Search results for: multivariate time series
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 19960

Search results for: multivariate time series

19060 Optimization of Electric Vehicle (EV) Charging Station Allocation Based on Multiple Data - Taking Nanjing (China) as an Example

Authors: Yue Huang, Yiheng Feng

Abstract:

Due to the global pressure on climate and energy, many countries are vigorously promoting electric vehicles and building charging (public) charging facilities. Faced with the supply-demand gap of existing electric vehicle charging stations and unreasonable space usage in China, this paper takes the central city of Nanjing as an example, establishes a site selection model through multivariate data integration, conducts multiple linear regression SPSS analysis, gives quantitative site selection results, and provides optimization models and suggestions for charging station layout planning.

Keywords: electric vehicle, charging station, allocation optimization, urban mobility, urban infrastructure, nanjing

Procedia PDF Downloads 83
19059 Low SPOP Expression and High MDM2 expression Are Associated with Tumor Progression and Predict Poor Prognosis in Hepatocellular Carcinoma

Authors: Chang Liang, Weizhi Gong, Yan Zhang

Abstract:

Purpose: Hepatocellular carcinoma (HCC) is a malignant tumor with a high mortality rate and poor prognosis worldwide. Murine double minute 2 (MDM2) regulates the tumor suppressor p53, increasing cancer risk and accelerating tumor progression. Speckle-type POX virus and zinc finger protein (SPOP), a key of subunit of Cullin-Ring E3 ligase, inhibits tumor genesis and progression by the ubiquitination of its downstream substrates. This study aimed to clarify whether SPOP and MDM2 are mutually regulated in HCC and the correlation between SPOP and MDM2 and the prognosis of HCC patients. Methods: First, the expression of SPOP and MDM2 in HCC tissues were detected by TCGA database. Then, 53 paired samples of HCC tumor and adjacent tissues were collected to evaluate the expression of SPOP and MDM2 using immunohistochemistry. Chi-square test or Fisher’s exact test were used to analyze the relationship between clinicopathological features and the expression levels of SPOP and MDM2. In addition, Kaplan‒Meier curve analysis and log-rank test were used to investigate the effects of SPOP and MDM2 on the survival of HCC patients. Last, the Multivariate Cox proportional risk regression model analyzed whether the different expression levels of SPOP and MDM2 were independent risk factors for the prognosis of HCC patients. Results: Bioinformatics analysis revealed the low expression of SPOP and high expression of MDM2 were related to worse prognosis of HCC patients. The relationship between the expression of SPOP and MDM2 and tumor stem-like features showed an opposite trend. The immunohistochemistry showed the expression of SPOP protein was significantly downregulated while MDM2 protein significantly upregulated in HCC tissue compared to that in para-cancerous tissue. Tumors with low SPOP expression were related to worse T stage and Barcelona Clinic Liver Cancer (BCLC) stage, but tumors with high MDM2 expression were related to worse T stage, M stage, and BCLC stage. Kaplan–Meier curves showed HCC patients with high SPOP expression and low MDM2 expression had better survival than those with low SPOP expression and high MDM2 expression (P < 0.05). A multivariate Cox proportional risk regression model confirmed that a high MDM2 expression level was an independent risk factor for poor prognosis in HCC patients (P <0.05). Conclusion: The expression of SPOP protein was significantly downregulated, while the expression of MDM2 significantly upregulated in HCC. The low expression of SPOP and high expression. of MDM2 were associated with malignant progression and poor prognosis of HCC patients, indicating a potential therapeutic target for HCC patients.

Keywords: hepatocellular carcinoma, murine double minute 2, speckle-type POX virus and zinc finger protein, ubiquitination

Procedia PDF Downloads 130
19058 Existence and Uniqueness of Solutions to Singular Higher Order Two-Point BVPs on Time Scales

Authors: Zhenjie Liu

Abstract:

This paper investigates the existence and uniqueness of solutions for singular higher order boundary value problems on time scales by using mixed monotone method. The theorems obtained are very general. For the different time scale, the problem may be the corresponding continuous or discrete boundary value problem.

Keywords: mixed monotone operator, boundary value problem, time scale, green's function, positive solution, singularity

Procedia PDF Downloads 247
19057 Study on Measuring Method and Experiment of Arc Fault Detection Device

Authors: Yang Jian-Hong, Zhang Ren-Cheng, Huang Li

Abstract:

Arc fault is one of the main inducements of electric fires. Arc Fault Detection Device (AFDD) can detect arc fault effectively. Arc fault detections and unhooking standards are the keys to AFDD practical application. First, an arc fault continuous production system was developed, which could count the arc half wave number. Then, Combining with the UL1699 standard, ignition probability curve of cotton and unhooking time of various currents intensity were obtained by experiments. The combustion degree of arc fault could be expressed effectively by arc area. Experiments proved that electric fires would be misjudged or missed only using arc half wave number as AFDD unhooking basis. At last, Practical tests were carried out on the self-developed AFDD system. The result showed that actual AFDD unhooking time was the sum of arc half wave cycling number, Arc wave identification time and unhooking mechanical operation time And the first two shared shorter time. Unhooking time standard depended on the shortest mechanical operation time.

Keywords: arc fault detection device, arc area, arc half wave, unhooking time, arc fault

Procedia PDF Downloads 494
19056 Aptian Ramp Sedimentation of the Jebel Serdj Massif, North-Central Tunisia, and Sea Level Variations Recorded in Magnetic Susceptibility

Authors: Houda Khaled, Fredj Chaabani, Frederic Boulvain

Abstract:

The Aptian series in north-central Tunisia was studied in detail regarding to lithology, microfacies, and magnetic susceptibility to provide new insights into the paleoenvironmental evolution and sea level changes in the carbonate platform. The study series is about 350 meters thick, and it consists of fives sequences of limestones, separated by four levels of marlstones and marly limestones. Petrographic study leads to the definition of 11 microfacies which are successively recorded along the Serdj section into the outer ramp, mid-ramp, inner ramp and coastal facies associations. The magnetic susceptibility of all samples was measured and compared with the facies and microfacies. There is a clear link between facies and magnetic susceptibility; the distal facies show high values while the proximal areas show lower values. The magnetic susceptibility profile reflects stratigraphic variations in response to relative changes in sea level and input of detrital materials. During the Aptian, kaolinite/illite intensity ratios show high values possibly indicating a warming trend followed then by decreasing values that may indicate a cooling trend. During the Albian, this cooling trend is reverted into humid/warming.

Keywords: Aptian, mineralogy, petrology, Serdj massif

Procedia PDF Downloads 350
19055 Multivariate Analysis of Students’ Performance in Math Courses and Specific Engineering Courses

Authors: H. Naccache, R. Hleiss

Abstract:

The aim of this research is to study the relationship between the performance of engineering students in different math courses and their performance in specific engineering courses. The considered courses are taken mainly by engineering students during the first two years of their major. Several factors are being studied, such as gender and final grades in the math and specific engineering courses. Participants of this study comprised a sample of more than thousands of engineering students at Lebanese University during their tertiary academic years. A significant relationship tends to appear between these factors and the performance of students in engineering courses. Moreover, female students appear to outperform their male counterparts in both the math and engineering courses, and a high correlation was found between their grades in math courses and their grades in specific engineering courses. The results and implications of the study were being discussed.

Keywords: education, engineering, math, performance

Procedia PDF Downloads 332
19054 Chemical Composition of Volatiles Emitted from Ziziphus jujuba Miller Collected during Different Growth Stages

Authors: Rose Vanessa Bandeira Reidel, Bernardo Melai, Pier Luigi Cioni, Luisa Pistelli

Abstract:

Ziziphus jujuba Miller is a common species of the Ziziphus genus (Rhamnaceae family) native to the tropics and subtropics known for its edible fruits, fresh consumed or used in healthy food, as flavoring and sweetener. Many phytochemicals and biological activities are described for this species. In this work, the aroma profiles emitted in vivo by whole fresh organs (leaf, bud flower, flower, green and red fruits) were analyzed separately by mean of solid phase micro-extraction (SPME) coupled with gas chromatography mass spectrometry (GC-MS). The emitted volatiles from different plant parts were analysed using Supelco SPME device coated with polydimethylsiloxane (PDMS, 100µm). Fresh plant material was introduced separately into a glass conical flask and allowed to equilibrate for 20 min. After the equilibration time, the fibre was exposed to the headspace for 15 min at room temperature, the fibre was re-inserted into the needle and transferred to the injector of the CG and CG-MS system, where the fibre was desorbed. All the data were submitted to multivariate statistical analysis, evidencing many differences amongst the selected plant parts and their developmental stages. A total of 144 compounds were identified corresponding to 94.6-99.4% of the whole aroma profile of jujube samples. Sesquiterpene hydrocarbons were the main chemical class of compounds in leaves also present in similar percentage in flowers and bud flowers where (E, E)-α-farnesene was the main constituent in all cited plant parts. This behavior can be due to a protection mechanism against pathogens and herbivores as well as resistance to abiotic factors. The aroma of green fruits was characterized by high amount of perillene while the red fruits release a volatile blend mainly constituted by different monoterpenes. The terpenoid emission of flesh fruits has important function in the interaction with animals including attraction of seed dispersers and it is related to a good quality of fruits. This study provides for the first time the chemical composition of the volatile emission from different Ziziphus jujuba organs. The SPME analyses of the collected samples showed different patterns of emission and can contribute to understand their ecological interactions and fruit production management.

Keywords: Rhamnaceae, aroma profile, jujube organs, HS-SPME, GC-MS

Procedia PDF Downloads 243
19053 Optimal Solutions for Real-Time Scheduling of Reconfigurable Embedded Systems Based on Neural Networks with Minimization of Power Consumption

Authors: Ghofrane Rehaiem, Hamza Gharsellaoui, Samir Benahmed

Abstract:

In this study, Artificial Neural Networks (ANNs) were used for modeling the parameters that allow the real-time scheduling of embedded systems under resources constraints designed for real-time applications running. The objective of this work is to implement a neural networks based approach for real-time scheduling of embedded systems in order to handle real-time constraints in execution scenarios. In our proposed approach, many techniques have been proposed for both the planning of tasks and reducing energy consumption. In fact, a combination of Dynamic Voltage Scaling (DVS) and time feedback can be used to scale the frequency dynamically adjusting the operating voltage. Indeed, we present in this paper a hybrid contribution that handles the real-time scheduling of embedded systems, low power consumption depending on the combination of DVS and Neural Feedback Scheduling (NFS) with the energy Priority Earlier Deadline First (PEDF) algorithm. Experimental results illustrate the efficiency of our original proposed approach.

Keywords: optimization, neural networks, real-time scheduling, low-power consumption

Procedia PDF Downloads 359
19052 River Stage-Discharge Forecasting Based on Multiple-Gauge Strategy Using EEMD-DWT-LSSVM Approach

Authors: Farhad Alizadeh, Alireza Faregh Gharamaleki, Mojtaba Jalilzadeh, Houshang Gholami, Ali Akhoundzadeh

Abstract:

This study presented hybrid pre-processing approach along with a conceptual model to enhance the accuracy of river discharge prediction. In order to achieve this goal, Ensemble Empirical Mode Decomposition algorithm (EEMD), Discrete Wavelet Transform (DWT) and Mutual Information (MI) were employed as a hybrid pre-processing approach conjugated to Least Square Support Vector Machine (LSSVM). A conceptual strategy namely multi-station model was developed to forecast the Souris River discharge more accurately. The strategy used herein was capable of covering uncertainties and complexities of river discharge modeling. DWT and EEMD was coupled, and the feature selection was performed for decomposed sub-series using MI to be employed in multi-station model. In the proposed feature selection method, some useless sub-series were omitted to achieve better performance. Results approved efficiency of the proposed DWT-EEMD-MI approach to improve accuracy of multi-station modeling strategies.

Keywords: river stage-discharge process, LSSVM, discrete wavelet transform, Ensemble Empirical Decomposition Mode, multi-station modeling

Procedia PDF Downloads 169
19051 Gastrointestinal Basidiobolomycosis in a Tertiary Care Center at Saudi Arabia, Makkah: Case Series

Authors: Yaser Meeralam, Walaa Alharthi, Hadeel Ashi, Alaa Bakhsh, Kholood Aljabri, Ebtihal Bin Salim

Abstract:

Background:Basidiobolusranrum causes one of the rare fungal diseases that infects mainly immunocompetent individuals. Gastrointestinal Basidiobolomycosis (GIB) is a rare and uncommon form of this fungal infection. It’s still ambiguous how this fungus is reaching the gastrointestinal tract leading to Gastrointestinal Basidiobolomycosis. Objective: To summarize the clinical features, imaging, and histopathological of patients diagnosed with GIB in our institution. Patients and methods: A series of five cases of patients who diagnosed by basidiobolomycosis in King Abdullah Medical City, Makkah, Saudi Arabia, which reviewed by latest literature related to diagnosis and treatment. Results: Most of the patients were externally evaluated and were initially misdiagnosed. Some of them were suspected of colonic malignancy, other presumed to have hepatic hemangioma and fistulizing crohn’s disease. The definitive diagnosis is often based on histopathological examination and fungal culture of the surgically resected mass. An optimum standardized treatment of basidiobolomycosis has not yet been established. Conclusion: Deeper knowledge of clinical characteristics, diagnosis, and treatment of basidiobolomycosis will allow early initiating of treatment with a subsequent positive impact on the patients’ outcome. More studies are needed to establish a definite treatment.

Keywords: gastrointestinal infection, crohn's mimics, malignancy mimics, fungal infection

Procedia PDF Downloads 148
19050 Comparison of Different Methods to Produce Fuzzy Tolerance Relations for Rainfall Data Classification in the Region of Central Greece

Authors: N. Samarinas, C. Evangelides, C. Vrekos

Abstract:

The aim of this paper is the comparison of three different methods, in order to produce fuzzy tolerance relations for rainfall data classification. More specifically, the three methods are correlation coefficient, cosine amplitude and max-min method. The data were obtained from seven rainfall stations in the region of central Greece and refers to 20-year time series of monthly rainfall height average. Three methods were used to express these data as a fuzzy relation. This specific fuzzy tolerance relation is reformed into an equivalence relation with max-min composition for all three methods. From the equivalence relation, the rainfall stations were categorized and classified according to the degree of confidence. The classification shows the similarities among the rainfall stations. Stations with high similarity can be utilized in water resource management scenarios interchangeably or to augment data from one to another. Due to the complexity of calculations, it is important to find out which of the methods is computationally simpler and needs fewer compositions in order to give reliable results.

Keywords: classification, fuzzy logic, tolerance relations, rainfall data

Procedia PDF Downloads 307
19049 An Evaluation of the Trends in Land Values around Institutions of Higher Learning in North Central Nigeria

Authors: Ben Nwokenkwo, Michael M. Eze, Felix Ike

Abstract:

The need to study trends in land values around institutions of higher learning cannot be overemphasized. Numerous studies in Nigeria have investigated the economic, and social influence of the sitting of institutions of higher learning at the micro, meso and macro levels. However, very few studies have evaluated the temporal extent at which such institution influences local land values. Since institutions greatly influence both the physical and environmental aspects of their immediate vicinity, attention must be taken to understand the influence of such changes on land values. This study examines the trend in land values using the Mann-Kendall analysis in order to determine if, between its beginning and end, a monotonic increase, decrease or stability exist in the land values across six institutions of higher learning for the period between 2004 and 2014. Specifically, The analysis was applied to the time series of the price(or value) of the land .The results of this study revealed that land values has either been increasing or remained stabled across all the institution sampled. The study finally recommends measures that can be put in place as counter magnets for land values estimation across institutions of higher learning.

Keywords: influence, land, trend, value

Procedia PDF Downloads 357
19048 The Development of E-Commerce in Mexico: An Econometric Analysis

Authors: Alma Lucero Ortiz, Mario Gomez

Abstract:

Technological advances contribute to the well-being of humanity by allowing man to perform in a more efficient way. Technology offers tangible advantages to countries with the adoption of information technologies, communication, and the Internet in all social and productive sectors. The Internet is a networking infrastructure that allows the communication of people throughout the world, exceeding the limits of time and space. Nowadays the internet has changed the way of doing business leading to a digital economy. In this way, e-commerce has emerged as a commercial transaction conducted over the Internet. For this inquiry e-commerce is seen as a source of economic growth for the country. Thereby, these research aims to answer the research question, which are the main variables that have affected the development of e-commerce in Mexico. The research includes a period of study from 1990 to 2017. This inquiry aims to get insight on how the independent variables influence the e-commerce development. The independent variables are information infrastructure construction, urbanization level, economic level, technology level, human capital level, educational level, standards of living, and price index. The results suggest that the independent variables have an impact on development of the e-commerce in Mexico. The present study is carried out in five parts. After the introduction, in the second part, a literature review about the main qualitative and quantitative studies to measure the variables subject to the study is presented. After, an empirical study is applied through time series data, and to process the data an econometric model is performed. In the fourth part, the analysis and discussion of results are presented, and finally, some conclusions are included.

Keywords: digital economy, e-commerce, econometric model, economic growth, internet

Procedia PDF Downloads 226
19047 Power System Stability Enhancement Using Self Tuning Fuzzy PI Controller for TCSC

Authors: Salman Hameed

Abstract:

In this paper, a self-tuning fuzzy PI controller (STFPIC) is proposed for thyristor controlled series capacitor (TCSC) to improve power system dynamic performance. In a STFPIC controller, the output scaling factor is adjusted on-line by an updating factor (α). The value of α is determined from a fuzzy rule-base defined on error (e) and change of error (Δe) of the controlled variable. The proposed self-tuning controller is designed using a very simple control rule-base and the most natural and unbiased membership functions (MFs) (symmetric triangles with equal base and 50% overlap with neighboring MFs). The comparative performances of the proposed STFPIC and the standard fuzzy PI controller (FPIC) have been investigated on a multi-machine power system (namely, 4 machine two area system) through detailed non-linear simulation studies using MATLAB/SIMULINK. From the simulation studies it has been found out that for damping oscillations, the performance of the proposed STFPIC is better than that obtained by the standard FPIC. Moreover, the proposed STFPIC as well as the FPIC have been found to be quite effective in damping oscillations over a wide range of operating conditions and are quite effective in enhancing the power carrying capability of the power system significantly.

Keywords: genetic algorithm, power system stability, self-tuning fuzzy controller, thyristor controlled series capacitor

Procedia PDF Downloads 416
19046 Cognitive SATP for Airborne Radar Based on Slow-Time Coding

Authors: Fanqiang Kong, Jindong Zhang, Daiyin Zhu

Abstract:

Space-time adaptive processing (STAP) techniques have been motivated as a key enabling technology for advanced airborne radar applications. In this paper, the notion of cognitive radar is extended to STAP technique, and cognitive STAP is discussed. The principle for improving signal-to-clutter ratio (SCNR) based on slow-time coding is given, and the corresponding optimization algorithm based on cyclic and power-like algorithms is presented. Numerical examples show the effectiveness of the proposed method.

Keywords: space-time adaptive processing (STAP), airborne radar, signal-to-clutter ratio, slow-time coding

Procedia PDF Downloads 265
19045 A Study of Islamic Stock Indices and Macroeconomic Variables

Authors: Mohammad Irfan

Abstract:

The purpose of this paper is to investigate the relationship among the key macroeconomic variables and Islamic stock market in India. This study is based on the time series data of financial years 2009-2015 to explore the consistency of relationship between macroeconomic variables and Shariah Indices. The ADF (Augmented Dickey–Fuller Test Statistic) and PP (Phillips–Perron Test Statistic) tests are employed to check stationarity of the data. The study depicts the long run relationship between Shariah indices and macroeconomic variables by using the Johansen Co-integration test. BSE Shariah and Nifty Shariah have uni-direct Granger causality. The outcome of VECM is significantly confirming the applicability of best fitted model. Thus, Islamic stock indices are proficiently working for the development of Indian economy. It suggests that by keeping eyes on Islamic stock market which will be more interactive in the future with other macroeconomic variables.

Keywords: Indian Shariah Indices, macroeconomic variables, co-integration, Granger causality, vector error correction model (VECM)

Procedia PDF Downloads 273
19044 Leverage Effect for Volatility with Generalized Laplace Error

Authors: Farrukh Javed, Krzysztof Podgórski

Abstract:

We propose a new model that accounts for the asymmetric response of volatility to positive ('good news') and negative ('bad news') shocks in economic time series the so-called leverage effect. In the past, asymmetric powers of errors in the conditionally heteroskedastic models have been used to capture this effect. Our model is using the gamma difference representation of the generalized Laplace distributions that efficiently models the asymmetry. It has one additional natural parameter, the shape, that is used instead of power in the asymmetric power models to capture the strength of a long-lasting effect of shocks. Some fundamental properties of the model are provided including the formula for covariances and an explicit form for the conditional distribution of 'bad' and 'good' news processes given the past the property that is important for the statistical fitting of the model. Relevant features of volatility models are illustrated using S&P 500 historical data.

Keywords: heavy tails, volatility clustering, generalized asymmetric laplace distribution, leverage effect, conditional heteroskedasticity, asymmetric power volatility, GARCH models

Procedia PDF Downloads 376
19043 Relationship between Depression, Stress, and Life Satisfaction among Students

Authors: Rexa Pasha

Abstract:

The aim of this study was to examine the relationship between depression, stress and life satisfaction with sleep disturbance among Islamic Azad University Ahvaz Branch students. Samples in the study included 230 students who were selected by stratified random sampling. For data collection, the Beck Depression Inventory, stress, life satisfaction and quality of sleep (PSQI) was used. Which all have acceptable reliability and validity. This study was correlation and Data analysis using Pearson correlation and multivariate regression significance level (pKeywords: depression, life satisfaction, sleep disorder, sleep disturbane

Procedia PDF Downloads 421
19042 Improving the Ability of Constructed Wetlands to Treat Acid Mine Drainage

Authors: Chigbo Emmanuel Ikechukwu

Abstract:

Constructed wetlands are seen as a potential means of ameliorating the poor quality water that derives from coal and gold mining operations. However, the processes whereby a wetland environment is able to improve water quality are not well understood and techniques for optimising their performance poorly developed. A parameter that may be manipulated in order to improve the treatment capacity of a wetland is the substrate in which the aquatic plants are rooted. This substrate can provide an environment wherein sulphate reducing bacteria, which contribute to the removal of contaminants from the water, are able to flourish. The bacteria require an energy source which is largely provided by carbon in the substrate. This paper discusses the form in which carbon is most suitable for the bacteria and describes the results of a series of experiments in which different materials were used as substrate. Synthetic acid mine drainage was passed through an anaerobic bioreactor that contained either compost or cow manure. The effluent water quality was monitored with respect to time and the effect of the substrate composition discussed.

Keywords: constructed wetland, bacteria, carbon, acid mine drainage, sulphate

Procedia PDF Downloads 430
19041 Investigation of Time Pressure and Instinctive Reaction in Moral Dilemmas While Driving

Authors: Jacqueline Miller, Dongyuan Y. Wang, F. Dan Richard

Abstract:

Before trying to make an ethical machine that holds a higher ethical standard than humans, a better understanding of human moral standards that could be used as a guide is crucial. How humans make decisions in dangerous driving situations like moral dilemmas can contribute to developing acceptable ethical principles for autonomous vehicles (AVs). This study uses a driving simulator to investigate whether drivers make utilitarian choices (choices that maximize lives saved and minimize harm) in unavoidable automobile accidents (moral dilemmas) with time pressure manipulated. This study also investigates how impulsiveness influences drivers’ behavior in moral dilemmas. Manipulating time pressure results in collisions that occur at varying time intervals (4 s, 5 s, 7s). Manipulating time pressure helps investigate how time pressure may influence drivers’ response behavior. Thirty-one undergraduates participated in this study using a STISM driving simulator to respond to driving moral dilemmas. The results indicated that the percentage of utilitarian choices generally increased when given more time to respond (from 4 s to 7 s). Additionally, participants in vehicle scenarios preferred responding right over responding left. Impulsiveness did not influence utilitarian choices. However, as time pressure decreased, response time increased. Findings have potential implications and applications on the regulation of driver assistance technologies and AVs.

Keywords: time pressure, automobile moral dilemmas, impulsiveness, reaction time

Procedia PDF Downloads 48
19040 Using Printouts as Social Media Evidence and Its Authentication in the Courtroom

Authors: Chih-Ping Chang

Abstract:

Different from traditional objective evidence, social media evidence has its own characteristics with easily tampering, recoverability, and cannot be read without using other devices (such as a computer). Simply taking a screenshot from social network sites must be questioned its original identity. When the police search and seizure digital information, a common way they use is to directly print out digital data obtained and ask the signature of the parties at the presence, without taking original digital data back. In addition to the issue on its original identity, this conduct to obtain evidence may have another two results. First, it will easily allege that is tampering evidence because the police wanted to frame the suspect and falsified evidence. Second, it is not easy to discovery hidden information. The core evidence associated with crime may not appear in the contents of files. Through discovery the original file, data related to the file, such as the original producer, creation time, modification date, and even GPS location display can be revealed from hidden information. Therefore, how to show this kind of evidence in the courtroom will be arguably the most important task for ruling social media evidence. This article, first, will introduce forensic software, like EnCase, TCT, FTK, and analyze their function to prove the identity with another digital data. Then turning back to the court, the second part of this article will discuss legal standard for authentication of social media evidence and application of that forensic software in the courtroom. As the conclusion, this article will provide a rethinking, that is, what kind of authenticity is this rule of evidence chase for. Does legal system automatically operate the transcription of scientific knowledge? Or furthermore, it wants to better render justice, not only under scientific fact, but through multivariate debating.

Keywords: federal rule of evidence, internet forensic, printouts as evidence, social media evidence, United States v. Vayner

Procedia PDF Downloads 283
19039 Adaptive Discharge Time Control for Battery Operation Time Enhancement

Authors: Jong-Bae Lee, Seongsoo Lee

Abstract:

This paper proposes an adaptive discharge time control method to balance cell voltages in alternating battery cell discharging method. In the alternating battery cell discharging method, battery cells are periodically discharged in turn. Recovery effect increases battery output voltage while the given battery cell rests without discharging, thus battery operation time of target system increases. However, voltage mismatch between cells leads two problems. First, voltage difference between cells induces inter-cell current with wasted power. Second, it degrades battery operation time, since system stops when any cell reaches to the minimum system operation voltage. To solve this problem, the proposed method adaptively controls cell discharge time to equalize both cell voltages. In the proposed method, battery operation time increases about 19%, while alternating battery cell discharging method shows about 7% improvement.

Keywords: battery, recovery effect, low-power, alternating battery cell discharging, adaptive discharge time control

Procedia PDF Downloads 346
19038 Stability of Hybrid Stochastic Systems

Authors: Manlika Ratchagit

Abstract:

This paper is concerned with robust mean square stability of uncertain stochastic switched discrete time-delay systems. The system to be considered is subject to interval time-varying delays, which allows the delay to be a fast time-varying function and the lower bound is not restricted to zero. Based on the discrete Lyapunov functional, a switching rule for the robust mean square stability for the uncertain stochastic discrete time-delay system is designed via linear matrix inequalities. Finally, some examples are exploited to illustrate the effectiveness of the proposed schemes.

Keywords: robust mean square stability, discrete-time stochastic systems, hybrid systems, interval time-varying delays, Lyapunov functional, linear matrix inequalities

Procedia PDF Downloads 477
19037 Predicting Global Solar Radiation Using Recurrent Neural Networks and Climatological Parameters

Authors: Rami El-Hajj Mohamad, Mahmoud Skafi, Ali Massoud Haidar

Abstract:

Several meteorological parameters were used for the prediction of monthly average daily global solar radiation on horizontal using recurrent neural networks (RNNs). Climatological data and measures, mainly air temperature, humidity, sunshine duration, and wind speed between 1995 and 2007 were used to design and validate a feed forward and recurrent neural network based prediction systems. In this paper we present our reference system based on a feed-forward multilayer perceptron (MLP) as well as the proposed approach based on an RNN model. The obtained results were promising and comparable to those obtained by other existing empirical and neural models. The experimental results showed the advantage of RNNs over simple MLPs when we deal with time series solar radiation predictions based on daily climatological data.

Keywords: recurrent neural networks, global solar radiation, multi-layer perceptron, gradient, root mean square error

Procedia PDF Downloads 434
19036 Holistic Approach Illustrating the Use of Complementary and Alternative Medicine in Pain and Stress Management for Spinal Cord Injury

Authors: Priyanka Kalra

Abstract:

Background: Complementary and alternative medicine (CAM) includes various practices like Ayurveda, Yoga & Meditation Acupressure Acupuncture and Reiki. These practices are frequently used by patients with spinal cord injury (SCI). They have shown effectiveness in the management of pain and stress consequently improving overall quality of life post injury. Objective: The goals of the present case series were to evaluate the feasibility of 1) Using of Ayurvedic herbal oil massages in shoulder pain management, 2) Using yoga & meditation on managing the stress in spinal cord injury. Methodology: 15 SCI cases with muscular pain around shoulder were treated with Ayurvedic herbal oil massage for 10 days in CAM Department. Each session consisted of 30 min oil massage followed by 10 min hot towel fomentation. The patients continued regular therapy medications along with CAM. Another 15 SCI cases were treated with yoga and meditation for 15 days 30 min yoga (20 min Asana+ 10 min Pranayam + 15 min Meditation) in isolated yoga room of CAM department. Results: On the VAS scale the patients reported a reduction in their pain score by 70 %. On the PSS scale, the patients reported a reduction in their stress score by 80 %. Conclusion: These case series may encourage more people to explore CAM therapies.

Keywords: spinal cord injury, Ayurveda, complementary and alternative medicine, yoga, meditation

Procedia PDF Downloads 293
19035 New Results on Stability of Hybrid Stochastic Systems

Authors: Manlika Rajchakit

Abstract:

This paper is concerned with robust mean square stability of uncertain stochastic switched discrete time-delay systems. The system to be considered is subject to interval time-varying delays, which allows the delay to be a fast time-varying function and the lower bound is not restricted to zero. Based on the discrete Lyapunov functional, a switching rule for the robust mean square stability for the uncertain stochastic discrete time-delay system is designed via linear matrix inequalities. Finally, some examples are exploited to illustrate the effectiveness of the proposed schemes.

Keywords: robust mean square stability, discrete-time stochastic systems, hybrid systems, interval time-varying delays, lyapunov functional, linear matrix inequalities

Procedia PDF Downloads 423
19034 Transport Related Air Pollution Modeling Using Artificial Neural Network

Authors: K. D. Sharma, M. Parida, S. S. Jain, Anju Saini, V. K. Katiyar

Abstract:

Air quality models form one of the most important components of an urban air quality management plan. Various statistical modeling techniques (regression, multiple regression and time series analysis) have been used to predict air pollution concentrations in the urban environment. These models calculate pollution concentrations due to observed traffic, meteorological and pollution data after an appropriate relationship has been obtained empirically between these parameters. Artificial neural network (ANN) is increasingly used as an alternative tool for modeling the pollutants from vehicular traffic particularly in urban areas. In the present paper, an attempt has been made to model traffic air pollution, specifically CO concentration using neural networks. In case of CO concentration, two scenarios were considered. First, with only classified traffic volume input and the second with both classified traffic volume and meteorological variables. The results showed that CO concentration can be predicted with good accuracy using artificial neural network (ANN).

Keywords: air quality management, artificial neural network, meteorological variables, statistical modeling

Procedia PDF Downloads 513
19033 The Application of the Analytic Basis Function Expansion Triangular-z Nodal Method for Neutron Diffusion Calculation

Authors: Kunpeng Wang, Hongchun, Wu, Liangzhi Cao, Chuanqi Zhao

Abstract:

The distributions of homogeneous neutron flux within a node were expanded into a set of analytic basis functions which satisfy the diffusion equation at any point in a triangular-z node for each energy group, and nodes were coupled with each other with both the zero- and first-order partial neutron current moments across all the interfaces of the triangular prism at the same time. Based this method, a code TABFEN has been developed and applied to solve the neutron diffusion equation in a complicated geometry. In addition, after a series of numerical derivation, one can get the neutron adjoint diffusion equations in matrix form which is the same with the neutron diffusion equation; therefore, it can be solved by TABFEN, and the low-high scan strategy is adopted to improve the efficiency. Four benchmark problems are tested by this method to verify its feasibility, the results show good agreement with the references which demonstrates the efficiency and feasibility of this method.

Keywords: analytic basis function expansion method, arbitrary triangular-z node, adjoint neutron flux, complicated geometry

Procedia PDF Downloads 439
19032 An Ensemble System of Classifiers for Computer-Aided Volcano Monitoring

Authors: Flavio Cannavo

Abstract:

Continuous evaluation of the status of potentially hazardous volcanos plays a key role for civil protection purposes. The importance of monitoring volcanic activity, especially for energetic paroxysms that usually come with tephra emissions, is crucial not only for exposures to the local population but also for airline traffic. Presently, real-time surveillance of most volcanoes worldwide is essentially delegated to one or more human experts in volcanology, who interpret data coming from different kind of monitoring networks. Unfavorably, the high nonlinearity of the complex and coupled volcanic dynamics leads to a large variety of different volcanic behaviors. Moreover, continuously measured parameters (e.g. seismic, deformation, infrasonic and geochemical signals) are often not able to fully explain the ongoing phenomenon, thus making the fast volcano state assessment a very puzzling task for the personnel on duty at the control rooms. With the aim of aiding the personnel on duty in volcano surveillance, here we introduce a system based on an ensemble of data-driven classifiers to infer automatically the ongoing volcano status from all the available different kind of measurements. The system consists of a heterogeneous set of independent classifiers, each one built with its own data and algorithm. Each classifier gives an output about the volcanic status. The ensemble technique allows weighting the single classifier output to combine all the classifications into a single status that maximizes the performance. We tested the model on the Mt. Etna (Italy) case study by considering a long record of multivariate data from 2011 to 2015 and cross-validated it. Results indicate that the proposed model is effective and of great power for decision-making purposes.

Keywords: Bayesian networks, expert system, mount Etna, volcano monitoring

Procedia PDF Downloads 234
19031 Microwave Dielectric Relaxation Study of Diethanolamine with Triethanolamine from 10 MHz-20 GHz

Authors: A. V. Patil

Abstract:

The microwave dielectric relaxation study of diethanolamine with triethanolamine binary mixture have been determined over the frequency range of 10 MHz to 20 GHz, at various temperatures using time domain reflectometry (TDR) method for 11 concentrations of the system. The present work reveals molecular interaction between same multi-functional groups [−OH and –NH2] of the alkanolamines (diethanolamine and triethanolamine) using different models such as Debye model, Excess model, and Kirkwood model. The dielectric parameters viz. static dielectric constant (ε0) and relaxation time (τ) have been obtained with Debye equation characterized by a single relaxation time without relaxation time distribution by the least squares fit method.

Keywords: diethanolamine, excess properties, kirkwood properties, time domain reflectometry, triethanolamine

Procedia PDF Downloads 293