Search results for: conventional statistical methods

Authors: H. J. Wattimanela, U. S. Passaribu, N. T. Puspito, S. W. Indratno

Abstract:

Molluca Collision Zone is located at the junction of the Eurasian, Australian, Pacific and the Philippines plates. Between the Sangihe arc, west of the collision zone, and to the east of Halmahera arc is active collision and convex toward the Molluca Sea. This research will analyze the behavior of earthquake occurrence in Molluca Collision Zone related to the distributions of an earthquake in each partition regions, determining the type of distribution of a occurrence earthquake of partition regions, and the mean occurence of earthquakes each partition regions, and the correlation between the partitions region. We calculate number of earthquakes using partition method and its behavioral using conventional statistical methods. In this research, we used data of shallow earthquakes type and its magnitudes ≥4 SR (period 1964-2013). From the results, we can classify partitioned regions based on the correlation into two classes: strong and very strong. This classification can be used for early warning system in disaster management.

Keywords: Molluca Collision Zone, partition regions, conventional statistical methods, Earthquakes, classifications, disaster management.

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Authors: Khalid Elasnaoui, Brahim Aksasse, Mohammed Ouanan

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In this paper, we are interested in the problem of finding similar images in a large database. For this purpose we propose a new algorithm based on a combination of the 2-D histogram intersection in the HSV space and statistical moments. The proposed histogram is based on a 3x3 window and not only on the intensity of the pixel. This approach overcome the drawback of the conventional 1-D histogram which is ignoring the spatial distribution of pixels in the image, while the statistical moments are used to escape the effects of the discretisation of the color space which is intrinsic to the use of histograms. We compare the performance of our new algorithm to various methods of the state of the art and we show that it has several advantages. It is fast, consumes little memory and requires no learning. To validate our results, we apply this algorithm to search for similar images in different image databases.

Keywords: 2-D histogram, Statistical moments, Indexing, Similarity distance, Histograms intersection.

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Authors: Yunus Doğan, Ahmet Durap

Abstract:

Coastal regions are the one of the most commonly used places by the natural balance and the growing population. In coastal engineering, the most valuable data is wave behaviors. The amount of this data becomes very big because of observations that take place for periods of hours, days and months. In this study, some statistical methods such as the wave spectrum analysis methods and the standard statistical methods have been used. The goal of this study is the discovery profiles of the different coast areas by using these statistical methods, and thus, obtaining an instance based data set from the big data to analysis by using data mining algorithms. In the experimental studies, the six sample data sets about the wave behaviors obtained by 20 minutes of observations from Mersin Bay in Turkey and converted to an instance based form, while different clustering techniques in data mining algorithms were used to discover similar coastal places. Moreover, this study discusses that this summarization approach can be used in other branches collecting big data such as medicine.

Keywords: Clustering algorithms, coastal engineering, data mining, data summarization, statistical methods.

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Authors: Bharathi P. T, P. Subashini

Abstract:

Ice cover County has a significant impact on rivers as it affects with the ice melting capacity which results in flooding, restrict navigation, modify the ecosystem and microclimate. River ices are made up of different ice types with varying ice thickness, so surveillance of river ice plays an important role. River ice types are captured using infrared imaging camera which captures the images even during the night times. In this paper the river ice infrared texture images are analysed using first-order statistical methods and secondorder statistical methods. The second order statistical methods considered are spatial gray level dependence method, gray level run length method and gray level difference method. The performance of the feature extraction methods are evaluated by using Probabilistic Neural Network classifier and it is found that the first-order statistical method and second-order statistical method yields low accuracy. So the features extracted from the first-order statistical method and second-order statistical method are combined and it is observed that the result of these combined features (First order statistical method + gray level run length method) provides higher accuracy when compared with the features from the first-order statistical method and second-order statistical method alone.

Keywords: Gray Level Difference Method, Gray Level Run Length Method, Kurtosis, Probabilistic Neural Network, Skewness, Spatial Gray Level Dependence Method.

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Authors: M. Ghobeiti-Hasab

Abstract:

Magnetic powder of Sr-ferrite was prepared by conventional and sol-gel auto-combustion methods. In conventional method, strontium carbonate and ferric oxide powders were mixed together and then mixture was calcined. In sol-gel auto-combustion method, a solution containing strontium nitrate, ferric nitrate and citric acid was heated until the combustion took place automatically; then, as-burnt powder was calcined. Thermal behavior, phase identification, morphology and magnetic properties of powders obtained by these two methods were compared by DTA, XRD, SEM and VSM techniques. According to the results of DTA analysis, formation temperature of Sr-ferrite obtained by conventional and solgel auto-combustion methods were 1300°C and 1000°C, respectively. XRD results confirmed the formation of pure Sr-ferrite at the mentioned temperatures. Plate and hexagonal-shape particles of Srferrite were observed using SEM. The Sr-ferrite powder obtained by sol-gel auto-combustion method had saturation magnetization of 66.03 emu/g and coercivity of 5731 Oe in comparison with values of 58.20 emu/g and 4378 Oe obtained by conventional method.

Keywords: Sr-ferrite, Sol-gel, Magnetic properties, Calcination.

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Authors: Ayaz Keerio, Bhargav Kumar Mitra, Philip Birch, Rupert Young, Chris Chatwin

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Preprocessing of speech signals is considered a crucial step in the development of a robust and efficient speech or speaker recognition system. In this paper, we present some popular statistical outlier-detection based strategies to segregate the silence/unvoiced part of the speech signal from the voiced portion. The proposed methods are based on the utilization of the 3 σ edit rule, and the Hampel Identifier which are compared with the conventional techniques: (i) short-time energy (STE) based methods, and (ii) distribution based methods. The results obtained after applying the proposed strategies on some test voice signals are encouraging.

Keywords: STE based methods, Mahalanobis distance, 3 edit σ rule, Hampel Identifier.

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Authors: Dimitra Alexiou

Abstract:

During the last 10 years, in spite of the economic crisis, the number of tourists arriving in Greece has increased, particularly during the tourist season from April to October. In this paper, the number of annual tourist arrivals is studied to explore their preferences with regard to the month of travel, the selected destinations, as well the amount of money spent. The collected data are processed with statistical methods, yielding numerical and graphical results. From the computation of statistical parameters and the forecasting with exponential smoothing, useful conclusions are arrived at that can be used by the Greek tourism authorities, as well as by tourist organizations, for planning purposes for the coming years. The results of this paper and the computed forecast can also be used for decision making by private tourist enterprises that are investing in Greece. With regard to the statistical methods, the method of Simple Exponential Smoothing of time series of data is employed. The search for a best forecast for 2017 and 2018 provides the value of the smoothing coefficient. For all statistical computations and graphics Microsoft Excel is used.

Keywords: Tourism, statistical methods, exponential smoothing, land spatial planning, economy, Microsoft Excel.

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Authors: Ganesh D. Kale, Sheela N. Vadsola

Abstract:

Soil erosion is the most serious problem faced at global and local level. So planning of soil conservation measures has become prominent agenda in the view of water basin managers. To plan for the soil conservation measures, the information on soil erosion is essential. Universal Soil Loss Equation (USLE), Revised Universal Soil Loss Equation 1 (RUSLE1or RUSLE) and Modified Universal Soil Loss Equation (MUSLE), RUSLE 1.06, RUSLE1.06c, RUSLE2 are most widely used conventional erosion estimation methods. The essential drawbacks of USLE, RUSLE1 equations are that they are based on average annual values of its parameters and so their applicability to small temporal scale is questionable. Also these equations do not estimate runoff generated soil erosion. So applicability of these equations to estimate runoff generated soil erosion is questionable. Data used in formation of USLE, RUSLE1 equations was plot data so its applicability at greater spatial scale needs some scale correction factors to be induced. On the other hand MUSLE is unsuitable for predicting sediment yield of small and large events. Although the new revised forms of USLE like RUSLE 1.06, RUSLE1.06c and RUSLE2 were land use independent and they have almost cleared all the drawbacks in earlier versions like USLE and RUSLE1, they are based on the regional data of specific area and their applicability to other areas having different climate, soil, land use is questionable. These conventional equations are applicable for sheet and rill erosion and unable to predict gully erosion and spatial pattern of rills. So the research was focused on development of nonconventional (other than conventional) methods of soil erosion estimation. When these non-conventional methods are combined with GIS and RS, gives spatial distribution of soil erosion. In the present paper the review of literature on non- conventional methods of soil erosion estimation supported by GIS and RS is presented.

Keywords: Conventional methods, GIS, non-conventionalmethods, remote sensing, soil erosion modeling

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Authors: G. N. Srinivasan, G. Shobha

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This paper presents an overview of the methodologies and algorithms for statistical texture analysis of 2D images. Methods for digital-image texture analysis are reviewed based on available literature and research work either carried out or supervised by the authors.

Keywords: Image Texture, Texture Analysis, Statistical Approaches, Structural approaches, spectral approaches, Morphological approaches, Fractals, Fourier Transforms, Gabor Filters, Wavelet transforms.

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Authors: Mohamed Saad Ahmed Hussien

Abstract:

This paper discusses the risk management in Islamic banks and aims to determine the difference in the practices and methods of risk management in those banks compared to the conventional banks, and to make a case study of the biggest Islamic bank in Egypt (Faisal Islamic Bank of Egypt) to identify the most important financial risks faced and how to manage those risks. It was found that Islamic banks face two types of risks. The first type is similar to the risks in conventional banks; the second type is the additional risks which facing the Islamic banks only as a result of some Islamic modes of financing. With regard to the risk management, Islamic banks such as conventional banks applied the regulatory rules issued by the Central Banks and the Basel Committee; Islamic banks also applied the instructions and procedures issued by the Islamic Financial Services Board (IFSB). Also, Islamic banks are similar to the conventional banks in the practices and methods which they use to manage the risks. And there are some factors that may affect the risk management in Islamic banks, such as the size of the bank and the efficiency of the administration and the staff of the bank.

Keywords: Conventional banks, Faisal Islamic Bank of Egypt, Islamic banks, risk management.

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Authors: Jihye Jeon

Abstract:

This paper analyzes the conceptual framework of three statistical methods, multiple regression, path analysis, and structural equation models. When establishing research model of the statistical modeling of complex social phenomenon, it is important to know the strengths and limitations of three statistical models. This study explored the character, strength, and limitation of each modeling and suggested some strategies for accurate explaining or predicting the causal relationships among variables. Especially, on the studying of depression or mental health, the common mistakes of research modeling were discussed.

Keywords: Multiple regression, path analysis, structural equation models, statistical modeling, social and psychological phenomenon.

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Authors: Sung-Hae Jun, Kyung-Whan Oh

Abstract:

Statistical learning theory was developed by Vapnik. It is a learning theory based on Vapnik-Chervonenkis dimension. It also has been used in learning models as good analytical tools. In general, a learning theory has had several problems. Some of them are local optima and over-fitting problems. As well, statistical learning theory has same problems because the kernel type, kernel parameters, and regularization constant C are determined subjectively by the art of researchers. So, we propose an evolutionary statistical learning theory to settle the problems of original statistical learning theory. Combining evolutionary computing into statistical learning theory, our theory is constructed. We verify improved performances of an evolutionary statistical learning theory using data sets from KDD cup.

Keywords: Evolutionary computing, Local optima, Over-fitting, Statistical learning theory

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Authors: K. Afsahi, M. Soheilifar, S. H. Hosseini, O. S. Esmaeili, R. Kezemi, N. Mehrbod, N. Vahed, T. Hajiahmad, N. N. Ansari

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Background: Stroke is a disabling neurological disease. Rehabilitative therapies are important treatment methods. This clinical trial was done to compare the effects of virtual reality (VR) beside conventional rehabilitation versus conventional rehabilitation alone on the spasticity and motor function in stroke patients. Materials and methods: In this open-label randomized controlled clinical trial, 40 consecutive patients with stable first-ever ischemic stroke in the past three to 12 months that were referred to a rehabilitation clinic in Tehran, Iran in 2020 were enrolled. After signing the informed written consent form, subjects were randomly assigned by block randomization of five in each block as cases with 1:1 into two groups of 20 cases; conventional plus VR therapy group: 45-minute conventional therapy session plus 15-minute VR therapy, and conventional group: 60-minute conventional therapy session. VR rehabilitation is designed and developed with different stages. Outcomes were Modified Ashworth scale, Recovery Stage score for motor function, range of motion (ROM) of shoulder abduction/wrist extension, and patients’ satisfaction rate. Data were compared after study termination. Results: The satisfaction rate among the patients was significantly better in combination group (P = 0.003). Only wrist extension was varied between groups and was better in combination group. The variables generally had statistically significant difference (P < 0.05). Conclusion: VR plus conventional rehabilitation therapy is superior versus conventional rehabilitation alone on the wrist and elbow spasticity and motor function in patients with stroke.

Keywords: Stroke, virtual therapy, efficacy, rehabilitation.

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Authors: Jihyung Kim, Taejin Kim, Sungho Park, Jun-Dong Cho

Abstract:

A conventional binding method for low power in a high-level synthesis mainly focuses on finding an optimal binding for an assumed input data, and obtains only one binding table. In this paper, we show that a binding method which uses multiple binding tables gets better solution compared with the conventional methods which use a single binding table, and propose a dynamic bus binding scheme for low power using multiple binding tables. The proposed method finds multiple binding tables for the proper partitions of an input data, and switches binding tables dynamically to produce the minimum total switching activity. Experimental result shows that the proposed method obtains a binding solution having 12.6-28.9% smaller total switching activity compared with the conventional methods.

Keywords: low power, bus binding, switching activity, multiplebinding tables

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Authors: Khaled M. Alhawiti

Abstract:

This research study aims to present a retrospective study about speech recognition systems and artificial intelligence. Speech recognition has become one of the widely used technologies, as it offers great opportunity to interact and communicate with automated machines. Precisely, it can be affirmed that speech recognition facilitates its users and helps them to perform their daily routine tasks, in a more convenient and effective manner. This research intends to present the illustration of recent technological advancements, which are associated with artificial intelligence. Recent researches have revealed the fact that speech recognition is found to be the utmost issue, which affects the decoding of speech. In order to overcome these issues, different statistical models were developed by the researchers. Some of the most prominent statistical models include acoustic model (AM), language model (LM), lexicon model, and hidden Markov models (HMM). The research will help in understanding all of these statistical models of speech recognition. Researchers have also formulated different decoding methods, which are being utilized for realistic decoding tasks and constrained artificial languages. These decoding methods include pattern recognition, acoustic phonetic, and artificial intelligence. It has been recognized that artificial intelligence is the most efficient and reliable methods, which are being used in speech recognition.

Keywords: Speech recognition, acoustic phonetic, artificial intelligence, Hidden Markov Models (HMM), statistical models of speech recognition, human machine performance.

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Authors: Ibtihaj Al-Siyabi

Abstract:

The crisis of COVID-19 posed enormous challenges to the statistical providers. While official statistics were disrupted by the pandemic and related containment measures, there was a growing and pressing need for real-time data and statistics to inform decisions. This paper gives an account of the way the pandemic impacted the operations of the National Statistical Offices (NSOs) in general in terms of data collection and methods used, and the main challenges encountered by them based on international surveys. It highlights the performance of the Statistical Centre for the Cooperation Council for the Arab Countries of the Gulf, GCC-STAT, and its responsiveness to the pandemic placing special emphasis on environmental statistics. The paper concludes by confirming the GCC-STAT’s resilience and success in facing the challenges.

Keywords: NSO, COVID-19, pandemic, National Statistical Offices.

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Authors: Nang Thwe Thwe Oo

Abstract:

Traditional object segmentation methods are time consuming and computationally difficult. In this paper, onedimensional object detection along the secant lines is applied. Statistical features of texture images are computed for the recognition process. Example matrices of these features and formulae for calculation of similarities between two feature patterns are expressed. And experiments are also carried out using these features.

Keywords: 1-D object segmentation, secant lines, objectoccurrence(frequency) matrix, contiguity matrix, statistical features.

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Authors: A. Chaouachi, R.M. Kamel, R. Ichikawa, H. Hayashi, K. Nagasaka

Abstract:

This paper presents the applicability of artificial neural networks for 24 hour ahead solar power generation forecasting of a 20 kW photovoltaic system, the developed forecasting is suitable for a reliable Microgrid energy management. In total four neural networks were proposed, namely: multi-layred perceptron, radial basis function, recurrent and a neural network ensemble consisting in ensemble of bagged networks. Forecasting reliability of the proposed neural networks was carried out in terms forecasting error performance basing on statistical and graphical methods. The experimental results showed that all the proposed networks achieved an acceptable forecasting accuracy. In term of comparison the neural network ensemble gives the highest precision forecasting comparing to the conventional networks. In fact, each network of the ensemble over-fits to some extent and leads to a diversity which enhances the noise tolerance and the forecasting generalization performance comparing to the conventional networks.

Keywords: Neural network ensemble, Solar power generation, 24 hour forecasting, Comparative study

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Authors: Yuji Mizuno, Hiroshi Mabuchi

Abstract:

Initial values of reference vectors have significant influence on recognition accuracy in LVQ. There are several existing techniques, such as SOM and k-means, for setting initial values of reference vectors, each of which has provided some positive results. However, those results are not sufficient for the improvement of recognition accuracy. This study proposes an ACO-used method for initializing reference vectors with an aim to achieve recognition accuracy higher than those obtained through conventional methods. Moreover, we will demonstrate the effectiveness of the proposed method by applying it to the wine data and English vowel data and comparing its results with those of conventional methods.

Keywords: Clustering, LVQ, ACO, SOM, k-means.

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Authors: C. Temaneh Nyah

Abstract:

The analysis of electromagnetic environment using deterministic mathematical models is characterized by the impossibility of analyzing a large number of interacting network stations with a priori unknown parameters, and this is characteristic, for example, of mobile wireless communication networks. One of the tasks of the tools used in designing, planning and optimization of mobile wireless network is to carry out simulation of electromagnetic environment based on mathematical modelling methods, including computer experiment, and to estimate its effect on radio communication devices. This paper proposes the development of a statistical model of electromagnetic environment of a mobile wireless communication network by describing the parameters and factors affecting it including the propagation channel and their statistical models.

Keywords: Electromagnetic Environment, Statistical model, Wireless communication network.

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Authors: Bhupeshwaran Mani, S. Radha, A. Jawahar, A. Sivasubramanian

Abstract:

Here, we study the characteristic feature of conventional (ON-OFF keying) and soliton based transmission system. We consider 20Gbps transmission system implemented with Conventional Single Mode Fiber (C-SMF) to examine the role of Gaussian pulse which is the characteristic of conventional propagation and Hyperbolic-secant pulse which is the characteristic of soliton propagation in it. We note the influence of these pulses with respect to different dispersion lengths and soliton period in conventional and soliton system respectively and evaluate the system performance in terms of Quality factor. From the analysis, we could prove that the soliton pulse has the consistent performance even for long distance without dispersion compensation than the conventional system as it is robust to dispersion. For the length of transmission of 200Km, soliton system yielded Q of 33.958 while the conventional system totally exhausted with Q=0.

Keywords: Soliton, dispersion length, Soliton period, Return-tozero (RZ), Q-factor.

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Authors: Wiriya Loongyai, Kiettisak Promphet, Nilubol Kangsukul, Ratchawat Noppha

Abstract:

Polymerase chain reaction (PCR) assay and conventional microbiological methods were used to detect bacterial contamination of egg shells and egg content in different commercial housing systems, open house system and evaporative cooling system. A PCR assay was developed for direct detection using a set of primers specific for the invasion by A gene (invA) of Salmonella spp. PCR detected the presence of Salmonella in 2 samples of shell egg from the evaporative cooling system, while conventional cultural methods detected no Salmonella from the same samples.

Keywords: egg content, egg shell, invA gene, PCR, Salmonellaspp.

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Authors: Ramdan B. A. Koad, Ahmed. F. Zobaa

Abstract:

Since the output characteristics of photovoltaic (PV) system depends on the ambient temperature, solar radiation and load impedance, its maximum power point (MPP) is not constant. Under each condition PV module has a point at which it can produce its MPP. Therefore, a maximum power point tracking (MPPT) method is needed to uphold the PV panel operating at its MPP. This paper presents comparative study between the conventional MPPT methods used in (PV) system: Perturb and Observe (P&O), Incremental Conductance (IncCond), andParticle Swarm Optimization (PSO) algorithmfor (MPPT) of (PV) system. To evaluate the study, the proposed PSO MPPT is implemented on a DC-DC cuk converter and has been compared with P&O and INcond methods in terms of their tracking speed, accuracy and performance by using the Matlab tool Simulink. The simulation result shows that the proposed algorithm is simple, and is superior to the P&O and IncCond methods.

Keywords: Incremental Conductance (IncCond) Method, Perturb and Observe (P&O) Method, Photovoltaic Systems (PV) and Practical Swarm Optimization Algorithm (PSO).

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Authors: Stefan Bauer, Josef Frysak

Abstract:

According to the scientific information management literature, the improper use of information technology (e.g. personal computers) by employees are one main cause for operational and information security loss events. Therefore, organizations implement information security awareness programs to increase employees’ awareness to further prevention of loss events. However, in many cases these information security awareness programs consist of conventional delivery methods like posters, leaflets, or internal messages to make employees aware of information security policies. We assume that a viral information security awareness video might be more effective medium than conventional methods commonly used by organizations. The purpose of this research is to develop a viral video artifact to improve employee security behavior concerning information technology.

Keywords: Information Security Awareness, Delivery Methods, Viral Videos, Employee Security Behavior.

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Authors: Efstratios Doukakis, Nikolaos Petrelis

Abstract:

All climate models agree that the temperature in Greece will increase in the range of 1° to 2°C by the year 2030 and mean sea level in Mediterranean is expected to rise at the rate of 5 cm/decade. The aim of the present paper is the estimation of the coastline displacement driven by the climate change and sea level rise. In order to achieve that, all known statistical and non-statistical computational methods are employed on some Greek coastal areas. Furthermore, Kalman filtering techniques are for the first time introduced, formulated and tested. Based on all the above, shoreline change signals and noises are computed and an inter-comparison between the different methods can be deduced to help evaluating which method is most promising as far as the retrieve of shoreline change rate is concerned.

Keywords: Climate Change, Coastal Displacement, KalmanFilter

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Authors: Nikoo Soleimani

Abstract:

Background: Reducing torque during bone drilling is one of the effective factors in reaching to an optimal drilling process. Methods: 15 bovine femurs were drilled in vitro with a drill bit with a diameter of 4 mm using two methods of torsional ultrasonic assisted drilling (T-UAD) and convent conventional drilling (CD) and the effects of changing the feed rate and rotational speed on the torque were compared in both methods. Results: There was no significant difference in the thrust force measured in both methods due to the direction of vibrations. Results showed that using T-UAD method for bone drilling at feed rates of 0.16, 0.24 and 0.32 mm/rev led for all rotational speeds to a decrease of at least 16.3% in torque compared to the CD method. Further, using T-UAD at rotational speeds of 355~1000 rpm with various feed rates resulted in a torque reduction of 16.3~50.5% compared to CD method. Conclusions: Reducing the feed rate and increasing the rotational speed, except for the rotational speed of 500 rpm and a feed rate of 0.32 mm/rev, resulted generally in torque reduction in both methods. However, T-UAD is a more effective and desirable option for bone drilling considering its significant torque reduction.

Keywords: Torsional ultrasonic assisted drilling, torque, bone drilling, rotational speed, feed rate.

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Authors: A. R. Abdul Syukor, A. W. Zularisam, Z. Ideris, M. S. Mohd Ismid, H. M. Nakmal, S. Sulaiman, A. H. Hasmanie, M. R. Siti Norsita, M. Nasrullah

Abstract:

In this study, the effectiveness of an integrated aquatic plants in phytogreen zone was studied and statistical analysis for the promotional integrated phytogreen system approached was discussed. It was found that's the effectiveness of using aquatic plant such as Typha angustifolia sp., Lepironia articulata sp., Limnocharis flava sp., Monochoria vaginalis sp., Pistia stratiotes sp., and Eichhornia crassipes sp., in the conventional oxidation pond process in order to comply the standard A according to Malaysia Environmental Quality Act 1974 (Act 127); Environmental Quality (Sewage) Regulation 2009 for effluent discharge into inland water near the residential area was successfully shown. It was concluded that the integrated phtogreen system developed in this study has great potential for refurbishment wastewater in conventional oxidation pond.

Keywords: Phytoremediation, integrated phytogreen system, sewage treatment plant, oxidation pond, aquatic plants.

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Authors: Dongjoo Kim, Chang-Sik Son, Won-Seok Kang

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Adequate sleep affects various parts of one’s overall physical and mental life. As one of the methods in determining the appropriate amount of sleep, this research presents a heart rate based sleep quality index. In order to evaluate sleep quality using the heart rate, sleep data from 280 subjects taken over one month are used. Their sleep data are categorized by a three-part heart rate range. After categorizing, some features are extracted, and the statistical significances are verified for these features. The results show that some features of this sleep quality index model have statistical significance. Thus, this heart rate based sleep quality index may be a useful discriminator of sleep.

Keywords: Sleep, sleep quality, heart rate, statistical analysis.

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Authors: Gh. Jandaghi, H. Zarei Matin, A. Farjami

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In this article, while it is attempted to describe the problem and its importance, transformational leadership is studied by considering leadership theories. Issues such as the definition of transformational leadership and its aspects are compared on the basis of the ideas of various connoisseurs and then it (transformational leadership) is examined in successful and unsuccessful companies. According to the methodology, the method of research, hypotheses, population and statistical sample are investigated and research findings are analyzed by using descriptive and inferential statistical methods in the framework of analytical tables. Finally, our conclusion is provided by considering the results of statistical tests. The final result shows that transformational leadership is significantly higher in successful companies than unsuccessful ones P<0.0001).

Keywords: Idealized influence, individualized considerations, inspirational motivation, intellectual stimulation, transformational leadership

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Authors: Edlira Donefski, Lorenc Ekonomi, Tina Donefski

Abstract:

Edgeworth approximation is one of the most important statistical methods that has a considered contribution in the reduction of the sum of standard deviation of the independent variables’ coefficients in a Quantile Regression Model. This model estimates the conditional median or other quantiles. In this paper, we have applied approximating statistical methods in an economical problem. We have created and generated a quantile regression model to see how the profit gained is connected with the realized sales of the cosmetic products in a real data, taken from a local business. The Linear Regression of the generated profit and the realized sales was not free of autocorrelation and heteroscedasticity, so this is the reason that we have used this model instead of Linear Regression. Our aim is to analyze in more details the relation between the variables taken into study: the profit and the finalized sales and how to minimize the standard errors of the independent variable involved in this study, the level of realized sales. The statistical methods that we have applied in our work are Edgeworth Approximation for Independent and Identical distributed (IID) cases, Bootstrap version of the Model and the Edgeworth approximation for Bootstrap Quantile Regression Model. The graphics and the results that we have presented here identify the best approximating model of our study.

Keywords: Bootstrap, Edgeworth approximation, independent and Identical distributed, quantile.

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