Search results for: normal state.

Authors: T. Denkçeken, M. Canpolat, Đ. Bassorgun, S. Yücel, M.A. Çiftçioğlu, M. Baykara Murat Canpolat , Tuba Denkçeken , Đbrahim Bassorgun , Selçuk Yücel , M. Akif Çiftçioğlu , Mehmet Baykara

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Elastic light single-scattering spectroscopy system with a single optical fiber probe was employed to differentiate cancerous prostate tissue from non-cancerous prostate tissue ex-vivo just after radical prostatectomy. First, ELSSS spectra were acquired from cancerous prostate tissue to define its spectral features. Then, spectra were acquired from normal prostate tissue to define difference in spectral features between the cancerous and normal prostate tissues. Of the total 66 tissue samples were evaluated from nine patients by ELSSS system. Comparing of histopathology results and ELSSS measurements revealed that sign of the spectral slopes of cancerous prostate tissue is negative and non-cancerous tissue is positive in the wavelength range from 450 to 750 nm. Based on the correlation between histopathology results and sign of the spectral slopes, ELSSS system differentiates cancerous prostate tissue from non- cancerous with a sensitivity of 0.95 and a specificity of 0.94.

Keywords: Diagnosis, prostatic neoplasm, prostatectomy, spectrum analysis

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Authors: V. Sacca, A. Sarica, F. Novellino, S. Barone, T. Tallarico, E. Filippelli, A. Granata, P. Valentino, A. Quattrone

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In the last few years, resting-state functional MRI (rs-fMRI) was widely used to investigate the architecture of brain networks by investigating the Blood Oxygenation Level Dependent response. This technique represented an interesting, robust and reliable approach to compare pathologic and healthy subjects in order to investigate neurodegenerative diseases evolution. On the other hand, the elaboration of rs-fMRI data resulted to be very prone to noise due to confounding factors especially the head motion. Head motion has long been known to be a source of artefacts in task-based functional MRI studies, but it has become a particularly challenging problem in recent studies using rs-fMRI. The aim of this work was to evaluate in MS patients a well-known motion correction algorithm from the FMRIB's Software Library - MCFLIRT - that could be applied to minimize the head motion distortions, allowing to correctly interpret rs-fMRI results.

Keywords: Head motion correction, MCFLIRT algorithm, multiple sclerosis, resting state fMRI.

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Authors: Essam Al-Daoud

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A potentially serious problem with current payment systems is that their underlying hard problems from number theory may be solved by either a quantum computer or unanticipated future advances in algorithms and hardware. A new quantum payment system is proposed in this paper. The suggested system makes use of fundamental principles of quantum mechanics to ensure the unconditional security without prior arrangements between customers and vendors. More specifically, the new system uses Greenberger-Home-Zeilinger (GHZ) states and Quantum Key Distribution to authenticate the vendors and guarantee the transaction integrity.

Keywords: Bell state, GHZ state, Quantum key distribution, Quantum payment system.

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Authors: Yeo Kyeong Lee, Hae Won Min, Ji Yeon Kang, Hee Sun Kim, Yeong Soo Shin

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In recent years, fire accidents have been steadily increased and the amount of property damage caused by the accidents has gradually raised. Damaging building structure, fire incidents bring about not only such property damage but also strength degradation and member deformation. As a result, the building structure undermines its structural ability. Examining the degradation and the deformation is very important because reusing the building is more economical than reconstruction. Therefore, engineers need to investigate the strength degradation and member deformation well, and make sure that they apply right rehabilitation methods. This study aims at evaluating deformation characteristics of fire damaged and rehabilitated normal strength concrete beams through both experiments and finite element analyses. For the experiments, control beams, fire damaged beams and rehabilitated beams are tested to examine deformation characteristics. Ten test beam specimens with compressive strength of 21MPa are fabricated and main test variables are selected as cover thickness of 40mm and 50mm and fire exposure time of 1 hour or 2 hours. After heating, fire damaged beams are air-recurred for 2 months and rehabilitated beams are repaired with polymeric cement mortar after being removed the fire damaged concrete cover. All beam specimens are tested under four points loading. FE analyses are executed to investigate the effects of main parameters applied to experimental study. Test results show that both maximum load and stiffness of the rehabilitated beams are higher than those of the fire damaged beams. In addition, predicted structural behaviors from the analyses also show good rehabilitation effect and the predicted load-deflection curves are similar to the experimental results. For the further, the proposed analytical method can be used to predict deformation characteristics of fire damaged and rehabilitated concrete beams without suffering from time and cost consuming of experimental process.

Keywords: Fire, Normal strength concrete, Rehabilitation, Reinforced concrete beam.

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Authors: Su-Hyun Jung, Chang-Bin Ha, Hyoung-Kyu Song

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Recently, increasing the quality of experience (QoE) is an important issue. Since performance degradation at cell edge extremely reduces the QoE, several techniques are defined at LTE/LTE-A standard to remove inter-cell interference (ICI). However, the conventional techniques have disadvantage because there is a trade-off between resource allocation and reliable communication. The proposed scheme reduces the ICI more efficiently by using channel state information (CSI) smartly. It is shown that the proposed scheme can reduce the ICI with fewer resources.

Keywords: Adaptive beam forming, CoMP, LTE-A, ICI reduction.

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Authors: G. Tamilpavai, C. Vishnuppriya

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Studying DNA (deoxyribonucleic acid) sequence is useful in biological processes and it is applied in the fields such as diagnostic and forensic research. DNA is the hereditary information in human and almost all other organisms. It is passed to their generations. Earlier stage detection of defective DNA sequence may lead to many developments in the field of Bioinformatics. Nowadays various tedious techniques are used to identify defective DNA. The proposed work is to analyze and identify the cancer-causing DNA motif in a given sequence. Initially the human DNA sequence is separated as k-mers using k-mer separation rule. The separated k-mers are clustered using Self Organizing Map (SOM). Using Levenshtein distance measure, cancer associated DNA motif is identified from the k-mer clusters. Experimental results of this work indicate the presence or absence of cancer causing DNA motif. If the cancer associated DNA motif is found in DNA, it is declared as the cancer disease causing DNA sequence. Otherwise the input human DNA is declared as normal sequence. Finally, elapsed time is calculated for finding the presence of cancer causing DNA motif using clustering formation. It is compared with normal process of finding cancer causing DNA motif. Locating cancer associated motif is easier in cluster formation process than the other one. The proposed work will be an initiative aid for finding genetic disease related research.

Keywords: Bioinformatics, cancer motif, DNA, k-mers, Levenshtein distance, SOM.

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Authors: A. S. Haruna

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The incessant discomfort for Voluntary Counselling and Testing (VCT) exhibited by students in some tertiary institutions in Kano State, Nigeria is capable of causing Psychological Resistance as well as jeopardizing the purpose of HIV intervention. This study investigated the Prevalence of Psychological Resistance to VCT of HIV/AIDS among students of tertiary institutions in the state. Two null hypotheses were postulated and tested. Cross- Sectional Survey Design was employed in which 1512 sample was selected from a student population of 104,841 following Stratified Random Sampling technique. A self-developed 20-item scale whose reliability coefficient is 0.83 was used for data collection. Data analyzed via Chi-square and t-test reveals a prevalence of 38% with males (Mean=0.34; SD=0.475) constituting 60% and females (Mean=0.45; SD=0.498) 40%. Also, the calculated chi-square and ttest were not significant at 0.05 as such the null hypotheses were upheld. Recommendation offered suggests the use of reinforcement and social support for students who patronize HIV/AIDS counselling.

Keywords: HIV/AIDS, Prevalence rate, Psychological Resistance, VCT.

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Authors: Eric P. Jiang

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As the Internet continues to grow at a rapid pace as the primary medium for communications and commerce and as telecommunication networks and systems continue to expand their global reach, digital information has become the most popular and important information resource and our dependence upon the underlying cyber infrastructure has been increasing significantly. Unfortunately, as our dependency has grown, so has the threat to the cyber infrastructure from spammers, attackers and criminal enterprises. In this paper, we propose a new machine learning based network intrusion detection framework for cyber security. The detection process of the framework consists of two stages: model construction and intrusion detection. In the model construction stage, a semi-supervised machine learning algorithm is applied to a collected set of network audit data to generate a profile of normal network behavior and in the intrusion detection stage, input network events are analyzed and compared with the patterns gathered in the profile, and some of them are then flagged as anomalies should these events are sufficiently far from the expected normal behavior. The proposed framework is particularly applicable to the situations where there is only a small amount of labeled network training data available, which is very typical in real world network environments.

Keywords: classification, data analysis and mining, network intrusion detection, semi-supervised learning.

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Authors: Kuntal Thakkar, Chaouki Ghenai, Ahmed Hachicha

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An integrated modeling approach was used in this study for energy planning and climate change mitigation assessment. The main objective of this study was to develop various green-house gas (GHG) mitigations scenarios in the energy demand and supply sectors for the state of Florida. The Long range energy alternative planning (LEAP) model was used in this study to examine the energy alternative and GHG emissions reduction scenarios for short and long term (2010-2050). One of the energy analysis and GHG mitigation scenarios was developed by taking into account the available renewable energy resources potential for power generation in the state of Florida. This will help to compare and analyze the GHG reduction measure against “Business As Usual” and ‘State of Florida Policy” scenarios. Two master scenarios: “Electrification” and “Energy efficiency and Lifestyle” were developed through combination of various mitigation scenarios: technological changes and energy efficiency and conservation. The results show a net reduction of the energy demand and GHG emissions by adopting these two energy scenarios compared to the business as usual.

Keywords: Integrated modeling, energy planning, climate change mitigation assessment, greenhouse gas emissions, renewable energy, energy efficiency.

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Authors: Choulseung Hyun, Hunki Kwon, Jaeho Kim, Eujoon Byun, Jongmoo Choi, Donghee Lee, Sam H. Noh

Abstract:

Most file systems overwrite modified file data and metadata in their original locations, while the Log-structured File System (LFS) dynamically relocates them to other locations. We design and implement the Evergreen file system that can select between overwriting or relocation for each block of a file or metadata. Therefore, the Evergreen file system can achieve superior write performance by sequentializing write requests (similar to LFS-style relocation) when space utilization is low and overwriting when utilization is high. Another challenging issue is identifying performance benefits of LFS-style relocation over overwriting on a newly introduced SSD (Solid State Drive) which has only Flash-memory chips and control circuits without mechanical parts. Our experimental results measured on a SSD show that relocation outperforms overwriting when space utilization is below 80% and vice versa.

Keywords: Evergreen File System, Overwrite, Relocation, Solid State Drive.

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Authors: Kailash C. Madan

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We study four models of a three server queueing system with Bernoulli schedule optional server vacations. Customers arriving at the system one by one in a Poisson process are provided identical exponential service by three parallel servers according to a first-come, first served queue discipline. In model A, all three servers may be allowed a vacation at one time, in Model B at the most two of the three servers may be allowed a vacation at one time, in model C at the most one server is allowed a vacation, and in model D no server is allowed a vacation. We study steady the state behavior of the four models and obtain steady state probability generating functions for the queue size at a random point of time for all states of the system. In model D, a known result for a three server queueing system without server vacations is derived.

Keywords: A three server queue, Bernoulli schedule server vacations, queue size distribution at a random epoch, steady state.

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Authors: K. Benhabib, X. Pierens, V-D Nguyen, G. Mimanne

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The main hypothesis of the dynamics of solid phase microextraction (SPME) is that steady-state mass transfer is respected throughout the SPME extraction process. It considers steady-state diffusion is established in the two phases and fast exchange of the analyte at the solid phase film/water interface. An improved model is proposed in this paper to handle with the situation when the analyte (atrazine) is in contact with colloid suspensions (carboxylate latex in aqueous solution). A mathematical solution is obtained by substituting the diffusion coefficient by the mean of diffusion coefficient between analyte and carboxylate latex, and also thickness layer by the mean thickness in aqueous solution. This solution provides an equation relating the extracted amount of the analyte to the extraction a little more complicated than previous models. It also gives a better description of experimental observations. Moreover, the rate constant of analyte obtained is in satisfactory agreement with that obtained from the initial curve fitting.

Keywords: Pesticide, SPME methods, polyacrylate, steady state.

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Authors: Fahad Suleiman

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The aim of this paper is to study students’ view on mathematics learning in Katsina State Senior Secondary Schools of Nigeria, such as their conceptions of mathematics, attitudes toward mathematics learning, etc. A questionnaire was administered to a random sample of 1,225 senior secondary two (SS II) students of Katsina State in Nigeria. The data collected showed a clear picture of the hurdles that affect the teaching and learning of mathematics in our schools. Problems such as logistics and operational which include shortage of mathematics teachers, non–availability of a mathematics laboratory, etc. were identified. It also depicted the substantial trends of changing views and attitudes toward mathematics across secondary schools. Students’ responses to the conception of mathematics were consistent and they demonstrated some specific characteristics of their views in learning mathematics. This survey has provided useful information regarding students’ needs and aspirations in mathematics learning for curriculum planners and frontline teachers for future curriculum reform and implementation.

Keywords: Attitude, education, mathematics, students.

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Authors: P. Ruttanee, K-N. Areerak, K-L. Areerak

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Dynamic models of power converters are normally time-varying because of their switching actions. Several approaches are applied to analyze the power converters to achieve the timeinvariant models suitable for system analysis and design via the classical control theory. The paper presents how to derive dynamic models of the power system consisting of a three-phase controlled rectifier feeding an uncontrolled buck converter by using the combination between the well known techniques called the DQ and the generalized state-space averaging methods. The intensive timedomain simulations of the exact topology model are used to support the accuracies of the reported model. The results show that the proposed model can provide good accuracies in both transient and steady-state responses.

Keywords: DQ method, Generalized state-space averaging method, Three-phase controlled rectifier, Uncontrolled buck converter, Averaging model, Modeling, Simulation.

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Authors: Gabriella Tjondro, Julita Dortua Laurentina Nainggolan

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Introduction: There are several things affecting menstrual cycle, namely, nutritional status, diet, financial status of one’s household and exercises. The most commonly used parameter to calculate the fat in a human body is body mass index. Therefore, it is necessary to do research to prevent complications caused by menstrual disorder in the future. Design Study: This research is an observational analytical study with the cross-sectional-case control approach. Participants (n = 124; median age = 19.5 years ± SD 3.5) were classified into 2 groups: normal, NM (n = 62; BMI = 18-23 kg/m²) and obese, OB (n = 62; BMI = > 25 kg/m²). BMI was calculated from the equation; BMI = weight, kg/height, m². Results: There were 79.10% from obese group who experienced menstrual cycle disorders (n=53, 79.10%; p value 0.00; OR 5.25) and 20.90% from normal BMI group with menstrual cycle disorders. There were several factors in this research that also influence the menstrual cycle disorders such as stress (44.78%; p value 0.00; OR 1.85), sleep disorders (25.37%; p value 0.00; OR 1.01), physical activities (25.37%; p value 0.00; OR 1.24) and diet (10.45%; p value 0.00; OR 1.07). Conclusion: There is a significant relation between body mass index (obese) and menstrual cycle disorders. However, BMI is not the only factor that affects the menstrual cycle disorders. There are several factors that also can affect menstrual cycle disorders, in this study we use stress, sleep disorders, physical activities and diet, in which none of them are dominant.

Keywords: Menstrual disorders, menstrual cycle, obesity, body mass index, stress, sleep disorders, physical activities, diet.

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Authors: Gaysu R. Arvind

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In policy discourse of 1990s, more inclusive spaces have been constructed for realizing full and meaningful participation of common people in education. These participatory spaces provide an alternative possibility for universalizing elementary education against the backdrop of a history of entrenched forms of social and economical exclusion; inequitable education provisions; and shrinking role of the state in today-s neo-liberal times. Drawing on case-studies of bottom-up approaches to school governance, the study examines an array of innovative ways through which poor people gained a sense of identity and agency by evolving indigenous solutions to issues regarding schooling of their children. In the process, state-s institutions and practices became more accountable and responsive to educational concerns of the marginalized people. The deliberative participation emerged as an active way of experiencing deeper forms of empowerment and democracy than its passive realization as mere bearers of citizen rights.

Keywords: Deliberative Forum, Inclusive Spaces, Participatory Governance, People's Agency

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Authors: Victor Breux, Jérôme Boutet, Alain Goret, Viviane Cattin

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Early detection of anomalies in data centers is important to reduce downtimes and the costs of periodic maintenance. However, there is little research on this topic and even fewer on the fusion of sensor data for the detection of abnormal events. The goal of this paper is to propose a method for anomaly detection in data centers by combining sensor data (temperature, humidity, power) and deep learning models. The model described in the paper uses one autoencoder per sensor to reconstruct the inputs. The auto-encoders contain Long-Short Term Memory (LSTM) layers and are trained using the normal samples of the relevant sensors selected by correlation analysis. The difference signal between the input and its reconstruction is then used to classify the samples using feature extraction and a random forest classifier. The data measured by the sensors of a data center between January 2019 and May 2020 are used to train the model, while the data between June 2020 and May 2021 are used to assess it. Performances of the model are assessed a posteriori through F1-score by comparing detected anomalies with the data center’s history. The proposed model outperforms the state-of-the-art reconstruction method, which uses only one autoencoder taking multivariate sequences and detects an anomaly with a threshold on the reconstruction error, with an F1-score of 83.60% compared to 24.16%.

Keywords: Anomaly detection, autoencoder, data centers, deep learning.

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Authors: Prathuang Usaborisut, Dithaporn Thungsotanon

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Soil compaction induced by a tractor towing trailer becomes a major problem associated to sugarcane productivity. Soil beneath the tractor’s tire is not only under compressing stress but also shearing stress. Therefore, in order to help to understand such effects on soil, this research aimed to determine stress state in soil and predict compaction of soil under a tractive tire. The octahedral stress ratios under the tires were higher than one and much higher under higher draft forces. Moreover, the ratio was increasing with increase of number of tire’s passage. Soil compaction model was developed using data acquired from triaxial tests. The model was then used to predict soil bulk density under tractive tire. The maximum error was about 4% at 15 cm depth under lower draft force and tended to increase with depth and draft force. At depth of 30 cm and under higher draft force, the maximum error was about 16%.

Keywords: Draft force, soil compaction model, stress state, tractive tire.

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Authors: Frank Emmert Streib, Matthias Dehmer, Jing Liu, Max Mühlhauser

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In this paper we present a method for gene ranking from DNA microarray data. More precisely, we calculate the correlation networks, which are unweighted and undirected graphs, from microarray data of cervical cancer whereas each network represents a tissue of a certain tumor stage and each node in the network represents a gene. From these networks we extract one tree for each gene by a local decomposition of the correlation network. The interpretation of a tree is that it represents the n-nearest neighbor genes on the n-th level of a tree, measured by the Dijkstra distance, and, hence, gives the local embedding of a gene within the correlation network. For the obtained trees we measure the pairwise similarity between trees rooted by the same gene from normal to cancerous tissues. This evaluates the modification of the tree topology due to progression of the tumor. Finally, we rank the obtained similarity values from all tissue comparisons and select the top ranked genes. For these genes the local neighborhood in the correlation networks changes most between normal and cancerous tissues. As a result we find that the top ranked genes are candidates suspected to be involved in tumor growth and, hence, indicates that our method captures essential information from the underlying DNA microarray data of cervical cancer.

Keywords: Graph similarity, DNA microarray data, cancer.

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Authors: Jehad Al Dallal, Paul Sorenson

Abstract:

An application framework provides a reusable design and implementation for a family of software systems. Application developers extend the framework to build their particular applications using hooks. Hooks are the places identified to show how to use and customize the framework. Hooks define the Framework Interface Classes (FICs) and their possible specifications, which helps in building reusable test cases for the implementations of these classes. This paper introduces a novel technique called all paths-state to generate state-based test cases to test the FICs at class level. The technique is experimentally evaluated. The empirical evaluation shows that all paths-state technique produces test cases with a high degree of coverage for the specifications of the implemented FICs comparing to test cases generated using round-trip path and all-transition techniques.

Keywords: Hooks, object-oriented framework, frameworkinterface classes (FICs), specification-based testing, test casegeneration.

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Authors: Pavan K. Rallabandi, Kailash C. Patidar

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In this paper, we present an optimization technique or a learning algorithm using the hybrid architecture by combining the most popular sequence recognition models such as Recurrent Neural Networks (RNNs) and Hidden Markov models (HMMs). In order to improve the sequence/pattern recognition/classification performance by applying a hybrid/neural symbolic approach, a gradient descent learning algorithm is developed using the Real Time Recurrent Learning of Recurrent Neural Network for processing the knowledge represented in trained Hidden Markov Models. The developed hybrid algorithm is implemented on automata theory as a sample test beds and the performance of the designed algorithm is demonstrated and evaluated on learning the deterministic finite state automata.

Keywords: Hybrid systems, Hidden Markov Models, Recurrent neural networks, Deterministic finite state automata.

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Authors: P. T. Ahamed Seyd, V. I. Thajudin Ahamed, Jeevamma Jacob, Paul Joseph K

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Diabetes mellitus (DM) is frequently characterized by autonomic nervous dysfunction. Analysis of heart rate variability (HRV) has become a popular noninvasive tool for assessing the activities of autonomic nervous system (ANS). In this paper, changes in ANS activity are quantified by means of frequency and time domain analysis of R-R interval variability. Electrocardiograms (ECG) of 16 patients suffering from DM and of 16 healthy volunteers were recorded. Frequency domain analysis of extracted normal to normal interval (NN interval) data indicates significant difference in very low frequency (VLF) power, low frequency (LF) power and high frequency (HF) power, between the DM patients and control group. Time domain measures, standard deviation of NN interval (SDNN), root mean square of successive NN interval differences (RMSSD), successive NN intervals differing more than 50 ms (NN50 Count), percentage value of NN50 count (pNN50), HRV triangular index and triangular interpolation of NN intervals (TINN) also show significant difference between the DM patients and control group.

Keywords: Autonomic nervous system, diabetes mellitus, frequency domain and time domain analysis, heart rate variability.

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Authors: Mohammad Ali Tabarzad, Caro Lucas, Ali Hamzeh

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Generalization is one of the most challenging issues of Learning Classifier Systems. This feature depends on the representation method which the system used. Considering the proposed representation schemes for Learning Classifier System, it can be concluded that many of them are designed to describe the shape of the region which the environmental states belong and the other relations of the environmental state with that region was ignored. In this paper, we propose a new representation scheme which is designed to show various relationships between the environmental state and the region that is specified with a particular classifier.

Keywords: Classifier Systems, Reinforcement Learning, Relational Representation, XCSF.

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Authors: S.M. Gupta, V.K. Sehgal, S.K. Kaushik

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This paper presents the results of an experimental investigation carried out to evaluate the shrinkage of High Strength Concrete. High Strength Concrete is made by partially replacement of cement by flyash and silica fume. The shrinkage of High Strength Concrete has been studied using the different types of coarse and fine aggregates i.e. Sandstone and Granite of 12.5 mm size and Yamuna and Badarpur Sand. The Mix proportion of concrete is 1:0.8:2.2 with water cement ratio as 0.30. Superplasticizer dose @ of 2% by weight of cement is added to achieve the required degree of workability in terms of compaction factor. From the test results of the above investigation it can be concluded that the shrinkage strain of High Strength Concrete increases with age. The shrinkage strain of concrete with replacement of cement by 10% of Flyash and Silica fume respectively at various ages are more (6 to 10%) than the shrinkage strain of concrete without Flyash and Silica fume. The shrinkage strain of concrete with Badarpur sand as Fine aggregate at 90 days is slightly less (10%) than that of concrete with Yamuna Sand. Further, the shrinkage strain of concrete with Granite as Coarse aggregate at 90 days is slightly less (6 to 7%) than that of concrete with Sand stone as aggregate of same size. The shrinkage strain of High Strength Concrete is also compared with that of normal strength concrete. Test results show that the shrinkage strain of high strength concrete is less than that of normal strength concrete.

Keywords: Shrinkage high strength concrete, fly ash, silica fume& superplastizers.

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Authors: Fury Khristianty Fitriyah

Abstract:

This study aims to identify the extent of the role of the Satuan Pengawas Intern (Internal Audit Unit) in detecting and preventing fraud in public universities in West Java under the Ministry of Research, Technology and Higher Education. The research method applied was a qualitative case study approach, while the unit of analysis for this study is the Internal Audit Unit at each public university. Results of this study indicate that the Internal Audit Unit is able to detect and prevent fraud within a public university environment by means of red flags to mark accounting anomalies. These stem from inaccurate budget planning that prompts inappropriate use of funds, exacerbated by late disbursements of funds, which potentially lead to fictitious transactions, and discrepancies in recording state-owned assets into a state property management system (SIMAK BMN), which, if not conducted properly, potentially causes loss to the state.

Keywords: Internal Audit Unit, efficiency, fraud, public university.

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Authors: Osifeko Olalekan Remigious, Adesanya Adebisi Joseph, Omolade Akinmade Olatunde

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The focus of this study was to determine the factors associated with the use of substances for sport performance of youth in Lagos state sport. Questionnaire was the instrument used for the study. Descriptive research method was used. The estimated population for the study was 2000 sport men and women. The sample size was 200 respondents for purposive sampling techniques were used. The instrument was validated in it content and constructs value. The instrument was administered with the assistance of the coaches. Same 200 copies administered were returned. The data obtained was analysed using simple percentage and chi-square (x2) for stated hypothesis at 0.05 level of significance. The finding reveal that sport injuries exercise induced and anaphylaxis and asthma and feeling of loss of efficacy associated with alcohol used on sport performance among the users of substances. Alcohol users are recommended to partake in sport like swimming, basketball and volleyball because they have space of time for resting while at play. Government should be fully in charge of the health of sport men and women.

Keywords: Implications, Lagos state, substances, sports performance, youths.

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Authors: Yun-Hsuan Yu, Chi-Shung Tang, Nzar Rauf Abdullah, Vidar Gudmundsson

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Spin-orbit gap feature in energy dispersion of one-dimensional devices is revealed via strong spin-orbit interaction (SOI) effects under Zeeman field. We describe the utilization of a finger-gate or a top-gate to control the spin-dependent transport characteristics in the SOI-Zeeman influenced split-gate devices by means of a generalized spin-mixed propagation matrix method. For the finger-gate system, we find a bound state in continuum for incident electrons within the ultra-low energy regime. For the top-gate system, we observe more bound-state features in conductance associated with the formation of spin-associated hole-like or electron-like quasi-bound states around band thresholds, as well as hole bound states around the reverse point of the energy dispersion. We demonstrate that the spin-dependent transport behavior of a top-gate system is similar to that of a finger-gate system only if the top-gate length is less than the effective Fermi wavelength.

Keywords: Spin-orbit, Zeeman, top-gate, finger-gate, bound state.

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Authors: K. Thulasimani, K. G. Srinivasagan

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Driver fatigue is an important factor in the increasing number of road accidents. Dynamic template matching method was proposed to address the problem of real-time driver fatigue detection system based on eye-tracking. An effective vision based approach was used to analyze the driver’s eye state to detect fatigue. The driver fatigue system consists of Face detection, Eye detection, Eye tracking, and Fatigue detection. Initially frames are captured from a color video in a car dashboard and transformed from RGB into YCbCr color space to detect the driver’s face. Canny edge operator was used to estimating the eye region and the locations of eyes are extracted. The extracted eyes were considered as a template matching for eye tracking. Edge Map Overlapping (EMO) and Edge Pixel Count (EPC) matching function were used for eye tracking which is used to improve the matching accuracy. The pixel of eyeball was tracked from the eye regions which are used to determine the fatigue state of the driver.

Keywords: Driver fatigue detection, Driving safety, Eye tracking, Intelligent transportation system, Template matching.

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Authors: E. N. Vetrova, L.V. Lapochkina, N. V. Nikulina

Abstract:

In the national economy, entrepreneurship plays the role of a buffer between economy and policy for it contributes to improving budget effectiveness and decreasing dependence of economy on the state. Entrepreneurship in industry makes it possible to increase the added value that is formed in production chains and to decrease dependence on import. Under the current circumstances, when sanctions are being imposed, this is especially relevant for Russia and for the realization of projects in the Russian Arctic. However, development of entrepreneurship in industry requires an enlightened state policy. The purpose of the research is elaboration of recommendations for improving economic effectiveness of the realization of the Arctic projects on the basis of conceptual proposals for the development of entrepreneurship in industry. The paper presents the studies of the extractive industry role in the Russian economy and proves its raw material character. The analysis of production chains in industry on the basis of the conception of the added value global chains demonstrated a low added value formed by Russian companies. The study of changes in the structure of economy based on systemic, statistical and comparative analyses revealed no positive changes in the structure of economy over the period under consideration. This is a manifestation of ineffectiveness of the Russian industrial policy in general and within the Arctic region in particular. The authors identified the problems information and implementation of the state industrial policy in the Arctic region and in the development of national entrepreneurship, analyzed the shortcomings of the current state policy in the sphere of the Russian industry. On the basis of the conducted studies, the authors formulated conceptual approaches to change the state policy in the Arctic. The basic idea of the authors is to substantiate the focus of the state regulation on the development of entrepreneurship in industry in the process of the Russian Arctic exploration. At the same time another problem is solved–that of the development of the manufacturing industry in the southern regions of the northwestern part of Russia. The criterion of effectiveness in this case is the economic effectiveness.

Keywords: Entrepreneurship in industry, global chains of the added value, government regulation, industrial policies, production chains in the Arctic region, economic effectiveness.

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Authors: Xiaowei Zhang, Min Xu, Saeid Habibi, Fengjun Yan, Ryan Ahmed

Abstract:

Recently, Electric Vehicles (EVs) have received extensive consideration since they offer a more sustainable and greener transportation alternative compared to fossil-fuel propelled vehicles. Lithium-Ion (Li-ion) batteries are increasingly being deployed in EVs because of their high energy density, high cell-level voltage, and low rate of self-discharge. Since Li-ion batteries represent the most expensive component in the EV powertrain, accurate monitoring and control strategies must be executed to ensure their prolonged lifespan. The Battery Management System (BMS) has to accurately estimate parameters such as the battery State-of-Charge (SOC), State-of-Health (SOH), and Remaining Useful Life (RUL). In order for the BMS to estimate these parameters, an accurate and control-oriented battery model has to work collaboratively with a robust state and parameter estimation strategy. Since battery physical parameters, such as the internal resistance and diffusion coefficient change depending on the battery state-of-life (SOL), the BMS has to be adaptive to accommodate for this change. In this paper, an extensive battery aging study has been conducted over 12-months period on 5.4 Ah, 3.7 V Lithium polymer cells. Instead of using fixed charging/discharging aging cycles at fixed C-rate, a set of real-world driving scenarios have been used to age the cells. The test has been interrupted every 5% capacity degradation by a set of reference performance tests to assess the battery degradation and track model parameters. As battery ages, the combined model parameters are optimized and tracked in an offline mode over the entire batteries lifespan. Based on the optimized model, a state and parameter estimation strategy based on the Extended Kalman Filter (EKF) and the relatively new Smooth Variable Structure Filter (SVSF) have been applied to estimate the SOC at various states of life.

Keywords: Lithium-Ion batteries, genetic algorithm optimization, battery aging test, and parameter identification.

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