Search results for: interval features

Authors: D. Scarpanti, M. Brondino, M. Pasini

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Background: the present study explores the role of light and restorativeness on work. According with the Attention Restoration Theory (ART) and a Model of Work Environment, the main idea is that some features of environment, i.e., lighting, influences the direct attention, and so, the performance. Restorativeness refers to the presence/absence level of all the characteristics of physical environment that help to regenerate direct attention. Specifically, lighting can affect level of fascination and attention in one hand; and in other hand promotes several biological functions via pineal gland. Different reviews on this topic show controversial results. In order to bring light on this topic, the hypotheses of this study are that lighting can affect the construct of restorativeness and, in the second time, the restorativeness can affect the performance. Method: the participants are 30 workers of a mechatronic company in the North Italy. Every subject answered to a questionnaire valuing their subjective perceptions of environment in a different way: some objective features of environment, like lighting, temperature and air quality; some subjective perceptions of this environment; finally, the participants answered about their perceived performance. The main attention is on the features of light and his components: visual comfort, general preferences and pleasantness; and the dimensions of the construct of restorativeness; fascination, coherence and being away. The construct of performance per se is conceptualized in three level: individual, team membership and organizational membership; and in three different components: proficiency, adaptability, and proactivity, for a total of 9 subcomponents. Findings: path analysis showed that some characteristics of lighting respectively affected the dimension of fascination; and, as expected, the dimension of fascination affected work performance. Conclusions: The present study is a first pilot step of a wide research. These first results can be summarized with the statement that lighting and restorativeness contribute to explain work performance variability: in details perceptions of visual comfort, satisfaction and pleasantness, and fascination respectively. Results related to fascination are particularly interesting because fascination is conceptualized as the opposite of the construct of direct attention. The main idea is, in order to regenerate attentional capacity, it’s necessary to provide a lacking of attention (fascination). The sample size did not permit to test simultaneously the role of the perceived characteristics of light to see how they differently contribute to predict fascination of the work environment. However, the results highlighted the important role that light could have in predicting restorativeness dimensions and probably with a larger sample we could find larger effects also on work performance. Furthermore, longitudinal data will contribute to better analyze the causal model along time. Applicative implications: the present pilot study highlights the relevant role of lighting and perceived restorativeness in the work environment and the importance to focus attention on light features and the restorative characteristics in the design of work environments.

Keywords: lighting, performance, restorativeness, workplace

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Authors: A. A. James, A. O. Adesanya, M. R. Odekunle, D. G. Yakubu

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This paper examines the development of one step, five hybrid point method for the solution of first order initial value problems. We adopted the method of collocation and interpolation of power series approximate solution to generate a continuous linear multistep method. The continuous linear multistep method was evaluated at selected grid points to give the discrete linear multistep method. The method was implemented using a constant order predictor of order seven over an overlapping interval. The basic properties of the derived corrector was investigated and found to be zero stable, consistent and convergent. The region of absolute stability was also investigated. The method was tested on some numerical experiments and found to compete favorably with the existing methods.

Keywords: interpolation, approximate solution, collocation, differential system, half step, converges, block method, efficiency

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Authors: Cinzia Cruder, Deborah Falla, Francesca Mangili, Laura Azzimonti, Liliana Araujo, Aaron Williamon, Marco Barbero

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Background and aims: According to the existing literature, musicians are at risk to experience a range of musculoskeletal painful conditions. Recently, digital technology has been developed to investigate pain location and pain extent. The aim of this study was to describe pain location and pain extent in musicians using a digital method for pain drawing analysis. Additionally, the association between pain drawing (PD) variables and clinical features in musicians with pain were explored. Materials and Methods: One hundred fifty-eight musicians (90 women and 68 men; age 22.4±3.6 years) were recruited from Swiss and UK conservatoires. Participants were asked to complete a survey including both background musical information and clinical features, the Quick Dash (QD) questionnaire and the digital PDs. Results: Of the 158 participants, 126 musicians (79.7%) reported having pain, with more prevalence in the areas of the neck and shoulders, the lower back and the right arm. The mean of pain extent was 3.1% ±6.5. The mean of QD was larger for musicians showing the presence of pain than for those without pain. Additionally, the results indicated a positive correlation between QD score and pain extent, and there were significant correlations between age and pain intensity, as well as between pain extent and pain intensity. Conclusions: The high prevalence of pain among musicians has been confirmed using a digital PD. In addition, positive correlations between pain extent and upper limb disability has been demonstrated. Our findings highlight the need for effective prevention and treatment strategies for musicians.

Keywords: pain location, pain extent, musicians, pain drawings

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Authors: Debrah Mtshelwane, Alewyn Nel, Lizelle Brink

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Social desirability is an important topic to study. It may be possible that different cultures experience social desirability in different ways. Different cultural groups exist within South Africa, however the focus of this study is specifically in the Zulu culture. This research aims to explore social desirability from an emic perspective within the social constructivist paradigm among individuals within the Zulu culture. The researcher intended to identify those features Zulu individuals deem as socially desirable and undesirable from their cultural viewpoint. The research was conducted using a qualitative research design and the constructivism paradigm was utilised in this study. Combined purposive and quota non-probability sampling was employed for this study. A sample of 30 employees (N = 30) working in various organisations from the provinces of Gauteng and KwaZulu-Natal formed part of this study and data were collected through semi-structured interviews. Thematic analysis was used to analyse the data. The main findings showed that Zulu people regard certain behaviours and actions as socially desirable and others as undesirable. The following are considered socially desirable: Conscientiousness, dominance, subjective expectations and positive relations, these are the themes that were reported on the most. These are positive features in the Zulu culture, and they reflect on behaviour patterns, attitudes and manners that people display, which are also seen as acceptable and good in the Zulu culture. The following are regarded as socially undesirable features that were identified by people who belong to the Zulu culture, the themes that were identified as undesirable are: non-conscientiousness, non-dominance (male), dominance (females), tradition, negative relations and subjective expectations. This study creates awareness on social desirability in the workplace and provides basic tools to management on how to deal with such behaviours relating to this phenomenon in the workplace. This knowledge informs employees on the concept of socially desirable behaviour, and provide more insight into behaviours and/or emotions Zulu individuals. The outcome of this study provided new indigenous, empirical knowledge on the phenomenon of social desirability within the South African context.

Keywords: cultural diversity, emic perspective, social constructivism paradigm, social desirability, Zulu culture

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Authors: Steffy Maria Joseph, Abdu Rahiman V, Abdul Hameed K. M.

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Online handwritten character recognition is a challenging field in Artificial Intelligence. The classification success rate of current techniques decreases when the dataset involves similarity and complexity in stroke styles, number of strokes and stroke characteristics variations. Malayalam is a complex south indian language spoken by about 35 million people especially in Kerala and Lakshadweep islands. In this paper, we consider the significant feature extraction for the similar stroke styles of Malayalam. This extracted feature set are suitable for the recognition of other handwritten south indian languages like Tamil, Telugu and Kannada. A classification scheme based on support vector machines (SVM) is proposed to improve the accuracy in classification and recognition of online malayalam handwritten characters. SVM Classifiers are the best for real world applications. The contribution of various features towards the accuracy in recognition is analysed. Performance for different kernels of SVM are also studied. A graphical user interface has developed for reading and displaying the character. Different writing styles are taken for each of the 44 alphabets. Various features are extracted and used for classification after the preprocessing of input data samples. Highest recognition accuracy of 97% is obtained experimentally at the best feature combination with polynomial kernel in SVM.

Keywords: SVM, matlab, malayalam, South Indian scripts, onlinehandwritten character recognition

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Authors: Mojtaba Heydarizad

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Andarokh basin is one of the main karstic regions in Khorasan Razavi province NE Iran. This basin is part of Kopeh-Dagh mega zone extending from Caspian Sea in the east to northern Afghanistan in the west. This basin is covered by Mozdooran Formation, Ngr evaporative formation and quaternary alluvium deposits in descending order of age. Mozdooran carbonate formation is notably karstified. The main surface karstic features in Mozdooran formation are Groove karren, Cleft karren, Rain pit, Rill karren, Tritt karren, Kamintza, Domes, and Table karren. In addition to surface features, deep karstic feature Andarokh Cave also exists in the region. Studying Ca, Mg, Mn, Sr, Fe concentration and Sr/Mn ratio in Mozdooran formation samples with distance to main faults and joints system using PCA analyses demonstrates intense meteoric digenesis role in controlling carbonate rock geochemistry. The karst evaluation in Andarokh basin varies from early stages 'deep seated karst' in Mesozoic to mature karstic system 'Exhumed karst' in quaternary period. Andarokh cave (the main cave in Andarokh basin) is rudimentary branch work consists of three passages of A, B and C and two entrances Andarokh and Sky.

Keywords: Andarokh basin, Andarokh cave, geochemical analyses, karst evaluation

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Authors: Eyad Almaita

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In this paper, a novel adaptive Radial Basis Function Neural Networks (RBFNN) algorithm is used to forecast the hour by hour electrical load demand in Jordan. A small and effective RBFNN model is used to forecast the hourly total load demand based on a small number of features. These features are; the load in the previous day, the load in the same day in the previous week, the temperature in the same hour, the hour number, the day number, and the day type. The proposed adaptive RBFNN model can enhance the reliability of the conventional RBFNN after embedding the network in the system. This is achieved by introducing an adaptive algorithm that allows the change of the weights of the RBFNN after the training process is completed, which will eliminates the need to retrain the RBFNN model again. The data used in this paper is real data measured by National Electrical Power co. (Jordan). The data for the period Jan./2012-April/2013 is used train the RBFNN models and the data for the period May/2013- Sep. /2013 is used to validate the models effectiveness.

Keywords: load forecasting, adaptive neural network, radial basis function, short-term, electricity consumption

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Authors: Oladejo Olagoke Peter, Adagunodo T. A., Ogunkoya C. O.

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The research investigated the arrangement of some geological features under Ilesa employing aeromagnetic data. The obtained data was subjected to various data filtering and processing techniques, which are Total Horizontal Derivative (THD), Depth Continuation and Analytical Signal Amplitude using Geosoft Oasis Montaj 6.4.2 software. The Reduced to the Equator –Total Magnetic Intensity (TRE-TMI) outcomes reveal significant magnetic anomalies, with high magnitude (55.1 to 155 nT) predominantly at the Northwest half of the area. Intermediate magnetic susceptibility, ranging between 6.0 to 55.1 nT, dominates the eastern part, separated by depressions and uplifts. The southern part of the area exhibits a magnetic field of low intensity, ranging from -76.6 to 6.0 nT. The lineaments exhibit varying lengths ranging from 2.5 and 16.0 km. Analyzing the Rose Diagram and the analytical signal amplitude indicates structural styles mainly of E-W and NE-SW orientations, particularly evident in the western, SW and NE regions with an amplitude of 0.0318nT/m. The identified faults in the area demonstrate orientations of NNW-SSE, NNE-SSW and WNW-ESE, situated at depths ranging from 500 to 750 m. Considering the divergence magnetic susceptibility, structural style or orientation of the lineaments, identified fault and their depth, these lithological features could serve as a valuable foundation for assessing ground motion, particularly in the presence of sufficient seismic energy.

Keywords: lineament, aeromagnetic, anomaly, fault, magnetic

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Authors: Yanmeng Liu

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This article analyzes and compares the linguistic differences between machine translation and manual translation, through a case study of the book Gone with the Wind. As an important carrier of human feeling and thinking, the literature translation poses a huge difficulty for machine translation, and it is supposed to expose distinct translation features apart from manual translation. In order to display linguistic features objectively, tentative uses of computerized and statistical evidence to the systematic investigation of large scale translation corpora by using quantitative methods have been deployed. This study compiles bilingual corpus with four versions of Chinese translations of the book Gone with the Wind, namely, Piao by Chunhai Fan, Piao by Huairen Huang, translations by Google Translation and Baidu Translation. After processing the corpus with the software of Stanford Segmenter, Stanford Postagger, and AntConc, etc., the study analyzes linguistic data and answers the following questions: 1. How does the machine translation differ from manual translation linguistically? 2. Why do these deviances happen? This paper combines translation study with the knowledge of corpus linguistics, and concretes divergent linguistic dimensions in translated text analysis, in order to present linguistic deviances in manual and machine translation. Consequently, this study provides a more accurate and more fine-grained understanding of machine translation products, and it also proposes several suggestions for machine translation development in the future.

Keywords: corpus-based analysis, linguistic deviances, machine translation, statistical evidence

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Authors: Raees Khan, Sheikh Z. Ul Abidin, Abdul S. Mumtaz, Jie Liu

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The present study is intended to assess gymnosperms pollen flora of Pakistan using Light Microscope (LM) and Scanning Electron Microscopy (SEM) for its taxonomic significance in identification of gymnosperms. Pollens of 35 gymnosperm species (12 genera and five families) were collected from its various distributional sites of gymnosperms in Pakistan. LM and SEM were used to investigate different palyno-morphological characteristics. Five pollen types (i.e., Inaperturate, Monolete, Monoporate, Vesiculate-bisaccate, and Polyplicate) were observed. In equatorial view seven types of pollens were observed, in which ten species were sub-angular, nine species were triangular, six species were perprolate, three species were rhomboidal, three species were semi-angular, two species were rectangular and two species were prolate. While five types of pollen were observed in polar view, in which ten species were spheroidal, nine species were angular, eight were interlobate, six species were circular, and two species were elliptic. Eighteen species have rugulate and 17 species has faveolate ornamentation. Eighteen species have verrucate and 17 have gemmate type sculpturing. The data was analysed through cluster analysis. The study showed that these palyno-morphological features have significance value in classification and identification of gymnosperms. Based on these different palyno-morphological features, a taxonomic key was proposed for the accurate and fast identifications of gymnosperms from Pakistan.

Keywords: gymnosperms, palynology, Pakistan, taxonomy

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Authors: Mithil Pandey, Ragunathan Bala Subramanian

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One of the major conversion technologies in the oil refinery industry is Fluid catalytic cracking (FCC) which produces the majority of the world’s gasoline. Some useful products are generated from the vacuum gas oil, heavy gas oil and residue feedstocks by the FCC unit in an oil refinery. Moreover, Zeolite catalysts (zeo-catalysts) have found widespread applications and have proved to be substantial and paradigmatic in oil refining and petrochemical processes, such as FCC because of their porous features. Several famous zeo-catalysts have been fabricated and applied in industrial processes as milestones in history, and have brought on huge changes in petrochemicals. So far, more than twenty types of zeolites have been industrially applied, and their versatile porous architectures with their essential features have contributed to affect the catalytic efficiency. This poster depicts the evolution of pore models in zeolite catalysts which are accompanied by an increase in environmental and demands. The crucial roles of modulating pore models are outlined for zeo-catalysts for the enhancement of their catalytic performances in various industrial processes. The development of industrial processes for the FCC process, aromatic conversions and olefin production, makes it obvious that the pore architecture plays a very important role in zeo-catalysis processes. By looking at the different necessities of industrial processes, rational construction of the pore model is critically essential. Besides, the pore structure of the zeolite would have a substantial and direct effect on the utilization efficiency of the zeo-catalyst.

Keywords: catalysts, fluid catalytic cracking, industrial processes, zeolite

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Authors: Tarek Sedki

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Madari gold mine is delineated by latitudes 22° 30' 29" and 22° 32' 33" N and longitudes 36° 24' 03" and 35°11' 44" E. Geologically, Madari rock units are classified into dismembered ophiolites, arc volcanic assemblage, syntectonic metagabbro-diorites and Mineralized quartz diorite and granodiorite. Deposition of gold in area occurred as a direct result of weathering of nearby gold-bearing veins. Main concentrations of gold are supposed to ensue close to the bed rock. Nevertheless, the several shallow channel-fill features covering lag deposits, arising throughout the alluvial fan sequence would definitely contain a percentage of the finer gold due to the limited washing and sorting capacity of the uncommon flood events. Gold deposits arise as disseminated and separate gold with limited pyrite, arsenopyrite and chalcopyrite everywhere veins in the wall rocks and lode gold deposits in quartz veins. In places, the wall rocks, in near district of the quartz vein, are grieved strong silicification, chloritization and pyritization as a result of a metasomatic alteration due to purification of external hydrothermal fluids. Quartz veins are mostly steeply dipping and display banding features and frequently sheared and brecciated.

Keywords: Madari gold mine, placer deposits, southern eastern desert, gold mineralization, quartz veins

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Authors: Abdul Ghani Rajput

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Although monitoring and evaluation concept adopted by Technical Vocational Education and Training (TVET) organization to track the progress over the continuous interval of time based on planned interventions and subsequently, evaluating it for the impact, quality assurance and sustainability. In digital world, TVET providers are giving preference to have real time information to do monitoring of training activities. Identifying the benefits and challenges of digitized monitoring & evaluation real time information system has not been sufficiently tackled in this date. This research paper looks at the impact of digitized M&E in TVET sector by analyzing two case studies and describe the benefits and challenges of using digitized M&E system. Finally, digitized M&E have been identified as carriers for high potential of TVET sector.

Keywords: digitized M&E, innovation, quality assurance, TVET

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Authors: Ceren Kaya, Okan Erkaymaz, Orhan Ayar, Mahmut Özer

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Diabetes Mellitus (Diabetes) is a disease based on insulin hormone disorders and causes high blood glucose. Clinical findings determine that diabetes can be diagnosed by electrophysiological signals obtained from the vital organs. 'Diabetic Retinopathy' is one of the most common eye diseases resulting on diabetes and it is the leading cause of vision loss due to structural alteration of the retinal layer vessels. In this study, features of horizontal and vertical Video-Oculography (VOG) signals have been used to classify non-proliferative and proliferative diabetic retinopathy disease. Twenty-five features are acquired by using discrete wavelet transform with VOG signals which are taken from 21 subjects. Two models, based on multi-layer perceptron and radial basis function, are recommended in the diagnosis of Diabetic Retinopathy. The proposed models also can detect level of the disease. We show comparative classification performance of the proposed models. Our results show that proposed the RBF model (100%) results in better classification performance than the MLP model (94%).

Keywords: diabetic retinopathy, discrete wavelet transform, multi-layer perceptron, radial basis function, video-oculography (VOG)

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Authors: Yao-Hong Tsai

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Due to the sensor technology, video surveillance has become the main way for security control in every big city in the world. Surveillance is usually used by governments for intelligence gathering, the prevention of crime, the protection of a process, person, group or object, or the investigation of crime. Many surveillance systems based on computer vision technology have been developed in recent years. Moving target tracking is the most common task for Unmanned Aerial Vehicle (UAV) to find and track objects of interest in mobile aerial surveillance for civilian applications. The paper is focused on vision-based collision avoidance for UAVs by recurrent neural networks. First, images from cameras on UAV were fused based on deep convolutional neural network. Then, a recurrent neural network was constructed to obtain high-level image features for object tracking and extracting low-level image features for noise reducing. The system distributed the calculation of the whole system to local and cloud platform to efficiently perform object detection, tracking and collision avoidance based on multiple UAVs. The experiments on several challenging datasets showed that the proposed algorithm outperforms the state-of-the-art methods.

Keywords: unmanned aerial vehicle, object tracking, deep learning, collision avoidance

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Authors: Yumei Wu, Xiaoyan Dang, Shenglong Yang, Shengmao Zhang

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The East China Sea is one of four main seas in China, where there are many fishery resources. Some important fishing grounds, such as Zhousan fishing ground important to society. But the eco-environment is destroyed seriously due to the rapid developing of industry and economy these years. In this paper, about twenty-year satellite data from MODIS and the statistical information of marine environment from the China marine environmental quality bulletin were applied to do the research. The chlorophyll-a concentration data from MODIS were dealt with in the East China Sea and then used to analyze the features and variations of plankton biomass in recent years. The statistics method was used to obtain their spatial and temporal features. The plankton biomass in the Yangtze River estuary and the Taizhou region were highest. The high phytoplankton biomass usually appeared between the 88th day to the 240th day (end-March - August). In the peak time of phytoplankton blooms, the Taizhou islands was the earliest, and the South China Sea was the latest. The intensity and period of phytoplankton blooms were connected with the global climate change. This work give us confidence to use satellite data to do more researches about the China Sea, and it also provides some help for us to know about the eco-environmental variation of the East China Sea and regional effect from global climate change.

Keywords: the East China Sea, phytoplankton biomass, temporal and spatial variation, phytoplankton bloom

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Authors: Yavuz Unal, Kemal Polat, H. Erdinc Kocer

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In this study, a decision support system comprising three stages has been proposed to detect the disc abnormalities of the lumbar region. In the first stage named the feature extraction, T2-weighted sagittal and axial Magnetic Resonance Images (MRI) were taken from 55 people and then 27 appearance and shape features were acquired from both sagittal and transverse images. In the second stage named the feature weighting process, k-means clustering based feature weighting (KMCBFW) proposed by Gunes et al. Finally, in the third stage named the classification process, the classifier algorithms including multi-layer perceptron (MLP- neural network), support vector machine (SVM), Naïve Bayes, and decision tree have been used to classify whether the subject has lumbar disc or not. In order to test the performance of the proposed method, the classification accuracy (%), sensitivity, specificity, precision, recall, f-measure, kappa value, and computation times have been used. The best hybrid model is the combination of k-means clustering based feature weighting and decision tree in the detecting of lumbar disc disease based on both sagittal and axial MR images.

Keywords: lumbar disc abnormality, lumbar MRI, lumbar spine, hybrid models, hybrid features, k-means clustering based feature weighting

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Authors: Majid Habib Khan, Jinwei Zhao, Xinhong Hei, Liu Jiedong, Rana Shahzad Noor, Muhammad Imran

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Deep learning is increasingly employed in image classification, yet the scarcity and high cost of labeled data for training remain a challenge. Limited samples often lead to overfitting due to biased sample distribution. This paper introduces a dynamic distribution calibration method for few-shot learning. Initially, base and new class samples undergo normalization to mitigate disparate feature magnitudes. A pre-trained model then extracts feature vectors from both classes. The method dynamically selects distribution characteristics from base classes (both adjacent and remote) in the embedding space, using a threshold value approach for new class samples. Given the propensity of similar classes to share feature distributions like mean and variance, this research assumes a Gaussian distribution for feature vectors. Subsequently, distributional features of new class samples are calibrated using a corrected hyperparameter, derived from the distribution features of both adjacent and distant base classes. This calibration augments the new class sample set. The technique demonstrates significant improvements, with up to 4% accuracy gains in few-shot classification challenges, as evidenced by tests on miniImagenet and CUB datasets.

Keywords: deep learning, computer vision, image classification, few-shot learning, threshold

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Authors: Natasa Todorovic, Jovana Nikolov

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Guard detector efficiency, cosmic background, and its variation were determinate using ultra low-level liquid scintillation spectrometer Quantulus 1220, equipped with an anti-Compton guard detector, in the surface laboratory at the University of Novi Sad, Serbia, Atmospheric pressure variation has an observable effect on the anti-Compton guard detector count rate. and the cosmic muon flux is lower during a high-pressure period. Also, the guard detector Compton continuum provides a good view of the level of gamma radiation in the laboratory environment. The efficiency of the guard detector in the channel interval from 750 to 1024 was assessed to 93.45%; efficiency in the entire window (channels 1 to 1024) was 75.23%, which is in good agreement with literature data.

Keywords: cosmic radiation, background reduction, liquid scintillation counting, guard detector efficiency

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Authors: S. Mani, M. Kafil, E. Asadi

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Condition Monitoring (CM) of electrical equipment has gained remarkable importance during the recent years; due to huge production losses, substantial imposed costs and increases in vulnerability, risk and uncertainty levels. Power cables feed numerous electrical equipment such as transformers, motors, and electric furnaces; thus their condition assessment is of a very great importance. This paper investigates electrical, structural and environmental failure sources, all of which influence cables' performances and limit their uptimes; and provides a comprehensive framework entailing practical CM guidelines for maintenance of cables in industries. The multilevel CM framework presented in this study covers performance indicative features of power cables; with a focus on both online and offline diagnosis and test scenarios, and covers short-term and long-term threats to the operation and longevity of power cables. The study, after concisely overviewing the concept of CM, thoroughly investigates five major areas of power quality, Insulation Quality features of partial discharges, tan delta and voltage withstand capabilities, together with sheath faults, shield currents and environmental features of temperature and humidity; and elaborates interconnections and mutual impacts between those areas; using mathematical formulation and practical guidelines. Detection, location, and severity identification methods for every threat or fault source are also elaborated. Finally, the comprehensive, practical guidelines presented in the study are presented for the specific case of Electric Arc Furnace (EAF) feeder MV power cables in Mobarakeh Steel Company (MSC), the largest steel company in MENA region, in Iran. Specific technical and industrial characteristics and limitations of a harsh industrial environment like MSC EAF feeder cable tunnels are imposed on the presented framework; making the suggested package more practical and tangible.

Keywords: condition monitoring, diagnostics, insulation, maintenance, partial discharge, power cables, power quality

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Authors: Ferydon Salehifar, Hassan Safarikia, Hossein Boromandfar

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Karkheh plant in Iran's Khuzestan province and is located in the city Andimeshk. The plant has a production capacity of 400 MW units with water and three hours. One of the important parameters of each country's power grid stability is the stability of the power grid is affected by the voltage and frequency In plants, the amount of active power frequency control is done so that when the unit is placed in the frequency control their productivity is a function of frequency and output power varies with frequency. Produced by hydroelectric power plants with the water level behind the dam has a direct relationship And to decrease and increase the water level behind the dam in order to reduce the power output increases But these changes have a different interval is due to some mechanical problems such as turbine cavitation and vibration are limited. In this study, the range of the frequency control can be Karkheh manufacturing plants have been identified and their effectiveness has been determined.

Keywords: Karkheh power, frequency control system, active power, efficiency

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Authors: R. R. Ramsheeja, R. Sreeraj

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For view the internal structures of the human body such as liver, brain, kidney etc have a wide range of different modalities for medical images are provided nowadays. Computer Tomography is one of the most significant medical image modalities. In this paper use CT liver images for study the use of automatic computer aided techniques to calculate the volume of the liver tumor. Segmentation method is used for the detection of tumor from the CT scan is proposed. Gaussian filter is used for denoising the liver image and Adaptive Thresholding algorithm is used for segmentation. Multiple Region Of Interest(ROI) based method that may help to characteristic the feature different. It provides a significant impact on classification performance. Due to the characteristic of liver tumor lesion, inherent difficulties appear selective. For a better performance, a novel proposed system is introduced. Multiple ROI based feature selection and classification are performed. In order to obtain of relevant features for Support Vector Machine(SVM) classifier is important for better generalization performance. The proposed system helps to improve the better classification performance, reason in which we can see a significant reduction of features is used. The diagnosis of liver cancer from the computer tomography images is very difficult in nature. Early detection of liver tumor is very helpful to save the human life.

Keywords: computed tomography (CT), multiple region of interest(ROI), feature values, segmentation, SVM classification

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Authors: Hamid Merzouk, Dajhida Talantikite, Amel Tounsi

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Thin films of ZnS have been deposited by chemical route into acidic medium. The deposition time fixed at 5 hours, and the bath temperature varied from 80° C to 95°C with an interval of 5°C. The X-ray diffraction (XRD), UV/ visible spectrophotometry, Fourier Transform Infrared spectroscopy (FTIR) have been used to study the effect of temperature on the structural and optical properties of ZnS thin films. The XRD spectrum of the ZnS layer obtained shows an increase of peaks intensity of ZnS with increasing bath temperature. The study of optical properties exhibit good transmittance (60–80% in the visible region), and the band gap energy of the ZnS thin film decrease from 3.71 eV to 3.64 eV while the refractive index (n) increase with increasing temperature bath. The FTIR analyze confirm our studies and show characteristics bands of vibration of Zn-S.

Keywords: ZnS thin films, XRD spectra, optical gap, XRD

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Authors: T. Garba, Y. Y. Babanyara, T. O. Quddus, A. K. Mukatari

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Human activities make environmental parameters in order to keep on changing globally. While some changes are necessary and beneficial to flora and fauna, others have serious consequences threatening the survival of their natural habitat if these changes are not properly monitored and mitigated. In-situ assessments are characterized by many challenges due to the absence of time series data and sometimes areas to be observed or monitored are inaccessible. Satellites Remote Sensing provide us with the digital images of same geographic areas within a pre-defined interval. This makes it possible to monitor and detect changes of environmental phenomena. This paper, therefore, reviewed the commonly use changes detection techniques globally such as image differencing, image rationing, image regression, vegetation index difference, change vector analysis, principal components analysis, multidate classification, post-classification comparison, and visual interpretation. The paper concludes by suggesting the use of more than one technique.

Keywords: environmental phenomena, change detection, monitor, techniques

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Authors: Ayesha Sanjana Kawser Parsha

Abstract:

S-acylation is an irreversible bond in which cysteine residues are linked to fatty acids palmitate (74%) or stearate (22%), either at the COOH or NH2 terminal, via a thioester linkage. There are several experimental methods that can be used to identify the S-palmitoylation site; however, since they require a lot of time, computational methods are becoming increasingly necessary. There aren't many predictors, however, that can locate S- palmitoylation sites in Arabidopsis Thaliana with sufficient accuracy. This research is based on the importance of building a better prediction tool. To identify the type of machine learning algorithm that predicts this site more accurately for the experimental dataset, several prediction tools were examined in this research, including the GPS PALM 6.0, pCysMod, GPS LIPID 1.0, CSS PALM 4.0, and NBA PALM. These analyses were conducted by constructing the receiver operating characteristics plot and the area under the curve score. An AI-driven deep learning-based prediction tool has been developed utilizing the analysis and three sequence-based input data, such as the amino acid composition, binary encoding profile, and autocorrelation features. The model was developed using five layers, two activation functions, associated parameters, and hyperparameters. The model was built using various combinations of features, and after training and validation, it performed better when all the features were present while using the experimental dataset for 8 and 10-fold cross-validations. While testing the model with unseen and new data, such as the GPS PALM 6.0 plant and pCysMod mouse, the model performed better, and the area under the curve score was near 1. It can be demonstrated that this model outperforms the prior tools in predicting the S- palmitoylation site in the experimental data set by comparing the area under curve score of 10-fold cross-validation of the new model with the established tools' area under curve score with their respective training sets. The objective of this study is to develop a prediction tool for Arabidopsis Thaliana that is more accurate than current tools, as measured by the area under the curve score. Plant food production and immunological treatment targets can both be managed by utilizing this method to forecast S- palmitoylation sites.

Keywords: S- palmitoylation, ROC PLOT, area under the curve, cross- validation score

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Authors: Tran Gia Khanh, Dao Phuong Nam, Do Trong Tan, Nguyen Van Huong, Mai Xuan Sinh

Abstract:

This work presents the problem of tube-based robust model predictive controller for a class of continuous-time systems in the presence of input disturbances. The main objective is to point out the state trajectory of closed system being maintained inside a sequence of tubes. An estimation of attraction region of the closed system is pointed out based on input state stability (ISS) theory and linearized model in each time interval. The theoretical analysis and simulation results demonstrate the performance of the proposed algorithm for a wheeled inverted pendulum system.

Keywords: input state stability (ISS), tube-based robust MPC, continuous-time nonlinear systems, wheeled inverted pendulum

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Authors: Ponghyung Lee

Abstract:

This study seeks to investigate the variations occurring to Korean consonantal variations center around laryngeal features of the concerned sounds, to the exclusion of others. Our fundamental premise is that the weak contrast associated with concerned segments might be held accountable for the oscillation of the status quo of the concerned consonants. What is more, we assume that an array of notions as a measure of communicative efficiency of linguistic units would be significantly influential on triggering those variations. To this end, we have tried to compute the surprisal, entropic contribution, and relative contrastiveness associated with Korean obstruent consonants. What we found therein is that the Information-theoretic perspective is compelling enough to lend support our approach to a considerable extent. That is, the variant realizations, chronologically and stylistically, prove to be profoundly affected by a set of Information-theoretic factors enumerated above. When it comes to the biblical proper names, we use Georgetown University CQP Web-Bible corpora. From the 8 texts (4 from Old Testament and 4 from New Testament) among the total 64 texts, we extracted 199 samples. We address the issue of laryngeal feature variations associated with Korean obstruent consonants under the presumption that the variations stem from the weak contrast among the triad manifestations of laryngeal features. The variants emerge from diverse sources in chronological and stylistic senses: Christianity biblical texts, ordinary casual speech, the shift of loanword adaptation over time, and ideophones. For the purpose of discussing what they are really like from the perspective of Information Theory, it is necessary to closely look at the data. Among them, the massive changes occurring to loanword adaptation of proper nouns during the centennial history of Korean Christianity draw our special attention. We searched 199 types of initially capitalized words among 45,528-word tokens, which account for around 5% of total 901,701-word tokens (12,786-word types) from Georgetown University CQP Web-Bible corpora. We focus on the shift of the laryngeal features incorporated into word-initial consonants, which are available through the two distinct versions of Korean Bible: one came out in the 1960s for the Protestants, and the other was published in the 1990s for the Catholic Church. Of these proper names, we have closely traced the adaptation of plain obstruents, e. g. /b, d, g, s, ʤ/ in the sources. The results show that as much as 41% of the extracted proper names show variations; 37% in terms of aspiration, and 4% in terms of tensing. This study set out in an effort to shed light on the question: to what extent can we attribute the variations occurring to the laryngeal features associated with Korean obstruent consonants to the communicative aspects of linguistic activities? In this vein, the concerted effects of the triad, of surprisal, entropic contribution, and relative contrastiveness can be credited with the ups and downs in the feature specification, despite being contentiousness on the role of surprisal to some extent.

Keywords: entropic contribution, laryngeal feature variation, relative contrastiveness, surprisal

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Authors: Mustafa Ümi̇t Ünal, Nafi̇z Çeli̇ktaş, Aysun Şener, Sara Betül Dolgun, Duygu Keser

Abstract:

The aim of this study was to compare acid and base pretreatment of switchgrass for bioethanol production. Switchgrass was pretreated with sulfuric acid and sodium hydroxide at 0.5, 1.0 and 1.5% (v/v) at 120, 140, 180 °C for 10, 60 and 90. Optimization of enzymatic hydrolysis of the pretreated switchgrass samples were carried out using three different enzyme mixtures (22.5 mg cellulase and 75 mg cellobiase /g biomass; 45 mg cellulase and 150 mg cellobiase /g biomass; 90 mg cellulase and 300 mg cellobiase /g biomass). Samples were removed at 24-h interval for fermentable sugar analyses with HPLC. The results showed that use of 90 mg cellulase and 300 mg cellobiase/g biomass resulted in the highest fermentable sugar formation. Furthermore, the highest fermentable sugar yield was obtained by pretreatment at 120 °C for 10 min using 1.0 % sodium hydroxide.

Keywords: switchgrass, acid pretreatment, enzymatic hydrolysis, base pretreatment, ethanol production

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Authors: Bin Liu

Abstract:

MicroRNAs (miRNAs) are small non-coding RNA molecules, functioning in transcriptional and post-transcriptional regulation of gene expression. The discrimination of the real pre-miRNAs from the false ones (such as hairpin sequences with similar stem-loops) is necessary for the understanding of miRNAs’ role in the control of cell life and death. Since both their small size and sequence specificity, it cannot be based on sequence information alone but requires structure information about the miRNA precursor to get satisfactory performance. Kmers are convenient and widely used features for modeling the properties of miRNAs and other biological sequences. However, Kmers suffer from the inherent limitation that if the parameter K is increased to incorporate long range effects, some certain Kmer will appear rarely or even not appear, as a consequence, most Kmers absent and a few present once. Thus, the statistical learning approaches using Kmers as features become susceptible to noisy data once K becomes large. In this study, we proposed a Gapped k-mer approach to overcome the disadvantages of Kmers, and applied this method to the field of miRNA prediction. Combined with the structure status composition, a classifier called imiRNA-GSSC was proposed. We show that compared to the original imiRNA-kmer and alternative approaches. Trained on human miRNA precursors, this predictor can achieve an accuracy of 82.34 for predicting 4022 pre-miRNA precursors from eleven species.

Keywords: gapped k-mer, imiRNA-GSSC, microRNA precursor, support vector machine

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Authors: Juan C. Sanchez, Jose L. Endrino, Alejandro Toro, Hugo A. Estupinan, Glenn Leighton

Abstract:

For years, the reduction of friction and wear has been a matter of interest in the engineering field. Several solutions have been proposed to address this issue, including the use of lubricants and coatings to reduce the frictional forces and to increase the surface wear resistance. Alternatively, texturing processes have been used in a wide variety of materials, in many cases inspired in natural surfaces. Nature has shown how species adapt to the environment and the engineers try to understand natural surfaces for particular applications by analyzing outstanding species such as gecko for high adhesion, lotus leaves for hydrophobicity, sharks for reduced flow resistance and snakes for optimized frictional response. Texturized surfaces have shown a superior performance in terms of the frictional response in many situations, and the control of its behavior greatly depends on the manufacturing process. The focus of this work is to evaluate the tribological behavior of AISI 52100 steel samples texturized by Photochemical Machining (PCM). The surface texture was inspired by several features of the snakeskin such as aspect ratio of fibrils and mean fibril spacing. Two coatings were applied on the texturized surface, namely Diamond-like Carbon (DLC) and Molybdenum Disulphide (MoS₂), and their tribological behavior after pin-on-disk tests were compared with that of the non-texturized and uncovered surfaces. The samples were characterised through Stereoscopic Microscope (SM), Scanning Electron Microscope (SEM), Optical Microscope (OM), Profilometer, Raman Spectrometer (RS) and X-Ray Diffractometer (XRD). The Coefficient of Friction (COF) measured in pin-on-disk tests showed correlations with the sliding direction (relative to the texture features) and the aspect ratio of the texture features. Regarding the coated surfaces, the DLC and MoS₂ coating had a good performance in terms of wear rate and coefficient of friction compared with the uncoated and non-texturized surfaces. On the other hand, for the uncoated surfaces, the texture showed an influence in the tribological performance with respect to the non-texturized surface.

Keywords: coating, coefficient of friction, deterministic surface, photochemical machining

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