Direction in Kabul City, Afghanistan

Authors: Ahmad Sharif Ahmadi, Yoshitaka Kajita

Abstract:

Kabul, the capital and largest city in Afghanistan has been experiencing a massive population expansion and fast economic development in last decade, in which urban land has increasingly expanded and formed a high informal development territory in the city. This paper investigates the urban land development direction based on the integrated urbanization trends in Kabul city since the last and the fastest ever urban land growth period (1999-2008), which is parallel with the establishment of the new government in Afghanistan. Considering the existing challenges in terms of informal settlements, squatter settlements, the population expansion of the city, and fast economic development, as well as the huge influx of returning refugees from neighboring countries, and the sprawl direction of urbanization of the Kabul city urban fringes, this research focuses on the possible urban land development direction and trends for the city. The paper studies the feasible future land development direction of Kabul city in the northern part called Shamali basin, in which district 17 is the gateway for future development. The area has much developable area including eight districts of Kabul province, and the vast area of Parwan and Kapisa provinces. The northern area of the Kabul city generally has favorable conditions for further urbanization from the city. It is a large and relatively flat area of area in the northern part of Kabul city, with ample water resources available from the Panjshir basin as a base principle of land development direction in the area.

Keywords: Kabul city, land development trends, urban land development, urbanization

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2078 The Effect of Aerobic Exercise Training on the Improvement of Nursing Staff's Sleep Quality: A Randomized Controlled Study

Authors: Niu Shu Fen

Abstract:

Sleep disturbance is highly prevalent among shift-working nurses. We aimed to evaluate whether aerobic exercise (i.e., walking combined with jogging) improves objective Sleepparameters among female nurses at the end of an 8-week exercise program and 4 weeks after study completion. This single-blinded, parallel design, randomized controlled trial was conducted in the floor classroom of a would-be medical center in northern Taiwan. Sixtyeligible female nurses were randomly assigned to either aerobic exercise (n = 30) or usual care (n = 30) group. The moderate-intensity aerobic exercise program was performed over 5days (60 min per day) a week for 8 weeks after work hours. Objective sleep outcomes including total sleep time (TST), sleep onset latency (SOL), wake after sleep onset (WASO), and sleep efficiency (SE), were retrieved using an Actigraph device. A generalized estimated equation model was used for data analyses. The aerobic exercise group had significant improvements in TST and SE at 4 weeks and 8 weeks compared with baseline evaluation(TST: B = 70.49 and 55.96, both p < 0.001; SE: B = 5.21 and 3.98, p < 0.001 and 0.002).Significant between-group differences were observed in SOL and WASO at 4 weeks but not8 weeks compared with the baseline evaluation (SOL: B = −7.18, p = 0.03; WASO: B =−11.38, p = 0.008). The positive lasting effects for TST were observed only until the 4-week follow-up. To improve sleep quality and quantity, we encourage female nurses to regularly perform moderate-intensity aerobic exercise.

Keywords: sleep quality, aerobic exercise, nurses, shift work

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2077 The Antecedents of Brand Loyalty on Female Cosmetics Buying Behavior

Authors: Velly Anatasia

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The worldwide annual expenditure for cosmetics is estimated at U.S. $18 billion and many players in the field are competing aggressively to capture more and more markets. Players in the cosmetics industry strive to be the foremost by establish customer loyalty. Furthermore, customer loyalty is portrayed by brand loyalty. Therefore, brand loyalty is the key determine of winning the competition in tight market. This study examines the influence of brand loyalty on cosmetics buying behavior of female consumers in Jakarta as capital of Indonesia. The seven factors of brand loyalty are brand name, Product quality, price, design, promotion, servicesquality and store environment. The paper adopted descriptive analysis, factor loading and multiple regression approach to test the hypotheses. The data has been collected by using questionnaires which were distributed and self-administered to 125female respondents accustomed using cosmetics. The findings of this study indicated that promotion has shown strong correlation with brand loyalty. The research results showed that there is positive and significant relationship between factors of brand loyalty (brand name, product quality, price, design, promotion, services quality and store environment) with cosmetics brand loyalty.

Keywords: brand loyalty, brand name, product quality, service quality, promotion

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2076 Geochemical Characterization of the Fahdene Formation in the Kef-Tedjerouine Area (Northwestern Tunisia)

Authors: Tahani Hallek, Dhaou Akrout, Riadh Ahmadi, Mabrouk Montacer

Abstract:

The present work is an organo-geochemical study of the Fahdene Formation outcrops at the Mahjouba region belonging to the Eastern part of the Kalaat Senan structure in northwestern Tunisia (the Kef-Tedjerouine area). The analytical study of the organic content of the samples collected, allowed us to point out that the Formation in question is characterized by an average to good oil potential. This fossilized organic matter has a planktonic marine origin (type II), as indicated by the relatively high values of hydrogen index. Tmax values are in the range 440°C and attest a thermal stage of the oil window beginning. Mineralogical study found the existence of macro and micro fractures that are parallel to rock stratification or oblique with a high density. Fill standpoint, the major component of the mineralized veins is the fibrous calcite with bitumen traces. The composition of these fractures is mainly due to the availability of chemical elements scattered in the surrounding rock. As for the origin of these fractures, we assume that fluid pressure processes are heavily involved, together with the regional compressional tectonic stress regime. The Fahdene Formation has a great importance in conventional oil development as a potential source rock, and even in terms of unconventional oil exploitation through the intense fracturing allowing the percolation of gas shale and facilitating its exploitation.

Keywords: fluid pressure, fracturation, oil exploration, organic matter

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2075 Root Cause Analysis of Excessive Vibration in a Feeder Pump of a Large Thermal Electric Power Plant: A Simulation Approach

Authors: Kavindan Balakrishnan

Abstract:

Root cause Identification of the Vibration phenomenon in a feedwater pumping station was the main objective of this research. First, the mode shapes of the pumping structure were investigated using numerical and analytical methods. Then the flow pressure and streamline distribution in the pump sump were examined using C.F.D. simulation, which was hypothesized can be a cause of vibration in the pumping station. As the problem specification of this research states, the vibration phenomenon in the pumping station, with four parallel pumps operating at the same time and heavy vibration recorded even after several maintenance steps. They also specified that a relatively large amplitude of vibration exited by pumps 1 and 4 while others remain normal. As a result, the focus of this research was on determining the cause of such a mode of vibration in the pump station with the assistance of Finite Element Analysis tools and Analytical methods. Major outcomes were observed in structural behavior which is favorable to the vibration pattern phenomenon in the pumping structure as a result of this research. Behaviors of the numerical and analytical models of the pump structure have similar characteristics in their mode shapes, particularly in their 2nd mode shape, which is considerably related to the exact cause of the research problem statement. Since this study reveals several possible points of flow visualization in the pump sump model that can be a favorable cause of vibration in the system, there is more room for improved investigation on flow conditions relating to pump vibrations.

Keywords: vibration, simulation, analysis, Ansys, Matlab, mode shapes, pressure distribution, structure

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2074 Sensitivity Analysis Optimization of a Horizontal Axis Wind Turbine from Its Aerodynamic Profiles

Authors: Kevin Molina, Daniel Ortega, Manuel Martinez, Andres Gonzalez-Estrada, William Pinto

Abstract:

Due to the increasing environmental impact, the wind energy is getting strong. This research studied the relationship between the power produced by a horizontal axis wind turbine (HAWT) and the aerodynamic profiles used for its construction. The analysis is studied using the Computational Fluid Dynamic (CFD), presenting the parallel between the energy generated by a turbine designed with selected profiles and another one optimized. For the study, a selection process was carried out from profile NACA 6 digits recommended by the National Renewable Energy Laboratory (NREL) for the construction of this type of turbines. The selection was taken into account different characteristics of the wind (speed and density) and the profiles (aerodynamic coefficients Cl and Cd to different Reynolds and incidence angles). From the selected profiles, was carried out a sensitivity analysis optimization process between its geometry and the aerodynamic forces that are induced on it. The 3D model of the turbines was realized using the Blade Element Momentum method (BEM) and both profiles. The flow fields on the turbines were simulated, obtaining the forces induced on the blade, the torques produced and an increase of 3% in power due to the optimized profiles. Therefore, the results show that the sensitivity analysis optimization process can assist to increment the wind turbine power.

Keywords: blade element momentum, blade, fluid structure interaction, horizontal axis wind turbine, profile design

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2073 Time Overrun in Pre-Construction Planning Phase of Construction Projects

Authors: Hafiz Usama Imad, Muhammad Akram Akhund, Tauha Hussain Ali, Ali Raza Khoso, Fida Hussain Siddiqui

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Construction industry plays a significant role in fulfilling the major requirements of the human being. It is one of the major constituents of every developed country. Although the construction industry of both the developing and developed countries encompasses a major part of the economy, and millions of rupees are utilized every year on various kinds of construction projects. But, this industry is facing numerous hurdles in terms of its budget and timely completion. Construction projects generally consist of several phases like planning, designing, execution, and finishing. This research study aims to determine the significant factors of time overrun in pre-construction planning (PCP) phase of construction projects in Pakistan. Questionnaires were distributed by various means and responses of respondents were compiled and collected data were then analyzed through a statistical technique using SPSS version 24. Major causes of time overrun in pre-construction planning phase; which is an extremely important phase of construction projects, were revealed. The research conclusion will provide a pathway for stakeholders to pay attention to the mentioned causes to overcome the major issue of time overrun.

Keywords: construction industry, Pakistan, pre-construction planning phase, time overrun

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2072 A Dynamic Neural Network Model for Accurate Detection of Masked Faces

Authors: Oladapo Tolulope Ibitoye

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Neural networks have become prominent and widely engaged in algorithmic-based machine learning networks. They are perfect in solving day-to-day issues to a certain extent. Neural networks are computing systems with several interconnected nodes. One of the numerous areas of application of neural networks is object detection. This is a prominent area due to the coronavirus disease pandemic and the post-pandemic phases. Wearing a face mask in public slows the spread of the virus, according to experts’ submission. This calls for the development of a reliable and effective model for detecting face masks on people's faces during compliance checks. The existing neural network models for facemask detection are characterized by their black-box nature and large dataset requirement. The highlighted challenges have compromised the performance of the existing models. The proposed model utilized Faster R-CNN Model on Inception V3 backbone to reduce system complexity and dataset requirement. The model was trained and validated with very few datasets and evaluation results shows an overall accuracy of 96% regardless of skin tone.

Keywords: convolutional neural network, face detection, face mask, masked faces

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2071 Artificial Reproduction System and Imbalanced Dataset: A Mendelian Classification

Authors: Anita Kushwaha

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We propose a new evolutionary computational model called Artificial Reproduction System which is based on the complex process of meiotic reproduction occurring between male and female cells of the living organisms. Artificial Reproduction System is an attempt towards a new computational intelligence approach inspired by the theoretical reproduction mechanism, observed reproduction functions, principles and mechanisms. A reproductive organism is programmed by genes and can be viewed as an automaton, mapping and reducing so as to create copies of those genes in its off springs. In Artificial Reproduction System, the binding mechanism between male and female cells is studied, parameters are chosen and a network is constructed also a feedback system for self regularization is established. The model then applies Mendel’s law of inheritance, allele-allele associations and can be used to perform data analysis of imbalanced data, multivariate, multiclass and big data. In the experimental study Artificial Reproduction System is compared with other state of the art classifiers like SVM, Radial Basis Function, neural networks, K-Nearest Neighbor for some benchmark datasets and comparison results indicates a good performance.

Keywords: bio-inspired computation, nature- inspired computation, natural computing, data mining

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2070 The Intersection/Union Region Computation for Drosophila Brain Images Using Encoding Schemes Based on Multi-Core CPUs

Authors: Ming-Yang Guo, Cheng-Xian Wu, Wei-Xiang Chen, Chun-Yuan Lin, Yen-Jen Lin, Ann-Shyn Chiang

Abstract:

With more and more Drosophila Driver and Neuron images, it is an important work to find the similarity relationships among them as the functional inference. There is a general problem that how to find a Drosophila Driver image, which can cover a set of Drosophila Driver/Neuron images. In order to solve this problem, the intersection/union region for a set of images should be computed at first, then a comparison work is used to calculate the similarities between the region and other images. In this paper, three encoding schemes, namely Integer, Boolean, Decimal, are proposed to encode each image as a one-dimensional structure. Then, the intersection/union region from these images can be computed by using the compare operations, Boolean operators and lookup table method. Finally, the comparison work is done as the union region computation, and the similarity score can be calculated by the definition of Tanimoto coefficient. The above methods for the region computation are also implemented in the multi-core CPUs environment with the OpenMP. From the experimental results, in the encoding phase, the performance by the Boolean scheme is the best than that by others; in the region computation phase, the performance by Decimal is the best when the number of images is large. The speedup ratio can achieve 12 based on 16 CPUs. This work was supported by the Ministry of Science and Technology under the grant MOST 106-2221-E-182-070.

Keywords: Drosophila driver image, Drosophila neuron images, intersection/union computation, parallel processing, OpenMP

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2069 Proteomic Analysis of 2,4-Epibrassinolide Alleviating Low Temperature Stress in Rice Seedling Leaves

Authors: Jiang Xu, Daoping Wang, Qun Li, Yinghong Pan

Abstract:

2,4-Epibrassinolide (EBR), which is a kind of plant hormone Brassinosteroids (BRs), is widely studied and applied in the global scale but the proteomic characteristics of EBR alleviating low temperature stress in rice seedling leaves are still not clear. In this study, seeding rice of Nipponbare were treated with EBR and distilled water, then stressed at 4℃ or 26 ℃, and analyzed by mass spectrometry analysis, verified by parallel reaction monitoring technique (PRM). The results showed that 5778 proteins were identified in total and 4834 proteins were identified with quantitative information. Among them, 401 up-regulated and 220 down-regulated proteins may be related to EBR alleviating low temperature stress in rice seedling leaves. The molecular functions of most of up-regulated proteins are RNA binding and hydrolase activity and are mainly enriched in the pathways of carbon metabolism, folic acid synthesis, and amino acid biosynthesis. The down-regulated proteins are mainly related to catalytic activity and oxidoreductase activity and are mainly enriched in the pathways of limonene and pinene degradation, riboflavin metabolism, porphyrin and chlorophyll metabolism, and other metabolic pathways. PRM validation and literature analysis showed that NADP-malic acidase, peroxidase, 3-phosphoglycerate dehydrogenase, enolase, glyceraldehyde-3- phosphate dehydrogenase and pyruvate kinase are closely related to the effect of EBR on low temperature stress. These results also suggested that BRs could relieve the effect of low temperature stress on rice seed germination in many ways.

Keywords: 2, 4-Epibrassinolid, low temperature stress, proteomic analysis, rice

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2068 General Purpose Graphic Processing Units Based Real Time Video Tracking System

Authors: Mallikarjuna Rao Gundavarapu, Ch. Mallikarjuna Rao, K. Anuradha Bai

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Real Time Video Tracking is a challenging task for computing professionals. The performance of video tracking techniques is greatly affected by background detection and elimination process. Local regions of the image frame contain vital information of background and foreground. However, pixel-level processing of local regions consumes a good amount of computational time and memory space by traditional approaches. In our approach we have explored the concurrent computational ability of General Purpose Graphic Processing Units (GPGPU) to address this problem. The Gaussian Mixture Model (GMM) with adaptive weighted kernels is used for detecting the background. The weights of the kernel are influenced by local regions and are updated by inter-frame variations of these corresponding regions. The proposed system has been tested with GPU devices such as GeForce GTX 280, GeForce GTX 280 and Quadro K2000. The results are encouraging with maximum speed up 10X compared to sequential approach.

Keywords: connected components, embrace threads, local weighted kernel, structuring elements

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2067 An Activity Based Trajectory Search Approach

Authors: Mohamed Mahmoud Hasan, Hoda M. O. Mokhtar

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With the gigantic increment in portable applications use and the spread of positioning and location-aware technologies that we are seeing today, new procedures and methodologies for location-based strategies are required. Location recommendation is one of the highly demanded location-aware applications uniquely with the wide accessibility of social network applications that are location-aware including Facebook check-ins, Foursquare, and others. In this paper, we aim to present a new methodology for location recommendation. The proposed approach coordinates customary spatial traits alongside other essential components including shortest distance, and user interests. We also present another idea namely, "activity trajectory" that represents trajectory that fulfills the set of activities that the user is intrigued to do. The approach dispatched acquaints the related distance value to select trajectory(ies) with minimum cost value (distance) and spatial-area to prune unneeded directions. The proposed calculation utilizes the idea of movement direction to prescribe most comparable N-trajectory(ies) that matches the client's required action design with least voyaging separation. To upgrade the execution of the proposed approach, parallel handling is applied through the employment of a MapReduce based approach. Experiments taking into account genuine information sets were built up and tested for assessing the proposed approach. The exhibited tests indicate how the proposed approach beets different strategies giving better precision and run time.

Keywords: location based recommendation, map-reduce, recommendation system, trajectory search

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2066 An Equivalent Circuit Model Approach for Battery Pack Simulation in a Hybrid Electric Vehicle System Powertrain

Authors: Suchitra Sivakumar, Hajime Shingyouchi, Toshinori Okajima, Kyohei Yamaguchi, Jin Kusaka

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The progressing need for powertrain electrification calls for more accurate and reliable simulation models. A battery pack serves as the most vital component for energy storage in an electrified powertrain. Hybrid electric vehicles (HEV) do not behave the same way as they age, and there are several environmental factors that account for the degradation of the battery on a system level. Therefore, in this work, a battery model was proposed to study the state of charge (SOC) variation and the internal dynamic changes that contribute to aging and performance degradation in HEV batteries. An equivalent circuit battery model (ECM) is built using MATLAB Simulink to investigate the output characteristics of the lithium-ion battery. The ECM comprises of circuit elements like a voltage source, a series resistor and a parallel RC network connected in series. A parameter estimation study is conducted on the ECM to study the dependencies of the circuit elements with the state of charge (SOC) and the terminal voltage of the battery. The battery model is extended to simulate the temperature dependence of the individual battery cell and the battery pack with the environment. The temperature dependence model accounts for the heat loss due to internal resistance build up in the battery pack during charging, discharging, and due to atmospheric temperature. The model was validated for a lithium-ion battery pack with an independent drive cycle showing a voltage accuracy of 4% and SOC accuracy of about 2%.

Keywords: battery model, hybrid electric vehicle, lithium-ion battery, thermal model

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2065 An ERP Study of Chinese Pseudo-Object Structures

Authors: Changyin Zhou

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Verb-argument relation is a very important aspect of syntax-semantics interaction in sentence processing. Previous ERP (event related potentials) studies in this field mainly concentrated on the relation between the verb and its core arguments. The present study aims to reveal the ERP pattern of Chinese pseudo-object structures (SOSs), in which a peripheral argument is promoted to occupy the position of the patient object, as compared with the patient object structures (POSs). The ERP data were collected when participants were asked to perform acceptability judgments about Chinese phrases. Our result shows that, similar to the previous studies of number-of-argument violations, Chinese SOSs show a bilaterally distributed N400 effect. But different from all the previous studies of verb-argument relations, Chinese SOSs demonstrate a sustained anterior positivity (SAP). This SAP, which is the first report related to complexity of argument structure operation, reflects the integration difficulty of the newly promoted arguments and the progressive nature of well-formedness checking in the processing of Chinese SOSs.

Keywords: Chinese pseudo-object structures, ERP, sustained anterior positivity, verb-argument relation

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2064 Determinants of Inward Foreign Direct Investment: New Evidence from Bangladesh

Authors: Mohammad Maruf Hasan

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Foreign Direct Investment (FDI) has been increased at a remarkable position around the globe in which emerging economies are getting more FDI compared to industrialized economies. This study aims to examine the determinants of inward FDI flows in Bangladesh. To estimate the long and short-run impact of the FDI determinants for 1996-2020, we employed the Autoregressive-Distributed Lag (ARDL) model. Results show that: (1) macroeconomic determinants, such as economic growth, infrastructure, and market size, have a significant and strong positive effect.(2) Inflation exchange rate shows insignificant effects, while trade openness has mixed (short-run negative, long-run positive) effects on FDI inflows in both the long and short run. (3) Current institutional determinants rule of law has a positive effect on FDI inflows but is statistically insignificant, political stability has a negative, and the rule of law has a considerable beneficial impact on inflows of FDI. (4) The macroeconomic factors have been determined to impact Bangladesh's FDI inflows. Finally, a stable macroeconomic climate is more effective at luring FDI, as this study confirms. From a policy perspective, this study will help the government and policymakers to make a new investment policy.

Keywords: determinants, FDI, ARDL, Bangladesh

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2063 Distributed Energy Storage as a Potential Solution to Electrical Network Variance

Authors: V. Rao, A. Bedford

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As the efficient performance of national grid becomes increasingly important to maintain the electrical network stability, the balance between the generation and the demand must be effectively maintained. To do this, any losses that occur in the power network must be reduced by compensating for it. In this paper, one of the main cause for the losses in the network is identified as the variance, which hinders the grid’s power carrying capacity. The reason for the variance in the grid is investigated and identified as the rise in the integration of renewable energy sources (RES) such as wind and solar power. The intermittent nature of these RES along with fluctuating demands gives rise to variance in the electrical network. The losses that occur during this process is estimated by analyzing the network’s power profiles. Whilst researchers have identified different ways to tackle this problem, little consideration is given to energy storage. This paper seeks to redress this by considering the role of energy storage systems as potential solutions to reduce variance in the network. The implementation of suitable energy storage systems based on different applications is presented in this paper as part of variance reduction method and thus contribute towards maintaining a stable and efficient grid operation.

Keywords: energy storage, electrical losses, national grid, renewable energy, variance

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2062 The Status of BIM Adoption in Six Continents

Authors: Wooyoung Jung, Ghang Lee

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This paper paper reports the worldwide status of building information modeling (BIM) adoption from the perspectives of the engagement level, the Hype Cycle model, the technology diffusion model, and BIM-uses. An online survey was distributed, and 156 experts from six continents responded. Overall, North America was the most advanced continent, followed by Oceania and Europe. Countries in Asia perceived their phase mainly as slope of enlightenment (mature) in the Hype Cycle model. In the technology diffusion model, the main BIM-users worldwide were “early majority” (third phase), but those in the Middle East/Africa and South America were “early adopters” (second phase). In addition, the more advanced the country, the more number of BIM services employed in general. In summary, North America, Europe, Oceania, and Asia were advancing rapidly toward the mature stage of BIM, whereas the Middle East/Africa and South America were still in the early phase. The simple indexes used in this study may be used to track the worldwide status of BIM adoption in long-term surveys.

Keywords: BIM adoption, BIM services, hype cycle model, technology diffusion model

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2061 Cooperative Sensing for Wireless Sensor Networks

Authors: Julien Romieux, Fabio Verdicchio

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Wireless Sensor Networks (WSNs), which sense environmental data with battery-powered nodes, require multi-hop communication. This power-demanding task adds an extra workload that is unfairly distributed across the network. As a result, nodes run out of battery at different times: this requires an impractical individual node maintenance scheme. Therefore we investigate a new Cooperative Sensing approach that extends the WSN operational life and allows a more practical network maintenance scheme (where all nodes deplete their batteries almost at the same time). We propose a novel cooperative algorithm that derives a piecewise representation of the sensed signal while controlling approximation accuracy. Simulations show that our algorithm increases WSN operational life and spreads communication workload evenly. Results convey a counterintuitive conclusion: distributing workload fairly amongst nodes may not decrease the network power consumption and yet extend the WSN operational life. This is achieved as our cooperative approach decreases the workload of the most burdened cluster in the network.

Keywords: cooperative signal processing, signal representation and approximation, power management, wireless sensor networks

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2060 A Study of Microglitches in Hartebeesthoek Radio Pulsars

Authors: Onuchukwu Chika Christian, Chukwude Augustine Ejike

Abstract:

We carried out a statistical analyse of microglitches events on a sample of radio pulsars. The distribution of microglitch events in frequency (ν) and first frequency derivatives ν˙ indicates that the size of a microglitch and sign combinations of events in ν and ν˙ are purely randomized. Assuming that the probability of a given size of a microglitch event occurring scales inversely as the absolute size of the event in both ν and ν˙, we constructed a cumulative distribution function (CDF) for the absolute sizes of microglitches. In most of the pulsars, the theoretical CDF matched the observed values. This is an indication that microglitches in pulsar may be interpreted as an avalanche process in which angular momentum is transferred erratically from the flywheel-like superfliud interior to the slowly decelerating solid crust. Analysis of the waiting time indicates that it is purely Poisson distributed with mean microglitch rate <γ> ∼ 0.98year^−1 for all the pulsars in our sample and <γ> / <∆T> ∼ 1. Correlation analysis, showed that the relative absolute size of microglitch event strongly with the rotation period of the pulsar with correlation coefficient r ∼ 0.7 and r ∼ 0.5 respectively for events in ν and ν˙. The mean glitch rate and number of microglitches (Ng) showed some dependence on spin down rate (r ∼ −0.6) and the characteristic age of the pulsar (τ) with (r ∼ −0.4/− 0.5).

Keywords: method-data analysis, star, neutron-pulsar, general

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2059 Bone Fracture Detection with X-Ray Images Using Mobilenet V3 Architecture

Authors: Ashlesha Khanapure, Harsh Kashyap, Abhinav Anand, Sanjana Habib, Anupama Bidargaddi

Abstract:

Technologies that are developing quickly are being developed daily in a variety of disciplines, particularly the medical field. For the purpose of detecting bone fractures in X-ray pictures of different body segments, our work compares the ResNet-50 and MobileNetV3 architectures. It evaluates accuracy and computing efficiency with X-rays of the elbow, hand, and shoulder from the MURA dataset. Through training and validation, the models are evaluated on normal and fractured images. While ResNet-50 showcases superior accuracy in fracture identification, MobileNetV3 showcases superior speed and resource optimization. Despite ResNet-50’s accuracy, MobileNetV3’s swifter inference makes it a viable choice for real-time clinical applications, emphasizing the importance of balancing computational efficiency and accuracy in medical imaging. We created a graphical user interface (GUI) for MobileNet V3 model bone fracture detection. This research underscores MobileNetV3’s potential to streamline bone fracture diagnoses, potentially revolutionizing orthopedic medical procedures and enhancing patient care.

Keywords: CNN, MobileNet V3, ResNet-50, healthcare, MURA, X-ray, fracture detection

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2058 1D Convolutional Networks to Compute Mel-Spectrogram, Chromagram, and Cochleogram for Audio Networks

Authors: Elias Nemer, Greg Vines

Abstract:

Time-frequency transformation and spectral representations of audio signals are commonly used in various machine learning applications. Training networks on frequency features such as the Mel-Spectrogram or Cochleogram have been proven more effective and convenient than training on-time samples. In practical realizations, these features are created on a different processor and/or pre-computed and stored on disk, requiring additional efforts and making it difficult to experiment with different features. In this paper, we provide a PyTorch framework for creating various spectral features as well as time-frequency transformation and time-domain filter-banks using the built-in trainable conv1d() layer. This allows computing these features on the fly as part of a larger network and enabling easier experimentation with various combinations and parameters. Our work extends the work in the literature developed for that end: First, by adding more of these features and also by allowing the possibility of either starting from initialized kernels or training them from random values. The code is written as a template of classes and scripts that users may integrate into their own PyTorch classes or simply use as is and add more layers for various applications.

Keywords: neural networks Mel-Spectrogram, chromagram, cochleogram, discrete Fourrier transform, PyTorch conv1d()

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2057 Functional Neural Network for Decision Processing: A Racing Network of Programmable Neurons Where the Operating Model Is the Network Itself

Authors: Frederic Jumelle, Kelvin So, Didan Deng

Abstract:

In this paper, we are introducing a model of artificial general intelligence (AGI), the functional neural network (FNN), for modeling human decision-making processes. The FNN is composed of multiple artificial mirror neurons (AMN) racing in the network. Each AMN has a similar structure programmed independently by the users and composed of an intention wheel, a motor core, and a sensory core racing at a specific velocity. The mathematics of the node’s formulation and the racing mechanism of multiple nodes in the network will be discussed, and the group decision process with fuzzy logic and the transformation of these conceptual methods into practical methods of simulation and in operations will be developed. Eventually, we will describe some possible future research directions in the fields of finance, education, and medicine, including the opportunity to design an intelligent learning agent with application in AGI. We believe that FNN has a promising potential to transform the way we can compute decision-making and lead to a new generation of AI chips for seamless human-machine interactions (HMI).

Keywords: neural computing, human machine interation, artificial general intelligence, decision processing

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2056 Evaluation of Energy Supply and Demand Side Management for Residential Buildings in Ekiti State, Nigeria

Authors: Oluwatosin Samuel Adeoye

Abstract:

Ekiti State is an agrarian state located in south western part of Nigeria. The injected power to the Ado-Ekiti and the entire state are 25MW and 37.6 MW respectively. The estimated power demand for Ado Ekiti and Ekiti state were 29.01MW and 224.116MW respectively. The distributed power to the consumers is characterized with shortcomings which include: in-adequate supply, poor voltage regulation, improper usage, illiteracy and wastage. The power generation in Nigeria is presently 1680.60MW which does not match the estimated power demand of 15,000MW with a population of over 170 million citizens. This paper evaluates the energy utilization in Ado Ekiti metropolis, the wastage and its economic implication as well as effective means of its management. The use of direct interviews, administration of questionnaires, measurements of current and voltage with clamp multimeter, and simple mathematical approach were used for the purpose of evaluation. Recommendations were made with the view of reducing energy waste from mean value of 10.84% to 2% in order to reduce the cost implication such that the huge financial waste can be injected to other parts of the economy as well as the management of energy in Ekiti state.

Keywords: consumers, demand, energy, management, power supply, waste

Procedia PDF Downloads 340