Search results for: Michael D. Short
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3487

Search results for: Michael D. Short

3367 Iraqi Short Term Electrical Load Forecasting Based on Interval Type-2 Fuzzy Logic

Authors: Firas M. Tuaimah, Huda M. Abdul Abbas

Abstract:

Accurate Short Term Load Forecasting (STLF) is essential for a variety of decision making processes. However, forecasting accuracy can drop due to the presence of uncertainty in the operation of energy systems or unexpected behavior of exogenous variables. Interval Type 2 Fuzzy Logic System (IT2 FLS), with additional degrees of freedom, gives an excellent tool for handling uncertainties and it improved the prediction accuracy. The training data used in this study covers the period from January 1, 2012 to February 1, 2012 for winter season and the period from July 1, 2012 to August 1, 2012 for summer season. The actual load forecasting period starts from January 22, till 28, 2012 for winter model and from July 22 till 28, 2012 for summer model. The real data for Iraqi power system which belongs to the Ministry of Electricity.

Keywords: short term load forecasting, prediction interval, type 2 fuzzy logic systems, electric, computer systems engineering

Procedia PDF Downloads 368
3366 Groundwater Level Prediction Using hybrid Particle Swarm Optimization-Long-Short Term Memory Model and Performance Evaluation

Authors: Sneha Thakur, Sanjeev Karmakar

Abstract:

This paper proposed hybrid Particle Swarm Optimization (PSO) – Long-Short Term Memory (LSTM) model for groundwater level prediction. The evaluation of the performance is realized using the parameters: root mean square error (RMSE) and mean absolute error (MAE). Ground water level forecasting will be very effective for planning water harvesting. Proper calculation of water level forecasting can overcome the problem of drought and flood to some extent. The objective of this work is to develop a ground water level forecasting model using deep learning technique integrated with optimization technique PSO by applying 29 years data of Chhattisgarh state, In-dia. It is important to find the precise forecasting in case of ground water level so that various water resource planning and water harvesting can be managed effectively.

Keywords: long short-term memory, particle swarm optimization, prediction, deep learning, groundwater level

Procedia PDF Downloads 44
3365 A Critical Discourse Study of Gender Identity Issues in Daniyal Mueenuddin’s Short Story “Saleema”

Authors: Zafar Ali

Abstract:

The aim of this research is to highlight problems that are faced by women at the hands of men. Males in Pakistani society have power and use this power for the exploitation of women. Further, the purpose of the study is to make societies like Pakistan and especially the young generation, aware and enable them to resist such issues, and the role of discourse in this regard is to minimize its political and social repercussions. The study finds out different discursive techniques and manipulative language used in the short story to construct gender identity. The study also investigates socio-economic roles in the construction of gender identity. This study has been completed with the help of Critical Discourse Analysis (CDA) principles. CDA principles have been applied to the text of the selected short story Saleema from Daniyal Mueenuddin’s collection In Other Rooms, Other Wonders. Related passages, structures, expressions, and text are analyzed from the point of view of CDA, especially Norman Fairclough’s CDA approach. It was found from the analysis that women have no identity of their own in patriarchal societies like Pakistan. Further, it was found women are mistreated, and they have a very limited and defined role in Pakistan. They cannot go beyond the limit defined to them by men.

Keywords: gender issues, resourceful groups, CDA, exploitation

Procedia PDF Downloads 99
3364 Solar Powered Front Wheel Drive (FWD) Electric Trike: An Innovation

Authors: Michael C. Barbecho, Romeo B. Morcilla

Abstract:

This study focused on the development of a solar powered front wheel drive electric trike for personal use and short distance travel, utilizing solar power and a variable speed transmission to adapt in places where varying road grades and unavailability of plug-in charging stations are of great problems. The actual performance of the vehicle was measured in terms of duration of charging using solar power, distance travel and battery power duration, top speed developed at full power, and load capacity. This project followed the research and development process which involved planning, designing, construction, and testing. Solar charging tests revealed that the vehicle requires 6 to 8 hours sunlight exposure to fully charge the batteries. At full charge, the vehicle can travel 35 km utilizing battery power down to 42%. Vehicle showed top speed of 25 kph at 0 to 3% road grade carrying a maximum load of 122 kg. The maximum climbing grade was 23% with the vehicle carrying a maximum load of 122 kg. Technically the project was feasible and can be a potential model for possible conversion of traditional Philippine made “pedicabs” and gasoline engine powered tricycle into modern electric vehicles. Moreover, it has several technical features and advantages over a commercialized electric vehicle such as the use solar charging system and variable speed power transmission and front drive power train for adaptability in any road gradient.

Keywords: electric vehicle, solar vehicles, front drive, solar, solar power

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3363 Juxtaposition of the Past and the Present: A Pragmatic Stylistic Analysis of the Short Story “Too Much Happiness” by Alice Munro

Authors: Inas Hussein

Abstract:

Alice Munro is a Canadian short-story writer who has been regarded as one of the greatest writers of fiction. Owing to her great contribution to fiction, she was the first Canadian woman and the only short-story writer ever to be rewarded the Nobel Prize for Literature in 2013. Her literary works include collections of short stories and one book published as a novel. Her stories concentrate on the human condition and the human relationships as seen through the lens of daily life. The setting in most of her stories is her native Canada- small towns much similar to the one where she grew up. Her writing style is not only realistic but is also characterized by autobiographical, historical and regional features. The aim of this research is to analyze one of the key stylistic devices often adopted by Munro in her fictions: the juxtaposition of the past and the present, with reference to the title story in Munro's short story collection Too Much Happiness. The story under exploration is a brief biography of the Russian Mathematician and novelist Sophia Kovalevsky (1850 – 1891), the first woman to be appointed as a professor of Mathematics at a European University in Stockholm. Thus, the story has a historical protagonist and is set on the European continent. Munro dramatizes the severe historical and cultural constraints that hindered the career of the protagonist. A pragmatic stylistic framework is being adopted and the qualitative analysis is supported by textual reference. The stylistic analysis reveals that the juxtaposition of the past and the present is one of the distinctive features that characterize the author; in a typical Munrovian manner, the protagonist often moves between the units of time: the past, the present and, sometimes, the future. Munro's style is simple and direct but cleverly constructed and densely complicated by the presence of deeper layers and stories within the story. Findings of the research reveal that the story under investigation merits reading and analyzing. It is recommended that this story and other stories by Munro are analyzed to further explore the features of her art and style.

Keywords: Alice Munro, Too Much Happiness, style, stylistic analysis

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3362 Reinforced Concrete Box Girder Bridge Hinge Replacement and Horizontal and Vertical Earthquake Restrainers

Authors: Kumars ZandParsa, Quynh Nguyen, Hadi Moradi

Abstract:

There are old cast-in-place concrete box girder bridges in California with inter-span hinges that are designed based on old earthquake codes. Hinge removal is part of the bridges’ earthquake retrofitting project, and hinges were removed and replaced with modified hinges per new earthquake codes. The span that has a hinge is divided into short and long cantilevers in which the short cantilever supports the long cantilever. In the recent bridge hinge replacement, the length of the short and long cantilevers were 20ft and 80ft, respectively. The seat in the new design is wider than the old design, and the horizontal and vertical movements of the deck at the hinge location must be computed to check if restraints are needed. In this paper, besides considering the conventional reinforced concrete box girder bridges, the hinge removal operations, along with the response spectrum analysis based on the El Centro 1940 earthquake, will be presented to verify if vertical and horizontal restrainers are needed.

Keywords: hinge replacement, restrainers, vertical earthquake, response spectrum analysis

Procedia PDF Downloads 527
3361 Short Text Classification for Saudi Tweets

Authors: Asma A. Alsufyani, Maram A. Alharthi, Maha J. Althobaiti, Manal S. Alharthi, Huda Rizq

Abstract:

Twitter is one of the most popular microblogging sites that allows users to publish short text messages called 'tweets'. Increasing the number of accounts to follow (followings) increases the number of tweets that will be displayed from different topics in an unclassified manner in the timeline of the user. Therefore, it can be a vital solution for many Twitter users to have their tweets in a timeline classified into general categories to save the user’s time and to provide easy and quick access to tweets based on topics. In this paper, we developed a classifier for timeline tweets trained on a dataset consisting of 3600 tweets in total, which were collected from Saudi Twitter and annotated manually. We experimented with the well-known Bag-of-Words approach to text classification, and we used support vector machines (SVM) in the training process. The trained classifier performed well on a test dataset, with an average F1-measure equal to 92.3%. The classifier has been integrated into an application, which practically proved the classifier’s ability to classify timeline tweets of the user.

Keywords: corpus creation, feature extraction, machine learning, short text classification, social media, support vector machine, Twitter

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3360 The Effectiveness of Intensive Short-Term Dynamic Psychotherapy on Ambiguity Tolerance, Emotional Intelligence and Stress Coping Strategies in Financial Market Traders

Authors: Ahmadreza Jabalameli, Mohammad Ebrahimpour Borujeni

Abstract:

This study aims to evaluate the effectiveness of intensive short-term dynamic psychotherapy (ISTDP) on ambiguity tolerance, emotional intelligence and stress coping strategies in financial market traders. The methodology of this study was quasi-experimental, pre-test and post-test with control group. The statistical population of this study includes all students at Jabalameli Information Technology Academy in 2022. Among them, 30 people were selected by voluntary sampling through interviews, and were randomly divided into two experimental and control groups of 51 people. And the components were measured according to McLain Ambiguity Tolerance Questionnaire, Bar-On Emotional Intelligence and Lazarus Stress Coping Strategies. The data were obtained by SPSS software and were analyzed by using multivariate analysis of covariance. The results indicate that intensive short-term dynamic psychotherapy influences the emotional intelligence as well as the ambiguity tolerance of traders.

Keywords: ISTDP, ambiguity tolerance, trading, emotional intelligence, stress

Procedia PDF Downloads 52
3359 Characteristics of Silicon Integrated Vertical Carbon Nanotube Field-Effect Transistors

Authors: Jingqi Li

Abstract:

A new vertical carbon nanotube field effect transistor (CNTFET) has been developed. The source, drain and gate are vertically stacked in this structure. The carbon nanotubes are put on the side wall of the vertical stack. Unique transfer characteristics which depend on both silicon type and the sign of drain voltage have been observed in silicon integrated CNTFETs. The significant advantage of this CNTFET is that the short channel of the transistor can be fabricated without using complicate lithography technique.

Keywords: carbon nanotubes, field-effect transistors, electrical property, short channel fabrication

Procedia PDF Downloads 323
3358 Long- and Short-Term Impacts of COVID-19 and Gold Price on Price Volatility: A Comparative Study of MIDAS and GARCH-MIDAS Models for USA Crude Oil

Authors: Samir K. Safi

Abstract:

The purpose of this study was to compare the performance of two types of models, namely MIDAS and MIDAS-GARCH, in predicting the volatility of crude oil returns based on gold price returns and the COVID-19 pandemic. The study aimed to identify which model would provide more accurate short-term and long-term predictions and which model would perform better in handling the increased volatility caused by the pandemic. The findings of the study revealed that the MIDAS model performed better in predicting short-term and long-term volatility before the pandemic, while the MIDAS-GARCH model performed significantly better in handling the increased volatility caused by the pandemic. The study highlights the importance of selecting appropriate models to handle the complexities of real-world data and shows that the choice of model can significantly impact the accuracy of predictions. The practical implications of model selection and exploring potential methodological adjustments for future research will be highlighted and discussed.

Keywords: GARCH-MIDAS, MIDAS, crude oil, gold, COVID-19, volatility

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3357 Deep Graph Embeddings for the Analysis of Short Heartbeat Interval Time Series

Authors: Tamas Madl

Abstract:

Sudden cardiac death (SCD) constitutes a large proportion of cardiovascular mortalities, provides little advance warning, and the risk is difficult to recognize based on ubiquitous, low cost medical equipment such as the standard, 12-lead, ten second ECG. Autonomic abnormalities have been shown to be strongly predictive of SCD risk; yet current methods are not trivially applicable to the brevity and low temporal and electrical resolution of standard ECGs. Here, we build horizontal visibility graph representations of very short inter-beat interval time series, and perform unsuper- vised representation learning in order to convert these variable size objects into fixed-length vectors preserving similarity rela- tions. We show that such representations facilitate classification into healthy vs. at-risk patients on two different datasets, the Mul- tiparameter Intelligent Monitoring in Intensive Care II and the PhysioNet Sudden Cardiac Death Holter Database. Our results suggest that graph representation learning of heartbeat interval time series facilitates robust classification even in sequences as short as ten seconds.

Keywords: sudden cardiac death, heart rate variability, ECG analysis, time series classification

Procedia PDF Downloads 207
3356 Silencing in Urdu Resistance Literature: A Postcolonial Study of the Short Fiction Written between 1977 and 1988

Authors: Muhammad Sheeraz

Abstract:

Literary responses to various forms of local and international oppressions can be found in all major Pakistani languages and their academic study is crucial to understand the local creative and critical mind. However, most of them have not yet received as much of scholarly attention as has the Anglophone Pakistani literature of this kind. One of the reasons for this indifference is that resistance literature is usually mistaken as incidental work produced in haste and thus not a serious subject or high art worthy of being considered critically. Literary criticism in the English language did not include this Urdu resistance literature because most of it has not yet been translated into English, and scholars proficient in Urdu and producing critical works in English have contented themselves to the critique of a few prominent writers of Urdu, for instance, Faiz Ahmad Faiz and Saadat Hassan Manto. While there is no denying the fact that they hold a significant position in Pakistani literature, the tradition of resistance is in no way limited to them. Bringing to the limelight other resistant voices from Urdu fiction, this qualitative research employs Barbara Harlow’s framework of postcolonial resistance literature to explore the strategy of silencing as used in twenty three short stories written between the military regime of Zia ul Haq (1977-1988) in Pakistan. The study shows that the writers of these Urdu short stories have not only recorded various tools of silencing employed by the oppressors but also represented various kinds of silences that were observed in the society. Moreover, they have also depicted how this silencing was dealt with by the writers and intellectual of the time. Thus, in the light of the analysis, it can be safely said that Urdu resistance literature notices, recounts, and theorizes silencing and silences within the local sociopolitical condition.

Keywords: resistance literature, Urdu short fiction, Zia ul Haq, postcolonialism

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3355 Dynamic Effects of Energy Consumption, Economic Growth, International Trade and Urbanization on Environmental Degradation in Nigeria

Authors: Abdulkarim Yusuf

Abstract:

Motivation: A crucial but difficult goal for governments and policymakers in Nigeria in recent years has been the sustainability of economic growth. This goal must be accomplished by regulating or lowering greenhouse gas emissions, which calls for switching to a low- or zero-carbon production system. The lack of in-depth empirical studies on the environmental impact of socioeconomic variables on Nigeria and a number of unresolved issues from earlier research is what led to the current study. Objective: This study fills an important empirical gap by investigating the existence of an Environmental Kuznets Curve hypothesis and the long and short-run dynamic impact of socioeconomic variables on ecological sustainability in Nigeria. Data and method: Annual time series data covering the period 1980 to 2020 and the Autoregressive Distributed Lag technique in the presence of structural breaks were adopted for this study. Results: The empirical findings support the existence of the environmental Kuznets curve hypothesis for Nigeria in the long and short run. Energy consumption and total import exacerbate environmental deterioration in the long and short run, whereas total export improves environmental quality in the long and short run. Financial development, which contributed to a conspicuous decrease in the level of environmental destruction in the long run, escalated it in the short run. In contrast, urbanization caused a significant increase in environmental damage in the long run but motivated a decrease in biodiversity loss in the short run. Implications: The government, policymakers, and all energy stakeholders should take additional measures to ensure the implementation and diversification of energy sources to accommodate more renewable energy sources that emit less carbon in order to promote efficiency in Nigeria's production processes and lower carbon emissions. In order to promote the production and trade of environmentally friendly goods, they should also revise and strengthen environmental policies. With affordable, dependable, and sustainable energy use for higher productivity and inclusive growth, Nigeria will be able to achieve its long-term development goals of good health and wellbeing.

Keywords: economic growth, energy consumption, environmental degradation, environmental Kuznets curve, urbanization, Nigeria

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3354 Evaluating Performance of Value at Risk Models for the MENA Islamic Stock Market Portfolios

Authors: Abderrazek Ben Maatoug, Ibrahim Fatnassi, Wassim Ben Ayed

Abstract:

In this paper we investigate the issue of market risk quantification for Middle East and North Africa (MENA) Islamic market equity. We use Value-at-Risk (VaR) as a measure of potential risk in Islamic stock market, for long and short position, based on Riskmetrics model and the conditional parametric ARCH class model volatility with normal, student and skewed student distribution. The sample consist of daily data for the 2006-2014 of 11 Islamic stock markets indices. We conduct Kupiec and Engle and Manganelli tests to evaluate the performance for each model. The main finding of our empirical results show that (i) the superior performance of VaR models based on the Student and skewed Student distribution, for the significance level of α=1% , for all Islamic stock market indices, and for both long and short trading positions (ii) Risk Metrics model, and VaR model based on conditional volatility with normal distribution provides the best accurate VaR estimations for both long and short trading positions for a significance level of α=5%.

Keywords: value-at-risk, risk management, islamic finance, GARCH models

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3353 The Relationships between Energy Consumption, Carbon Dioxide (CO2) Emissions, and GDP for Turkey: Time Series Analysis, 1980-2010

Authors: Jinhoa Lee

Abstract:

The relationships between environmental quality, energy use and economic output have created growing attention over the past decades among researchers and policy makers. Focusing on the empirical aspects of the role of carbon dioxide (CO2) emissions and energy use in affecting the economic output, this paper is an effort to fulfill the gap in a comprehensive case study at a country level using modern econometric techniques. To achieve the goal, this country-specific study examines the short-run and long-run relationships among energy consumption (using disaggregated energy sources: crude oil, coal, natural gas, and electricity), CO2 emissions and gross domestic product (GDP) for Turkey using time series analysis from the year 1980-2010. To investigate the relationships between the variables, this paper employs the Augmented Dickey-Fuller (ADF) test for stationarity, Johansen’s maximum likelihood method for cointegration and a Vector Error Correction Model (VECM) for both short- and long-run causality among the research variables for the sample. The long-run equilibrium in the VECM suggests no effects of the CO2 emissions and energy use on the GDP in Turkey. There exists a short-run bidirectional relationship between the electricity and natural gas consumption, and also there is a negative unidirectional causality running from the GDP to electricity use. Overall, the results partly support arguments that there are relationships between energy use and economic output; however, the effects may differ due to the source of energy such as in the case of Turkey for the period of 1980-2010. However, there is no significant relationship between the CO2 emissions and the GDP and between the CO2 emissions and the energy use both in the short term and long term.

Keywords: CO2 emissions, energy consumption, GDP, Turkey, time series analysis

Procedia PDF Downloads 485
3352 Studying the Impact of Agricultural Producers Support Policy in Export Market

Authors: Yazdani Saeed, Rafiei Hamed, Nekoofar Farahnaz

Abstract:

Governments Policies play a major role in national and international Markets. Pistachio is one of the most important non-oil export commodity of Iran. Therefore, in this study the relation between the producer support policies and the export of Pistachio was examined. An econometric model (VAR) was applied to test the study hypothesis. According to the estimated coefficient in VAR model, lag of producer support index has a significant and negative effect on variation of Pistachio’s export in short term. In other word, in short term, export advantage index is dependent on the amount of producers support in previous period.

Keywords: producer support, export advantage, pistachio, Iran

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3351 Design and Implementation of Machine Learning Model for Short-Term Energy Forecasting in Smart Home Management System

Authors: R. Ramesh, K. K. Shivaraman

Abstract:

The main aim of this paper is to handle the energy requirement in an efficient manner by merging the advanced digital communication and control technologies for smart grid applications. In order to reduce user home load during peak load hours, utility applies several incentives such as real-time pricing, time of use, demand response for residential customer through smart meter. However, this method provides inconvenience in the sense that user needs to respond manually to prices that vary in real time. To overcome these inconvenience, this paper proposes a convolutional neural network (CNN) with k-means clustering machine learning model which have ability to forecast energy requirement in short term, i.e., hour of the day or day of the week. By integrating our proposed technique with home energy management based on Bluetooth low energy provides predicted value to user for scheduling appliance in advanced. This paper describes detail about CNN configuration and k-means clustering algorithm for short-term energy forecasting.

Keywords: convolutional neural network, fuzzy logic, k-means clustering approach, smart home energy management

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3350 Internal DC Short-Circuit Fault Analysis and Protection for VSI of Wind Power Generation Systems

Authors: Mehdi Radmehr, Amir Hamed Mashhadzadeh, Mehdi Jafari

Abstract:

Traditional HVDC systems are tough to DC short circuits as they are current regulated with a large reactance connected in series with cables. Multi-terminal DC wind farm topologies are attracting increasing research attempt. With AC/DC converters on the generator side, this topology can be developed into a multi-terminal DC network for wind power collection, which is especially suitable for large-scale offshore wind farms. For wind farms, the topology uses high-voltage direct-current transmission based on voltage-source converters (VSC-HVDC). Therefore, they do not suffer from over currents due to DC cable faults and there is no over current to react to. In this study, the multi-terminal DC wind farm topology is introduced. Then, possible internal DC faults are analyzed according to type and characteristic. Fault over current expressions are given in detail. Under this characteristic analysis, fault detection and detailed protection methods are proposed. Theoretical analysis and PSCAD/EMTDC simulations are provided.

Keywords: DC short circuits, multi-terminal DC wind farm topologies, HVDC transmission based on VSC, fault analysis

Procedia PDF Downloads 395
3349 A Methodology for Characterising the Tail Behaviour of a Distribution

Authors: Serge Provost, Yishan Zang

Abstract:

Following a review of various approaches that are utilized for classifying the tail behavior of a distribution, an easily implementable methodology that relies on an arctangent transformation is presented. The classification criterion is actually based on the difference between two specific quantiles of the transformed distribution. The resulting categories enable one to classify distributional tails as distinctly short, short, nearly medium, medium, extended medium and somewhat long, providing that at least two moments exist. Distributions possessing a single moment are said to be long tailed while those failing to have any finite moments are classified as having an extremely long tail. Several illustrative examples will be presented.

Keywords: arctangent transformation, tail classification, heavy-tailed distributions, distributional moments

Procedia PDF Downloads 89
3348 Modeling Spillover Effects of Pakistan-India Bilateral Trade upon Sustainability of Economic Growth in Pakistan

Authors: Taimoor Hussain Alvi, Syed Toqueer Akhter

Abstract:

The focus of this research is to identify Pak-India bilateral trade spillover effects upon Pakistan’s Growth rate. Cross-country spillover growth Effects have been linked with openness and access to markets. In this research, we intend to see the short run and long run effects of Pak-India Bilateral Trade Openness upon economic growth in Pakistan. Trade Openness has been measured as the sum of bilateral exports and imports between the two countries. Increased emphasis on the condition and environment of financial markets is laid in light of globalization and trade liberalization. This research paper makes use of the Univariate Autoregressive Distributed Lagged Model to analyze the effects of bilateral trade variables upon the growth pattern of Pakistan in the short run and long run. Key findings of the study empirically support the notion that increased bilateral trade will be beneficial for Pakistan in the short run because of cost advantage and knowledge spillover in terms of increased technical and managerial ability from multinational firms. However, contrary to extensive literature, increased bilateral trade measures will affect Pakistan’s growth rate negatively in the long run because of the industrial size differential and increased integration of Indian economy with the world.

Keywords: bilateral trade openness, spillover, comparative advantage, univariate

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3347 Bidirectional Long Short-Term Memory-Based Signal Detection for Orthogonal Frequency Division Multiplexing With All Index Modulation

Authors: Mahmut Yildirim

Abstract:

This paper proposed the bidirectional long short-term memory (Bi-LSTM) network-aided deep learning (DL)-based signal detection for Orthogonal frequency division multiplexing with all index modulation (OFDM-AIM), namely Bi-DeepAIM. OFDM-AIM is developed to increase the spectral efficiency of OFDM with index modulation (OFDM-IM), a promising multi-carrier technique for communication systems beyond 5G. In this paper, due to its strong classification ability, Bi-LSTM is considered an alternative to the maximum likelihood (ML) algorithm, which is used for signal detection in the classical OFDM-AIM scheme. The performance of the Bi-DeepAIM is compared with LSTM network-aided DL-based OFDM-AIM (DeepAIM) and classic OFDM-AIM that uses (ML)-based signal detection via BER performance and computational time criteria. Simulation results show that Bi-DeepAIM obtains better bit error rate (BER) performance than DeepAIM and lower computation time in signal detection than ML-AIM.

Keywords: bidirectional long short-term memory, deep learning, maximum likelihood, OFDM with all index modulation, signal detection

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3346 Mixed Effects Models for Short-Term Load Forecasting for the Spanish Regions: Castilla-Leon, Castilla-La Mancha and Andalucia

Authors: C. Senabre, S. Valero, M. Lopez, E. Velasco, M. Sanchez

Abstract:

This paper focuses on an application of linear mixed models to short-term load forecasting. The challenge of this research is to improve a currently working model at the Spanish Transport System Operator, programmed by us, and based on linear autoregressive techniques and neural networks. The forecasting system currently forecasts each of the regions within the Spanish grid separately, even though the behavior of the load in each region is affected by the same factors in a similar way. A load forecasting system has been verified in this work by using the real data from a utility. In this research it has been used an integration of several regions into a linear mixed model as starting point to obtain the information from other regions. Firstly, the systems to learn general behaviors present in all regions, and secondly, it is identified individual deviation in each regions. The technique can be especially useful when modeling the effect of special days with scarce information from the past. The three most relevant regions of the system have been used to test the model, focusing on special day and improving the performance of both currently working models used as benchmark. A range of comparisons with different forecasting models has been conducted. The forecasting results demonstrate the superiority of the proposed methodology.

Keywords: short-term load forecasting, mixed effects models, neural networks, mixed effects models

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3345 Cement Mortar Lining as a Potential Source of Water Contamination

Authors: M. Zielina, W. Dabrowski, E. Radziszewska-Zielina

Abstract:

Several different cements have been tested to evaluate their potential to leach calcium, chromium and aluminum ions in soft water environment. The research allows comparing some different cements in order to the potential risk of water contamination. This can be done only in the same environment. To reach the results in reasonable short time intervals and to make heavy metals measurements with high accuracy, demineralized water was used. In this case the conditions of experiments are far away from the water supply practice, but short time experiments and measurably high concentrations of elements in the water solution are an important advantage. Moreover leaching mechanisms can be recognized, our experiments reported here refer to this kind of cements evaluation.

Keywords: concrete corrosion, hydrogen sulfide, odors, reinforced concrete sewers, sewerage

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3344 Development of a Telemedical Network Supporting an Automated Flow Cytometric Analysis for the Clinical Follow-up of Leukaemia

Authors: Claude Takenga, Rolf-Dietrich Berndt, Erling Si, Markus Diem, Guohui Qiao, Melanie Gau, Michael Brandstoetter, Martin Kampel, Michael Dworzak

Abstract:

In patients with acute lymphoblastic leukaemia (ALL), treatment response is increasingly evaluated with minimal residual disease (MRD) analyses. Flow Cytometry (FCM) is a fast and sensitive method to detect MRD. However, the interpretation of these multi-parametric data requires intensive operator training and experience. This paper presents a pipeline-software, as a ready-to-use FCM-based MRD-assessment tool for the daily clinical practice for patients with ALL. The new tool increases accuracy in assessment of FCM-MRD in samples which are difficult to analyse by conventional operator-based gating since computer-aided analysis potentially has a superior resolution due to utilization of the whole multi-parametric FCM-data space at once instead of step-wise, two-dimensional plot-based visualization. The system developed as a telemedical network reduces the work-load and lab-costs, staff-time needed for training, continuous quality control, operator-based data interpretation. It allows dissemination of automated FCM-MRD analysis to medical centres which have no established expertise for the benefit of an even larger community of diseased children worldwide. We established a telemedical network system for analysis and clinical follow-up and treatment monitoring of Leukaemia. The system is scalable and adapted to link several centres and laboratories worldwide.

Keywords: data security, flow cytometry, leukaemia, telematics platform, telemedicine

Procedia PDF Downloads 940
3343 A Comparative Analysis of Global Minimum Variance and Naïve Portfolios: Performance across Stock Market Indices and Selected Economic Regimes Using Various Risk-Return Metrics

Authors: Lynmar M. Didal, Ramises G. Manzano Jr., Jacque Bon-Isaac C. Aboy

Abstract:

This study analyzes the performance of global minimum variance and naive portfolios across different economic periods, using monthly stock returns from the Philippine Stock Exchange Index (PSEI), S&P 500, and Dow Jones Industrial Average (DOW). The performance is evaluated through the Sharpe ratio, Sortino ratio, Jensen’s Alpha, Treynor ratio, and Information ratio. Additionally, the study investigates the impact of short selling on portfolio performance. Six-time periods are defined for analysis, encompassing events such as the global financial crisis and the COVID-19 pandemic. Findings indicate that the Naive portfolio generally outperforms the GMV portfolio in the S&P 500, signifying higher returns with increased volatility. Conversely, in the PSEI and DOW, the GMV portfolio shows more efficient risk-adjusted returns. Short selling significantly impacts the GMV portfolio during mid-GFC and mid-COVID periods. The study offers insights for investors, suggesting the Naive portfolio for higher risk tolerance and the GMV portfolio as a conservative alternative.

Keywords: portfolio performance, global minimum variance, naïve portfolio, risk-adjusted metrics, short-selling

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3342 Approach to Establish Logistics as a Central Scientific Discipline of Tomorrow's Industry

Authors: Johannes Dregger, Michael Schmidt, Christian Prasse, Michael ten Hompel

Abstract:

Most of the today’s companies face increasing need to operate efficiently. Driven by global trends like shorter product cycles, mass customization and the rising speed of delivery, manufacturing value chains are becoming more and more distributed. Manufacturing processes are becoming highly integrated, e.g. 3D printing. All these changes are affecting companies´ organization. They are leading towards individual, small scale, and ad-hoc logistics processes and structures, and finally, towards a significant increase in the importance of logistics itself since traditional value chains transform into agile value networks. In the past logistics has been following manufacturing but in the future industry, this role allocation might change. With this increase in the logistics practice of companies and businesses, the relevance of logistics research as the methodological foundation of logistics networks and processes is gaining importance. Logistics research is evolving into a central and highly interdisciplinary science for the future industry. Using the example of Germany, this paper discusses ways to establish logistics as a central scientific discipline of the future industry. About three million people work in the logistics sector in Germany. Only automotive and retail industry have more employees. Even though there is a bunch of logistics degree programs at more than 100 institutions of higher education, a common understanding of logistics as a research discipline is missing. In this paper an innovative approach will be presented, including; identified perspectives on logistics, such as process orientation, IT orientation or employees orientation, relevant scientific disciplines for logistics science, a concept for interdisciplinary research approaches to unify the perspectives of the different scientific disciplines on logistics and the methodological base of logistics science.

Keywords: logistics, logistics science, logistics management, future challenges

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3341 The Financial and Metallurgical Benefits of Niobium Grain Refined As-Rolled 460 MPa H-Beam to the Construction Industry in SE Asia

Authors: Michael Wright, Tiago Costa

Abstract:

The construction industry in SE Asia has been relying on S355 MPa “as rolled” H-beams for many years now. It is an easily sourced, metallurgically simple, reliable product that all designers, fabricators and constructors are familiar with. However, as the Global demand to better use our finite resources gets stronger, the need for an as-rolled S460 MPa H-Beam is becoming more apparent. The Financial benefits of an “as-rolled” S460 MPa H-beam are obvious. The S460 MPa beam which is currently available and used is fabricated from rolled strip. However, making H-beam from 3 x 460 MPa strips requires costly equipment, valuable welding skills & production time, all of which can be in short supply or better used for other purposes. The Metallurgical benefits of an “as-rolled” S460 MPa H-beam are consistency in the product. Fabricated H-beams have inhomogeneous areas where the strips have been welded together - parent metal, heat affected zone and weld metal all in the one body. They also rely heavily on the skill of the welder to guarantee a perfect, defect free weld. If this does not occur, the beam is intrinsically flawed and could lead to failure in service. An as-rolled beam is a relatively homogenous product, with the optimum strength and ductility produced by delivering steel with as fine as possible uniform cross sectional grain size. This is done by cost effective alloy design coupled with proper metallurgical process control implemented into an existing mill’s equipment capability and layout. This paper is designed to highlight the benefits of bring an “as-rolled” S460 MPa H-beam to the construction market place in SE Asia, and hopefully encourage the current “as-rolled” H-beam producers to rise to the challenge and produce an innovative high quality product for the local market.

Keywords: fine grained, As-rolled, long products, process control, metallurgy

Procedia PDF Downloads 273
3340 By-Line Analysis of Determinants Insurance Premiums : Evidence from Tunisian Market

Authors: Nadia Sghaier

Abstract:

In this paper, we aim to identify the determinants of the life and non-life insurance premiums of different lines for the case of the Tunisian insurance market over a recent period from 1997 to 2019. The empirical analysis is conducted using the linear cointegration techniques in the panel data framework, which allow both long and short-run relationships. The obtained results show evidence of long-run relationship between premiums, losses, and financial variables (stock market indices and interest rate). Furthermore, we find that the short-run effect of explanatory variables differs across lines. This finding has important implications for insurance tarification and regulation.

Keywords: insurance premiums, lines, Tunisian insurance market, cointegration approach in panel data

Procedia PDF Downloads 155
3339 Effect of Short Chain Alcohols on Bending Rigidity of Lipid Bilayer

Authors: Buti Suryabrahmam, V. A. Raghunathan

Abstract:

We study the effect of short chain alcohols on mechanical properties of saturated lipid bilayers in the fluid phase. The Bending rigidity of 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC) membrane was measured at 28 °C by employing Vesicle Fluctuation Analysis technique. The concentration and chain length (n) of alcohol in the buffer solution were varied from 0 to 1.5 M and from 2 to 8 respectively. We observed a non-linear reduction in the bending rigidity from ~17×10⁻²⁰ J to ~10×10⁻²⁰ J, for all chain lengths of alcohols used in our experiment. We observed approximately three orders of the concentration difference between ethanol and octanol, to show the similar reduction in the bending values. We attribute this phenomenon to thinning of the bilayer due to the adsorption of alcohols at the bilayer-water interface.

Keywords: alcohols, bending rigidity, DMPC, lipid bilayers

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3338 Development of Long and Short Range Ordered Domains in a High Specific Strength Steel

Authors: Nikhil Kumar, Aparna Singh

Abstract:

Microstructural development when annealed at different temperatures in a high aluminum and manganese light weight steel has been examined. The FCC matrix of the manganese (Mn)-rich and nickel (Ni)-rich areas in the studied Fe-Mn-Al-Ni-C-light weight steel have been found to contain anti phase domains. In the Mn-rich region short order range of domains manifested by the diffuse scattering in the electron diffraction patterns was observed. Domains in the Ni-rich region were found to be arranged periodically validated through lattice imaging. The nature of these domains can be tuned with annealing temperature resulting in profound influence in the mechanical properties.

Keywords: Anti-phase domain boundaries, BCC, FCC, Light Weight Steel

Procedia PDF Downloads 109