Search results for: conventional statistical methods

Authors: Zamri Abu Bakar Zamri, Normaly Kamal Ismail Normaly, Mohd Izani Mohamed Rawi Izani

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Malay noun compound are phrases that consist of two or more nouns. The key characteristic behind noun compounds lies on its frequent occurrences within the text. Therefore, extracting these noun compounds is essential for several domains of research such as Information Retrieval, Sentiment Analysis and Question Answering. Many research efforts have been proposed in terms of extracting Malay noun compounds using linguistic and statistical approaches. Most of the existing methods have concentrated on the extraction of bi-gram noun+noun compound. However, extracting noun+verb, noun+adjective and noun+prepositional is challenging due to the difficulty of selecting an appropriate method with effective results. Thus, there is still room for improvement in terms of enhancing the effectiveness of compound word extraction. Therefore, this study proposed a combination of linguistic approach and statistical measures in order to enhance the extraction of compound words. Several preprocessing steps are involved including normalization, tokenization, and stemming. The linguistic approach that has been used in this study is Part-of-Speech (POS) tagging. In addition, a new linguistic pattern for named entities has been utilized using a list of Malays named entities in order to enhance the linguistic approach in terms of noun compound recognition. The proposed statistical measures consists of NC-value, NTC-value and NLC value.

Keywords: Compound Word, Noun Compound, Linguistic Approach, Statistical Approach

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Authors: Hee-Jeong Ahn, Kee-Won Kim, Seung-Hoon Kim

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The knowledge of the relationship between characters can help readers to understand the overall story or plot of the literary fiction. In this paper, we present a method for extracting the specific relationship between characters from a Korean literary fiction. Generally, methods for extracting relationships between characters in text are statistical or computational methods based on the sentence distance between characters without considering Korean linguistic features. Furthermore, it is difficult to extract the relationship with direction from text, such as one-sided love, because they consider only the weight of relationship, without considering the direction of the relationship. Therefore, in order to identify specific relationships between characters, we propose a statistical method considering linguistic features, such as syntactic patterns and speech verbs in Korean. The result of our method is represented by a weighted directed graph of the relationship between the characters. Furthermore, we expect that proposed method could be applied to the relationship analysis between characters of other content like movie or TV drama.

Keywords: data mining, Korean linguistic feature, literary fiction, relationship extraction

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Authors: Gülcan Taşkıran, Ayla Bayık Temel

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Background: Florence Nightingale, the modern founder of the nursing, is most famous for her role as a nurse. But not so much known about her contributions as a mathematician and statistician. Aim: In this conceptual article it is aimed to examine Florence Nightingale's statistics education, how she used her passion for statistics and applied statistical data in nursing care and her scientific contributions to statistical science. Design: Literature review method was used in the study. The databases of Istanbul University Library Search Engine, Turkish Medical Directory, Thesis Scanning Center of Higher Education Council, PubMed, Google Scholar, EBSCO Host, Web of Science were scanned to reach the studies. The keywords 'statistics' and 'Florence Nightingale' have been used in Turkish and English while being screened. As a result of the screening, totally 41 studies were examined from the national and international literature. Results: Florence Nightingale has interested in mathematics and statistics at her early ages and has received various training in these subjects. Lessons learned by Nightingale in a cultured family environment, her talent in mathematics and numbers, and her religious beliefs played a crucial role in the direction of the statistics. She was influenced by Quetelet's ideas in the formation of the statistical philosophy and received support from William Farr in her statistical studies. During the Crimean War, she applied statistical knowledge to nursing care, developed many statistical methods and graphics, so that she made revolutionary reforms in the health field. Conclusions: Nightingale's interest in statistics, her broad vision, the statistical ideas fused with religious beliefs, the innovative graphics she has developed and the extraordinary statistical projects that she carried out has been influential on the basis of her professional achievements. Florence Nightingale has also become a model for women in statistics. Today, using and teaching of statistics and research in nursing care practices and education programs continues with the light she gave.

Keywords: Crimean war, Florence Nightingale, nursing, statistics

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Authors: L. Abdou, O. Taibaoui, A. Moumen, A. Talib Ahmed

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This paper proposes an application of the simulated annealing to optimize the detection threshold in an ordered statistics constant false alarm rate (OS-CFAR) system. Using conventional optimization methods, such as the conjugate gradient, can lead to a local optimum and lose the global optimum. Also for a system with a number of sensors that is greater than or equal to three, it is difficult or impossible to find this optimum; Hence, the need to use other methods, such as meta-heuristics. From a variety of meta-heuristic techniques, we can find the simulated annealing (SA) method, inspired from a process used in metallurgy. This technique is based on the selection of an initial solution and the generation of a near solution randomly, in order to improve the criterion to optimize. In this work, two parameters will be subject to such optimisation and which are the statistical order (k) and the scaling factor (T). Two fusion rules; “AND” and “OR” were considered in the case where the signals are independent from sensor to sensor. The results showed that the application of the proposed method to the problem of optimisation in a distributed system is efficiency to resolve such problems. The advantage of this method is that it allows to browse the entire solutions space and to avoid theoretically the stagnation of the optimization process in an area of local minimum.

Keywords: distributed system, OS-CFAR system, independent sensors, simulating annealing

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Authors: Haiyan Wu, Ying Liu, Shaoyun Shi

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Authorship attribution is to extract features to identify authors of anonymous documents. Many previous works on authorship attribution focus on statistical style features (e.g., sentence/word length), content features (e.g., frequent words, n-grams). Modeling these features by regression or some transparent machine learning methods gives a portrait of the authors' writing style. But these methods do not capture the syntactic (e.g., dependency relationship) or semantic (e.g., topics) information. In recent years, some researchers model syntactic trees or latent semantic information by neural networks. However, few works take them together. Besides, predictions by neural networks are difficult to explain, which is vital in authorship attribution tasks. In this paper, we not only utilize the statistical style and content features but also take advantage of both syntactic and semantic features. Different from an end-to-end neural model, feature selection and prediction are two steps in our method. An attentive n-gram network is utilized to select useful features, and logistic regression is applied to give prediction and understandable representation of writing style. Experiments show that our extracted features can improve the state-of-the-art methods on three benchmark datasets.

Keywords: authorship attribution, attention mechanism, syntactic feature, feature extraction

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Authors: Queen Suraajini Rajendran, Sai Hung Cheung

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Statistical down scaling models are required to connect the global climate model outputs and the local weather variables for climate change impact prediction. For reliable climate change impact studies, the uncertainty associated with the model including natural variability, uncertainty in the climate model(s), down scaling model, model inadequacy and in the predicted results should be quantified appropriately. In this work, a new approach is developed by the authors for statistical classification, statistical down scaling and uncertainty assessment and is applied to Singapore rainfall. It is a robust Bayesian uncertainty analysis methodology and tools based on coupling dependent modeling error with classification and statistical down scaling models in a way that the dependency among modeling errors will impact the results of both classification and statistical down scaling model calibration and uncertainty analysis for future prediction. Singapore data are considered here and the uncertainty and prediction results are obtained. From the results obtained, directions of research for improvement are briefly presented.

Keywords: statistical downscaling, global climate model, climate change, uncertainty

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Authors: Epameinondas Xanthakis, Erik Kaunisto, Alain Le-Bail, Lilia Ahrné

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Fruits and vegetables are characterized as perishable food matrices due to their short shelf life as several deterioration mechanisms are being involved. Prior to the common preservation methods like freezing or canning, fruits and vegetables are being blanched in order to inactivate deteriorative enzymes. Both conventional blanching pretreatments and conventional freezing methods hide drawbacks behind their beneficial impacts on the preservation of those matrices. Conventional blanching methods may require longer processing times, leaching of minerals and nutrients due to the contact with the warm water which in turn leads to effluent production with large BOD. An important issue of freezing technologies is the size of the formed ice crystals which is also critical for the final quality of the frozen food as it can cause irreversible damage to the cellular structure and subsequently to degrade the texture and the colour of the product. Herein, the developed microwave blanching methodology and the results regarding quality aspects and enzyme inactivation will be presented. Moreover, heat transfer phenomena, mass balance, temperature distribution, and enzyme inactivation (such as Pectin Methyl Esterase and Ascorbic Acid Oxidase) of our microwave blanching approach will be evaluated based on measurements and computer modelling. The present work is part of the COLDμWAVE project which aims to the development of an innovative environmentally sustainable process for blanching and freezing of fruits and vegetables with improved textural and nutritional quality. In this context, COLDµWAVE will develop tailored equipment for MW blanching of vegetables that has very high energy efficiency and no water consumption. Furthermore, the next steps of this project regarding the development of innovative pathways in MW assisted freezing to improve the quality of frozen vegetables, by exploring in depth previous results acquired by the authors, will be presented. The application of MW assisted freezing process on fruits and vegetables it is expected to lead to improved quality characteristics compared to the conventional freezing. Acknowledgments: COLDμWAVE has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grand agreement No 660067.

Keywords: blanching, freezing, fruits, microwave blanching, microwave

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Authors: Alimshan Faizulayev, Eralp Bektas, Abdul Ghafar Ismail, Bezhan Rustamov

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This paper performs empirical analysis on determinants of profitability in Islamic and Conventional Banks. The main focus of this study is to evaluate and measure of financial performance of Islamic banking firms operating in Egypt, Iran, Malaysia, Pakistan, Turkey, UAE in contrast to Conventional ones in those countries. To evaluate empirically performance of the banks, various financial ratios are employed. We measure performance in terms of liquidity, profitability, solvency, and efficiency. In this work, t-test, F-test, and OLS analysis are used to make hypothesis tests. Our findings reveal that there are similarities and differences in profitability determinants of Islamic and Conventional banking firms. The cost to revenue ratio has inverse relationship with profitability indicators in both banking systems. However, there are differences in financial performances between Conventional Banks and Islamic banks which are found in overall picture of all banks in terms of net income margin.

Keywords: Islamic banking, conventional banking, GDP growth, emerging market economies

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Authors: Eman W. Boghdady, A. R. Shehata, M. A. Azem

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Database (DB) security demands permitting authorized users and prohibiting non-authorized users and intruders actions on the DB and the objects inside it. Organizations that are running successfully demand the confidentiality of their DBs. They do not allow the unauthorized access to their data/information. They also demand the assurance that their data is protected against any malicious or accidental modification. DB protection and confidentiality are the security concerns. There are four types of controls to obtain the DB protection, those include: access control, information flow control, inference control, and cryptographic. The cryptographic control is considered as the backbone for DB security, it secures the DB by encryption during storage and communications. Current cryptographic techniques are classified into two types: traditional classical cryptography using standard algorithms (DES, AES, IDEA, etc.) and chaos cryptography using continuous (Chau, Rossler, Lorenz, etc.) or discreet (Logistics, Henon, etc.) algorithms. The important characteristics of chaos are its extreme sensitivity to initial conditions of the system. In this paper, DB-security systems based on chaotic algorithms are described. The Pseudo Random Numbers Generators (PRNGs) from the different chaotic algorithms are implemented using Matlab and their statistical properties are evaluated using NIST and other statistical test-suits. Then, these algorithms are used to secure conventional DB (plaintext), where the statistical properties of the ciphertext are also tested. To increase the complexity of the PRNGs and to let pass all the NIST statistical tests, we propose two hybrid PRNGs: one based on two chaotic Logistic maps and another based on two chaotic Henon maps, where each chaotic algorithm is running side-by-side and starting from random independent initial conditions and parameters (encryption keys). The resulted hybrid PRNGs passed the NIST statistical test suit.

Keywords: algorithms and data structure, DB security, encryption, chaotic algorithms, Matlab, NIST

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Authors: Ahmed Assem Abd El Rahim

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BACKGROUND: Low back pain (LBP) is enormously common health problem& most of subjects experience it at some point of their life. Kinesio-taping is one of therapy methods introduced for studied cases with nonspecific low back pain. OBJECTIVES: to look at how Kinesio-taping affects studied cases with non-specific low back pain in terms of discomfort, range of motion, & back muscular strength. SUBJECTS: 40 mechanical LBP patients aged 20-40 years had been assigned haphazardly into two groups, They had been selected from outpatient clinic, KasrAl-AiniHospital, Cairo university. Methods: GroupA: 20 patients received the I-shape KT longitudinally & conventional physiotherapy program. Group B:20 studied cases received application of the KT Horizontally & conventional physiotherapy program. pain had been measured by visual analog scale, Range of motion had been measured by Roland Morris Disability Questionnaire (RMDQ), & strength had been measured by an isokinetic dynamometer before & after therapy. Therapy sessions had been three times weekly for four weeks. RESULTS: Groups (A & B) discovered decrease in pain& disability and rise in their flexion, extension ROM & peak torque of trunk extensor after end of 4 weeks of program. mean values of pain scale after therapy had been 3.7 and 5.04 in groups A & B. mean values of Disability scale after treatment had been 7.87.and 9.35 in groups A & B. mean values of ROM of flexion had been 28.06, and 24.53 in groups A & B. mean values of ROM of extension had been 13.43 & 10.73 in groups A & B. mean values of Peak torque of lumbar extensors were 65.43 and 63.22 in groups A & B. Though, participants who received the I-shape KT longitudinally as well as conventional physiotherapy program (group A), discovered more reduction in pain& disability and more improvement in ROM of flexion, extension, and Peak torque of lumbar extensors value (P<0.001) after therapy program CONCLUSION: Therapeutic longitudinal Kinesio-taping application with conventional physiotherapy will be more valuable than Therapeutic horizontal Kinesio-taping application with conventional physiotherapy when treating nonspecific low back pain studied cases.

Keywords: Kinesio taping, function, low back pain, muscle power

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Authors: Rishikesh Yadav, Ramakanta Meher, Vishnu Narayan Mishra

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The main aim of this article is to investigate the statistical convergence of the summation of integral type operators and to obtain the weighted statistical convergence. The rate of statistical convergence by means of modulus of continuity and function belonging to the Lipschitz class are also studied. We discuss the convergence of the defined operators by graphical representation and put a better rate of convergence than the Szasz-Mirakjan-Kantorovich operators. In the last section, we extend said operators into bivariate operators to study about the rate of convergence in sense of modulus of continuity and by means of Lipschitz class by using function of two variables.

Keywords: The Szasz-Mirakjan-Kantorovich operators, statistical convergence, modulus of continuity, Peeters K-functional, weighted modulus of continuity

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Authors: Mario Lupaca, Karol Munoz, Victor De Negri

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The present article presents a methodology for the improvement of the energy efficiency in pneumatic systems through the restoring of air. In this way, three techniques of expansion of a cylinder are identified: Expansion using the air of the compressor (conventional), restoring the air (efficient), and combining the air of the compressor and the restored air (hybrid). The methodology starts with the development of the GRAFCET of the system so that it can be decided whether to expand the cylinder in a conventional, efficient, or hybrid way. The methodology can be applied to any case. Finally, graphs of comparison between the three methods of expansion with certain cylinder strokes and workloads are presented, to facilitate the subsequent selection of one system or another.

Keywords: energetic, efficiency, GRAFCET, methodology, pneumatic

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Authors: Abdelsalam Elawwad, Mostafa Ragab, Hisham Abdel-Halim

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Leakage in sewerage system can cause groundwater and soil contamination in urban areas, especially in area with a high groundwater table. This is a serious problem in small villages in developing countries that rely on ground water as a source for irrigation and drinking purposes. In the developed countries, the recent trend in areas with low population densities is vacuum sewerage system, which is environmentally safer than conventional gravity system, protecting public health, preventing exfiltration to the ground water, very easily applied in a relatively short time and can cope with a faster expansion of the urbanized areas. The aim of this work is to assess the feasibility of using vacuum sewerage in developing country, such as Egypt. Knowledge of local conditions can determine the most suitable sewer system for a specific region. Technical, environmental and financial comparisons between conventional sewerage system and vacuum sewerage system were held using statistical analysis. Different conditions, such as population densities, geometry of area, and ground water depths were evaluated. Sample comprising of 30 Egyptian villages was selected, where a complete design for conventional sewerage system and vacuum sewerage system was done. Based on this study, it is recommended from the environmental point of view to construct the vacuum sewerage system in such villages with low population densities; however, it is not economic for all cases. From financial point of view, vacuum sewerage system was a good competitor to conventional systems in flat areas and areas with high groundwater table. The local market supplying of the construction equipment especially collection chambers will greatly affect the investment cost. Capacity building and social mobilization will also play a great role in sustainability of this system. At the end, it is noteworthy that environmental sustainability and public health are more important than the financial aspects.

Keywords: ground water, conventional system, vacuum system, statistics, cost, density, terrain

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Authors: Jamerson Felipe Pereira Lima, Jeane Cecília Bezerra de Melo

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The difficulty and cost related to obtaining of protein tertiary structure information through experimental methods, such as X-ray crystallography or NMR spectroscopy, helped raising the development of computational methods to do so. An approach used in these last is prediction of tridimensional structure based in the residue chain, however, this has been proved an NP-hard problem, due to the complexity of this process, explained by the Levinthal paradox. An alternative solution is the prediction of intermediary structures, such as the secondary structure of the protein. Artificial Intelligence methods, such as Bayesian statistics, artificial neural networks (ANN), support vector machines (SVM), among others, were used to predict protein secondary structure. Due to its good results, artificial neural networks have been used as a standard method to predict protein secondary structure. Recent published methods that use this technique, in general, achieved a Q3 accuracy between 75% and 83%, whereas the theoretical accuracy limit for protein prediction is 88%. Alternatively, to achieve better results, support vector machines prediction methods have been developed. The statistical evaluation of methods that use different AI techniques, such as ANNs and SVMs, for example, is not a trivial problem, since different training sets, validation techniques, as well as other variables can influence the behavior of a prediction method. In this study, we propose a prediction method based on artificial neural networks, which is then compared with a selected SVM method. The chosen SVM protein secondary structure prediction method is the one proposed by Huang in his work Extracting Physico chemical Features to Predict Protein Secondary Structure (2013). The developed ANN method has the same training and testing process that was used by Huang to validate his method, which comprises the use of the CB513 protein data set and three-fold cross-validation, so that the comparative analysis of the results can be made comparing directly the statistical results of each method.

Keywords: artificial neural networks, protein secondary structure, protein structure prediction, support vector machines

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Authors: Majid Arvan, Peyman Beygi, Sina Rokhsati

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In-time detection of fire in buildings is of great importance. Employing intelligent methods in data processing in fire detection systems leads to a significant reduction of fire damage at lowest cost. In this paper, the raw data obtained from the fire detection sensor networks in buildings is processed by using intelligent methods based on neural networks and the likelihood of fire happening is predicted. In order to enhance the quality of system, the noise in the sensor data is reduced by analyzing wavelets and applying SVD technique. Meanwhile, the proposed neural network is trained using particle swarm optimization (PSO). In the simulation work, the data is collected from sensor network inside the room and applied to the proposed network. Then the outputs are compared with conventional MLP network. The simulation results represent the superiority of the proposed method over the conventional one.

Keywords: intelligent fire detection, neural network, particle swarm optimization, fire sensor network

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Authors: Elham A. Kwildi, Yahia S. Abugnah, Nuri S. Madi

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This study was designed to evaluate the microbiological quality and safety of two types of salads prepared at a catering center affiliated with Libyan Airlines in Tripoli, Libya. Two hundred and twenty-one (221) samples (132 economy-class and 89 first- class) were used in this project which lasted for ten months. Biweekly, microbiological tests were performed which included total plate count (TPC) and total coliforms (TCF), in addition to enumeration and/or detection of some pathogenic bacteria mainly Escherichia coli, Staphylococcus aureus, Bacillus cereus, Salmonella sp, Listeria sp and Vibrio parahaemolyticus parahaemolyticus, By using conventional as well as compact dry methods. Results indicated that TPC of type 1 salad ranged between (<10 – 62 x 103 cfu/gm) and (<10 to 36 x103 cfu/g), while TCF were (<10 – 41 x 103 cfu/gm) and (< 10 to 66 x102 cfu/g) using both methods of detection respectively. On the other hand, TPC of type 2 salad were: (1 × 10 – 52 x 103) and (<10 – 55 x 103 cfu/gm) and in the range of (1 x10 to 45x103 cfu/g), and the (TCF) counts were between (< 10 to 55x103 cfu/g) and (< 10 to 34 x103 cfu/g) using the 1st and the 2nd methods of detection respectively. Also, the pathogens mentioned above were detected in both types of salads, but their levels varied according to the type of salad and the method of detection. The level of Staphylococcus aureus, for instance, was 17.4% using conventional method versus 14.4% using the compact dry method. Similarly, E. coli was 7.6% and 9.8%, while Salmonella sp. recorded the least percentage i.e. 3% and 3.8% with the two mentioned methods respectively. First class salads were also found to contain the same pathogens, but the level of E. coli was relatively higher in this case (14.6% and 16.9%) using conventional and compact dry methods respectively. The second rank came Staphylococcus aureus (13.5%) and (11.2%), followed by Salmonella (6.74%) and 6.70%). The least percentage was for Vibrio parahaemolyticus (4.9%) which was detected in the first class salads only. The other two pathogens Bacillus cereus and Listeria sp. were not detected in either one of the salads. Finally, it is worth mentioning that there was a significant decline in TPC and TCF counts in addition to the disappearance of pathogenic bacteria after the 6-7th month of the study which coincided with the first trial of the HACCP system at the center. The ups and downs in the counts along the early stages of the study reveal that there is a need for some important correction measures including more emphasis on training of the personnel in applying the HACCP system effectively.

Keywords: air travel, vegetable salads, foodborne outbreaks, Libya

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Authors: Oliver Chunho Ma, Tszying Chang

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Background: Traditional Chinese Medicine (TCM) has been widely used in the treatment of eczema. However, there is currently a lack of comprehensive research on the overall effectiveness of TCM in treating eczema, particularly using the Eczema Area and Severity Index (EASI) score as an evaluation tool. Meta-analysis can integrate the results of multiple studies to provide more convincing evidence. Objective: To conduct a systematic review and meta-analysis based on the EASI score to evaluate the overall effectiveness of TCM in the treatment of eczema. Specifically, the study will review and analyze published clinical studies that investigate TCM treatments for eczema and use the EASI score as an outcome measure, comparing the differences in improving the severity of eczema between TCM and other treatment modalities, such as conventional Western medicine treatments. Methods: Relevant studies, including randomized controlled trials (RCTs) and non-randomized controlled trials, that involve TCM treatment for eczema and use the EASI score as an outcome measure will be searched in medical literature databases such as PubMed, CNKI, etc. Relevant data will be extracted from the selected studies, including study design, sample size, treatment methods, improvement in EASI score, etc. The methodological quality and risk of bias of the included studies will be assessed using appropriate evaluation tools (such as the Cochrane Handbook). The results of the selected studies will be statistically analyzed, including pooling effect sizes (such as standardized mean differences, relative risks, etc.), subgroup analysis (e.g., different TCM syndromes, different treatment modalities), and sensitivity analysis (e.g., excluding low-quality studies). Based on the results of the statistical analysis and quality assessment, the overall effectiveness of TCM in improving the severity of eczema will be interpreted. Expected outcomes: By integrating the results of multiple studies, we expect to provide more convincing evidence regarding the specific effects of TCM in improving the severity of eczema. Additionally, subgroup analysis and sensitivity analysis can further elucidate whether the effectiveness of TCM treatment is influenced by different factors. Besides, we will compare the results of the meta-analysis with the clinical data from our clinic. For both the clinical data and the meta-analysis results, we will perform descriptive statistics such as means, standard deviations, percentages, etc. and compare the differences between the two using statistical tests such as independent samples t-test or non-parametric tests to assess the statistical differences between them.

Keywords: Eczema, traditional Chinese medicine, EASI, systematic review, meta-analysis

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Authors: Sheikh Omar Sillah

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Introduction: Monitoring is an important means of ensuring the smooth implementation and quality of clinical trials. For many years, traditional site monitoring approaches have been critical in detecting data errors but not optimal in identifying fabricated and implanted data as well as non-random data distributions that may significantly invalidate study results. The objective of this paper was to provide recommendations based on best statistical monitoring practices for detecting data-integrity issues suggestive of fabrication and implantation early in the study conduct to allow implementation of meaningful corrective and preventive actions. Methodology: Electronic bibliographic databases (Medline, Embase, PubMed, Scopus, and Web of Science) were used for the literature search, and both qualitative and quantitative studies were sought. Search results were uploaded into Eppi-Reviewer Software, and only publications written in the English language from 2012 were included in the review. Gray literature not considered to present reproducible methods was excluded. Results: A total of 18 peer-reviewed publications were included in the review. The publications demonstrated that traditional site monitoring techniques are not efficient in detecting data anomalies. By specifying project-specific parameters such as laboratory reference range values, visit schedules, etc., with appropriate interactive data monitoring, statistical monitoring can offer early signals of data anomalies to study teams. The review further revealed that statistical monitoring is useful to identify unusual data patterns that might be revealing issues that could impact data integrity or may potentially impact study participants' safety. However, subjective measures may not be good candidates for statistical monitoring. Conclusion: The statistical monitoring approach requires a combination of education, training, and experience sufficient to implement its principles in detecting data anomalies for the statistical aspects of a clinical trial.

Keywords: statistical monitoring, data anomalies, clinical trials, traditional monitoring

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Authors: Muhammad Awais Shafique, Eiji Hato

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Household trip data is of crucial importance for managing present transportation infrastructure as well as to plan and design future facilities. It also provides basis for new policies implemented under Transportation Demand Management. The methods used for household trip data collection have changed with passage of time, starting with the conventional face-to-face interviews or paper-and-pencil interviews and reaching to the recent approach of employing smartphones. This study summarizes the step-wise evolution in the travel data collection methods. It provides a comprehensive review of the topic, for readers interested to know the changing trends in the data collection field.

Keywords: computer, smartphone, telephone, travel survey

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Authors: Akshay B. Pawar, Rohit Y. Parasnis

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Heart Rate Variability (HRV) is a widely used indicator of the regulation between the autonomic nervous system (ANS) and the cardiovascular system. Besides being non-invasive, it also has the potential to predict mortality in cases involving critical injuries. The gold standard method for determining HRV is based on the analysis of RR interval time series extracted from ECG signals. However, because it is much more convenient to obtain photoplethysmogramic (PPG) signals as compared to ECG signals (which require the attachment of several electrodes to the body), many researchers have used pulse cycle intervals instead of RR intervals to estimate HRV. They have also compared this method with the gold standard technique. Though most of their observations indicate a strong correlation between the two methods, recent studies show that in healthy subjects, except for a few parameters, the pulse-based method cannot be a surrogate for the standard RR interval- based method. Moreover, the former tends to overestimate short-term variability in heart rate. This calls for improvements in or alternatives to the pulse-cycle interval method. In this study, besides the systolic peak-peak interval method (PP method) that has been studied several times, four recent PPG-based techniques, namely the first derivative peak-peak interval method (P1D method), the second derivative peak-peak interval method (P2D method), the valley-valley interval method (VV method) and the tangent-intersection interval method (TI method) were compared with the gold standard technique. ECG and PPG signals were obtained from 10 young and healthy adults (consisting of both males and females) seated in the armchair position. In order to de-noise these signals and eliminate baseline drift, they were passed through certain digital filters. After filtering, the following HRV parameters were computed from PPG using each of the five methods and also from ECG using the gold standard method: time domain parameters (SDNN, pNN50 and RMSSD), frequency domain parameters (Very low-frequency power (VLF), Low-frequency power (LF), High-frequency power (HF) and Total power or “TP”). Besides, Poincaré plots were also plotted and their SD1/SD2 ratios determined. The resulting sets of parameters were compared with those yielded by the standard method using measures of statistical correlation (correlation coefficient) as well as statistical agreement (Bland-Altman plots). From the viewpoint of correlation, our results show that the best PPG-based methods for the determination of most parameters and Poincaré plots are the P2D method (shows more than 93% correlation with the standard method) and the PP method (mean correlation: 88%) whereas the TI, VV and P1D methods perform poorly (<70% correlation in most cases). However, our evaluation of statistical agreement using Bland-Altman plots shows that none of the five techniques agrees satisfactorily well with the gold standard method as far as time-domain parameters are concerned. In conclusion, excellent statistical correlation implies that certain PPG-based methods provide a good amount of information on the pattern of heart rate variation, whereas poor statistical agreement implies that PPG cannot completely replace ECG in the determination of HRV.

Keywords: photoplethysmography, heart rate variability, correlation coefficient, Bland-Altman plot

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Authors: Saad Khalid Niaz, Arif Mahmood Siddiqui, Afzal Haqi

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Background: Estimated prevalence of Hepatitis C in Pakistan is 5% of which 78 % are Genotype 3, in which Response to conventional interferon is reported to be 70%. Objective: To determine the efficacy of pegylated interferon 20 kDa (Unipeg) plus ribavirin (Ribazole) in HCV genotype 3 patients who relapsed to conventional interferon. Methods: This is an ongoing study of 20 enrolled patients. Pegylated interferon alfa-2a 20 kDa 180 mcg weekly with ribavirin, were administered for a period of 24 weeks. Virological Responses were measured by Qualitative HCV RNA at weeks 4, 12, 24 and 48 to determine Rapid Virological Response (RVR), Early Virological Response (EVR), End of Treatment (ETR) and Sustained Virological Response (SVR), respectively. EVR was done for those who didn’t achieve RVR. Results: Males were 12 (60%) and mean age was 38.5 ±7.62 years. Out of 20 recruited patients, all completed 4 weeks therapy; RVR was achieved in 8 (40%) patients. One patient was lost to follow up and one yet to visit at 12 weeks. From 10 patients, 8 (80%) patients achieved EVR. Out of intent-to-treat patients, 15 completed 24 weeks therapy, ETR was achieved in 14 (93%) patients and 9 patients completed post therapy follow-up, of which, 8 (89%) patients achieved SVR. Conclusion: Our interim data demonstrates that Pegylated Interferon alfa-2a 20 kDa 180 mcg (Unipeg) in combination with Ribavirin (Ribazole) has shown promising results in treating HCV Genotype 3 patients who relapsed to conventional interferon. We recommend use of Pegylated Interferon in Relapsers with Genotype 3 when financial constraints limit the use of oral antivirals.

Keywords: pegylated interferon (unipeg), hepatitis c, relapsers, Pakistan

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Authors: Syamala Krishnannair

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A multivariate statistical process monitoring methodology using dissimilarity scale-based singular spectrum analysis (SSA) is proposed for the detection and diagnosis of process faults in the base metal flotation plant. Process faults are detected based on the multi-level decomposition of process signals by SSA using the dissimilarity structure of the process data and the subsequent monitoring of the multiscale signals using the unified monitoring index which combines T² with SPE. Contribution plots are used to identify the root causes of the process faults. The overall results indicated that the proposed technique outperformed the conventional multivariate techniques in the detection and diagnosis of the process faults in the flotation plant.

Keywords: fault detection, fault diagnosis, process monitoring, dissimilarity scale

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Authors: Prem Mohan, Namrata Jariwala

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In recent years 10000 dyes are approximately used by dying industry which makes dyeing wastewater more complex in nature. It is very difficult to treat dyeing wastewater by conventional methods. Here an attempt has been made to treat dyeing wastewater by the conventional and advanced method for removal of COD. Fenton process is the advanced method and activated carbon treatment is the conventional method. Experiments have been done on synthetic wastewater prepared from three different dyes; acidic, disperse and reactive. Experiments have also been conducted on real effluent obtained from industry. The optimum dose of catalyst and hydrogen peroxide in Fenton process and optimum activated carbon dose for each of these wastewaters were obtained. In Fenton treatment, COD removal was obtained up to 95% whereas 70% removal was obtained with activated carbon treatment.

Keywords: activated carbon, advanced oxidation process, dyeing waste water, fenton oxidation process

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Authors: Belkacem Laimouche

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With the field of artificial intelligence (AI) experiencing exponential growth, fueled by technological advancements that pave the way for increasingly innovative and promising applications, there is an escalating need to develop rigorous methods for assessing their performance in pursuit of transparency and equity. This article proposes a metrology-inspired statistical framework for evaluating bias and explainability in AI systems. Drawing from the principles of metrology, we propose a pioneering approach, using a concrete example, to evaluate the accuracy and precision of AI models, as well as to quantify the sources of measurement uncertainty that can lead to bias in their predictions. Furthermore, we explore a statistical approach for evaluating the explainability of AI systems based on their ability to provide interpretable and transparent explanations of their predictions.

Keywords: artificial intelligence, metrology, measurement uncertainty, prediction error, bias, machine learning algorithms, probabilistic models, interlaboratory comparison, data analysis, data reliability, measurement of bias impact on predictions, improvement of model accuracy and reliability

Procedia PDF Downloads 88

Authors: Nino Abesadze, Marine Mindorashvili, Nino Paresashvili

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The main purpose of the article is to make complex statistical analysis of tourist expenses of foreign visitors. We used mixed technique of selection that implies rules of random and proportional selection. Computer software SPSS was used to compute statistical data for corresponding analysis. Corresponding methodology of tourism statistics was implemented according to international standards. Important information was collected and grouped from the major Georgian airports. Techniques of statistical observation were prepared. A representative population of foreign visitors and a rule of selection of respondents were determined. We have a trend of growth of tourist numbers and share of tourists from post-soviet countries constantly increases. Level of satisfaction with tourist facilities and quality of service has grown, but still we have a problem of disparity between quality of service and prices. The design of tourist expenses of foreign visitors is diverse; competitiveness of tourist products of Georgian tourist companies is higher.

Keywords: tourist, expenses, methods, statistics, analysis

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Authors: Sanja Podunavac-Kuzmanović, Denis Kučević, Strahinja Kovačević, Milica Karadžić, Lidija Jevrić

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The present study describes the application of chemometric methods in analysis of milk samples which were collected in a conventional dairy farm and an organic dairy farm in AP Vojvodina, Republic of Serbia. The chemometric analysis included the application of univariate regression modeling and Analysis of Variance (ANOVA) method. The ANOVA was used in order to determine the differences in fatty acids content in the milk samples from conventional and organic farm. The results of the ANOVA testing indicate that there is a highly statistically significant difference between the content of fatty acid (saturated fatty acid vs. unsaturated fatty acids) in different dairy farming. Besides, the linear univariate models have been obtained as a result of modeling the linear relationships between the milk fat content and saturated fatty acids content, and the linear relationships between the milk fat content and unsaturated fatty acids content. The models obtained on the basis of the milk samples which originate from the organic farming are statistically better than the models based on the milk samples from conventional farming.

Keywords: hemometrics, milk, organic farming, quality control

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Authors: Mehmet Karabekir

Abstract:

Attack helicopters (AHs) are usually deployed in conventional warfare to destroy armored and mechanized forces of enemy. In addition, AHs are able to perform various tasks in the deep, and close operations – intelligence, surveillance, reconnaissance, air assault operations, and search and rescue operations. Apache helicopters were properly employed in the Gulf Wars and contributed the success of campaign by destroying a large number of armored and mechanized vehicles of Iraq Army. The purpose of this article is to discuss the deployment of AHs in conventional warfare in the light of Gulf Wars. First, the employment of AHs in deep and close operations will be addressed regarding the doctrine. Second, the US armed forces AH-64 doctrinal and tactical usage will be argued in the 1st and 2nd Gulf Wars.

Keywords: attack helicopter, conventional warfare, gulf wars

Procedia PDF Downloads 450

Authors: Daniel Schwarz, Jan Fivaz, Alessia Neuroni

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Although digitization is a buzzword in almost every election campaign, the political parties leave voters largely in the dark about their specific positions on digital issues. In the run-up to the 2019 elections in Switzerland, the ‘Digitization Monitor’ project (DMP) was launched in order to change this situation. Within the framework of the DMP, all 4,736 candidates were surveyed about their digital policy positions and values. The DMP is designed as a digital policy supplement to the existing ‘smartvote’ voting advice application. This enabled a direct comparison of the digital policy attitudes according to the DMP with the topics of the ‘smartvote’ questionnaire which are comprehensive in content but mainly related to conventional policy areas. This paper’s main research goal is to analyze and visualize possible differences between conventional and digital policy areas in terms of response patterns between and within political parties. The analysis is based on dimensionality reduction methods (multidimensional scaling and principal component analysis) for the visualization of inter-party differences, and on standard deviation as a measure of variation for the evaluation of intra-party unity. The results reveal that digital issues show a lower degree of inter-party polarization compared to conventional policy areas. Thus, the parties have more common ground in issues on digitization than in conventional policy areas. In contrast, the study reveals a mixed picture regarding intra-party unity. Homogeneous parties show a lower degree of unity in digitization issues whereas parties with heterogeneous positions in conventional areas have more united positions in digital areas. All things considered, the findings are encouraging as less polarized conditions apply to the debate on digital development compared to conventional politics. For the future, it would be desirable if in further countries similar projects to the DMP could emerge to broaden the basis for conclusions.

Keywords: comparison of political issue dimensions, digital awareness of candidates, digital policy space, party positions on digital issues

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Authors: H. Khanfari, M. Johari Fard

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Dealing with carbonate reservoirs can be mind-boggling for the reservoir engineers due to various digenetic processes that cause a variety of properties through the reservoir. A good estimation of the reservoir heterogeneity which is defined as the quality of variation in rock properties with location in a reservoir or formation, can better help modeling the reservoir and thus can offer better understanding of the behavior of that reservoir. Most of reservoirs are heterogeneous formations whose mineralogy, organic content, natural fractures, and other properties vary from place to place. Over years, reservoir engineers have tried to establish methods to describe the heterogeneity, because heterogeneity is important in modeling the reservoir flow and in well testing. Geological methods are used to describe the variations in the rock properties because of the similarities of environments in which different beds have deposited in. To illustrate the heterogeneity of a reservoir vertically, two methods are generally used in petroleum work: Dykstra-Parsons permeability variations (V) and Lorenz coefficient (L) that are reviewed briefly in this paper. The concept of Lorenz is based on statistics and has been used in petroleum from that point of view. In this paper, we correlated the statistical-based Lorenz method to a petroleum concept, i.e. Kozeny-Carman equation and derived the straight line plot of Lorenz graph for a homogeneous system. Finally, we applied the two methods on a heterogeneous field in South Iran and discussed each, separately, with numbers and figures. As expected, these methods show great departure from homogeneity. Therefore, for future investment, the reservoir needs to be treated carefully.

Keywords: carbonate reservoirs, heterogeneity, homogeneous system, Dykstra-Parsons permeability variations (V), Lorenz coefficient (L)

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Authors: Y. A. Yahaya, Ahmad Tijjani Asabe

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This paper focuses on the formulation of 3-step hybrid Adams type method for the solution of first order differential equation (ODE). The methods which was derived on both grid and off grid points using multistep collocation schemes and also evaluated at some points to produced Block Adams type method and Adams moulton method respectively. The method with the highest order was selected to serve as the corrector. The convergence was valid and efficient. The numerical experiments were carried out and reveal that hybrid Adams type methods performed better than the conventional Adams moulton method.

Keywords: adam-moulton type (amt), corrector method, off-grid, block method, convergence analysis

Procedia PDF Downloads 596