Search results for: statistical literacy

Authors: Mustapha Benssalah, Mustapha Djeddou, Karim Drouiche

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The random number generation (RNG) presents a significant importance for the security and the privacy of numerous applications, such as RFID technology and smart cards. Since, the quality of the generated bit sequences is paramount that a weak internal generator for example, can directly cause the entire application to be insecure, and thus it makes no sense to employ strong algorithms for the application. In this paper, we propose a new pseudo random number generator (PRNG), suitable for cryptosystems ECC-based, constructed by randomly selecting points from several elliptic curves randomly selected. The main contribution of this work is the increasing of the generator internal states by extending the set of its output realizations to several curves auto-selected. The quality and the statistical characteristics of the proposed PRNG are validated using the Chi-square goodness of fit test and the empirical Special Publication 800-22 statistical test suite issued by NIST.

Keywords: PRNG, security, cryptosystem, ECC

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Authors: H. Nouri, S. Chavoshi Borujeni, S. Anderson, S. Beecham, P. Sutton

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The potential risk of salt leaching through wastewater irrigation is of concern for most local governments and city councils. Despite the necessity of salinity monitoring and management in urban greenery, most attention has been on agricultural fields. This study was defined to investigate the capability and feasibility of monitoring and predicting soil salinity using near sensing and remote sensing approaches using EM38 surveys, and high-resolution multispectral image of WorldView3. Veale Gardens within the Adelaide Parklands was selected as the experimental site. The results of the near sensing investigation were validated by testing soil salinity samples in the laboratory. Over 30 band combinations forming salinity indices were tested using image processing techniques. The outcomes of the remote sensing and near sensing approaches were compared to examine whether remotely sensed salinity indicators could map and predict the spatial variation of soil salinity through a potential statistical model. Statistical analysis was undertaken using the Stata 13 statistical package on over 52,000 points. Several regression models were fitted to the data, and the mixed effect modelling was selected the most appropriate one as it takes to account the systematic observation-specific unobserved heterogeneity. Results showed that SAVI (Soil Adjusted Vegetation Index) was the only salinity index that could be considered as a predictor for soil salinity but further investigation is needed. However, near sensing was found as a rapid, practical and realistically accurate approach for salinity mapping of heterogeneous urban vegetation.

Keywords: WorldView3, remote sensing, EM38, near sensing, urban green spaces, green smart cities

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Authors: Swetha Priya Darshini Thammadi, Sateesh Kumar Pisini, Sanjay Kumar Shukla

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Source apportionment using Dispersion model depends primarily on the quality of Emission Inventory. In the present study, a CMB receptor model has been used to identify the sources of PM_2.5, while the AERMOD dispersion model has been used to account for missing sources of PM_2.5 in the Emission Inventory. A statistical approach has been developed to quantify the missing sources not considered in the Emission Inventory. The inventory of each grid was improved by adjusting emissions based on road lengths and deficit in measured and modelled concentrations. The results showed that in CMB analyses, fugitive sources - soil and road dust - contribute significantly to ambient PM_2.5 pollution. As a result, AERMOD significantly underestimated the ambient air concentration at most locations. The revised Emission Inventory showed a significant improvement in AERMOD performance which is evident through statistical tests.

Keywords: CMB, GIS, AERMOD, PM₂.₅, fugitive, emission inventory

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Authors: Sadia Afroza, Rakiba Rouf

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Road safety and associated behaviors have received significant attention in recent years, reflecting general public concern. This paper portrays a statistical scenario of the young drivers in UAE with emphasis on various concern points of young driver’s behavior and license issuance. Although there are many factors contributing to road accidents, statistically it is evident that age plays a major role in road accidents. Despite ensuring strict road safety laws enforced by the UAE government, there is a staggering correlation among road accidents and young driver’s at UAE. However, private organizations like BMW and RoadSafetyUAE have extended its support on conducting surveys on driver’s behavior with an aim to ensure road safety. Various strategies such as road safety law enforcement, license issuance, adapting new technologies like safety cameras and raising awareness can be implemented to improve the road safety concerns among young drivers.

Keywords: driving behavior, Graduated Driver Licensing System (GLDS), road safety, UAE drivers, young drivers

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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: Asaad Y. Shamseldin

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Analytical probabilistic approach is an innovative approach for urban stormwater modeling. It can provide information about the long-term performance of a stormwater management facility without being computationally very demanding. This paper explores the application of the analytical probabilistic approach in New Zealand. The paper presents the results of a case study aimed at development of an objective way of identifying what constitutes a rainfall storm event and the estimation of the corresponding statistical properties of storms using two selected automatic rainfall stations located in the Auckland region in New Zealand. The storm identification and the estimation of the storm statistical properties are regarded as the first step in the development of the analytical probabilistic models. The paper provides a recommendation about the definition of the storm inter-event time to be used in conjunction with the analytical probabilistic approach.

Keywords: hydrology, rainfall storm, storm inter-event time, New Zealand, stormwater management

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Authors: Shirly May Balais

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This study aims to evaluate the effects of vocabulary instruction in improving the students’ learning in science. The teacher-researcher utilized the vocabulary instructional materials in enriching the science vocabulary of grade four learners. The students were also given an achievement test to determine the effects of vocabulary instructional materials. The assessment indicated that students had shown improvement in comprehension and science literacy. This also helps the students to grasp, understand, and communicate appropriate science concepts and the integration of imagery makes learning science fun. In this research, descriptive qualitative methods and observation interviews were used to describe the effects of using vocabulary instructional materials in improving the science vocabulary of grade four learners. The students’ perceptions were studied, analyzed, and interpreted qualitatively.

Keywords: instruction, learning, science, vocabulary

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Authors: Fatemeh Asadi Farsad, Sima Modirkhameneh

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The purpose of this study was to explore the pattern of Psychological Well-Being (PWB) of Iranian male and female EFL teachers during the pandemic. It was intended to see if such a drastic change in the context and mode of teaching affects teachers' PWB. Furthermore, the possible difference between the six elements of PWB of Iranian EFL male vs. female teachers during the pandemic was investigated. The other purpose was to find out the EFL teachers’ perceptions of any modifications, and factors leading to such modifications in their PWB during pandemic. For the purpose of this investigation, a total of 81 EFL teachers (59 female, 22 male) with an age range of 25 to 35 were conveniently sampled from different cities in Iran. Ryff’s PWB questionnaire was sent to participant teachers through online platforms to elicit data on their PWB. As for their perceptions on the possible modifications and the factors involved in PWB during pandemic, a set of semi-structured interviews were run among both sample groups. The findings revealed that male EFL teachers had the highest mean on personal growth, followed by purpose of life, and self-acceptance and the lowest mean on environmental mastery. With a slightly similar pattern, female EFL teachers had the highest mean on personal growth, followed by purpose in life, and positive relationship with others with the lowest mean on environmental mastery. However, no significant difference was observed between the male and female groups’ overall means on elements of PWB. Additionally, participants perceived that their anxiety level in online classes altered due to factors like (1) Computer literacy skills, (2) Lack of social communications and interactions with colleagues and students, (3) Online class management, (4) Overwhelming workloads, and (5) Time management. The study ends with further suggestions as regards effective online teaching preparation considering teachers PWB, especially at severe situations such as covid-19 pandemic. The findings offer to determine the reformations of educational policies concerning enhancing EFL teachers’ PWB through computer literacy courses and stress management courses. It is also suggested that to proactively support teachers’ mental health, it is necessary to provide them with advisors and psychologists if possible for free. Limitations: One limitation is the small number of participants (81), suggesting that future replications should include more participants for reliable findings. Another limitation is the gender imbalance, which future studies should address to yield better outcomes. Furthermore, Limited data gathering tools suggest using observations, diaries, and narratives for more insights in future studies. The study focused on one model of PWB, calling for further research on other models in the literature. Considering the wide effect of the COVID-19 pandemic, future studies should consider additional variables (e.g., teaching experience, age, income) to understand Iranian EFL teachers’ vulnerabilities and strengths better.

Keywords: online teaching, psychological well-being, female and male EFL teachers, pandemic

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Authors: Seulki Lee, Seoung Bum Kim

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Statistical process control (SPC) is a practical and effective method for quality control. The most important and widely used technique in SPC is a control chart. The main goal of a control chart is to detect any assignable changes that affect the quality output. Most conventional control charts, such as Hotelling’s T2 charts, are commonly based on the assumption that the quality characteristics follow a multivariate normal distribution. However, in modern complicated manufacturing systems, appropriate control chart techniques that can efficiently handle the nonnormal processes are required. To overcome the shortcomings of conventional control charts for nonnormal processes, several methods have been proposed to combine statistical learning algorithms and multivariate control charts. Statistical learning-based control charts, such as support vector data description (SVDD)-based charts, k-nearest neighbors-based charts, have proven their improved performance in nonnormal situations compared to that of the T2 chart. Beside the nonnormal property, time-varying operations are also quite common in real manufacturing fields because of various factors such as product and set-point changes, seasonal variations, catalyst degradation, and sensor drifting. However, traditional control charts cannot accommodate future condition changes of the process because they are formulated based on the data information recorded in the early stage of the process. In the present paper, we propose a SVDD algorithm-based control chart, which is capable of adaptively monitoring time-varying and nonnormal processes. We reformulated the SVDD algorithm into a time-adaptive SVDD algorithm by adding a weighting factor that reflects time-varying situations. Moreover, we defined the updating region for the efficient model-updating structure of the control chart. The proposed control chart simultaneously allows efficient model updates and timely detection of out-of-control signals. The effectiveness and applicability of the proposed chart were demonstrated through experiments with the simulated data and the real data from the metal frame process in mobile device manufacturing.

Keywords: multivariate control chart, nonparametric method, support vector data description, time-varying process

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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: Hang Lo Lee, Ki Il Song, Hee Hwan Ryu

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An accurate prediction of TBM(Tunnel Boring Machine) performance is very difficult for reliable estimation of the construction period and cost in preconstruction stage. For this purpose, the aim of this study is to analyze the evaluation process of various prediction models published since 2000 for TBM performance, and to select the optimal input parameters for the prediction model. A classification system of TBM performance prediction model and applied methodology are proposed in this research. Input and output parameters applied for prediction models are also represented. Based on these results, a statistical analysis is performed using the collected data from shield TBM tunnel in South Korea. By performing a simple regression and residual analysis utilizinFg statistical program, R, the optimal input parameters are selected. These results are expected to be used for development of prediction model of TBM performance.

Keywords: TBM performance prediction model, classification system, simple regression analysis, residual analysis, optimal input parameters

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Authors: Pitak Keawbunsong, Sathaporn Promwong

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This paper presents an investigation on the efficiency of the optimized Davison path loss model in order to look for a suitable path loss model to design and planning DTTV propagation for small and medium urban areas in southern Thailand. Hadyai City in Songkla Province is chosen as the case study to collect the analytical data on the electric field strength. The optimization is conducted through the least square method while the efficiency index is through the statistical value of relative error (RE). The result of the least square method is the offset and slop of the frequency to be used in the optimized process. The statistical result shows that RE of the old Davidson model is at the least when being compared with the optimized Davison and the Hata models. Thus, the old Davison path loss model is the most accurate that further becomes the most optimized for the plan on the propagation network design.

Keywords: DTTV propagation, path loss model, Davidson model, least square method

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Authors: Lorato Itumeleng Kenosi

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Background: Negative attitudes towards the mentally ill are widespread and a course for concern as they have a detrimental impact on individuals affected by mental illness. A possible avenue for changing attitudes towards mental illness is through mental health literacy. In a college or university setting, an abnormal psychology course may be introduced in an attempt to change student’s attitudes towards the mentally ill. Objective: To determine if and how students’ attitudes towards the mentally ill change as a result of taking a course in abnormal psychology. Methods: Twenty nine (29) students were recruited from an abnormal psychology class at the University of Botswana. Attitude Scale for Mental Illness (ASMI) questionnaire was administered to participants at the beginning and end of the semester. SPSS was employed to analyze data. Pooled means were used to determine whether the student’s attitudes towards mental illness were negative or positive. A mean of 2.5 translated to negative attitude for both total attitude and attitudes in different domains of the scale. Paired sample t-test was then used to assess whether any changes noted in attitudes were statistically significant or not. Statistical significance was assumed at p < 0.05. Results: Students’ general attitude towards mental illness remained positive although the pooled mean value increased from 2.08 to 2.24. The change was not statistically significant. In relation to different sub scales, the values of the pooled means for all the sub scales showed an increase although the changes were not statistically significant except for the Stereotyping sub scale (p = 0.031). The stereotyping domain reflected a statistically significant change in student’s attitude from positive attitude to negative (X² = 2.06 to X² = 2.55). For the pessimistic prediction domain, students consistently showed a negative attitude (X² = 3.34 to X² = 3.55). The other 4 domains indicated that students had positive attitude toward mentally ill throughout. Discussion: Abnormal psychology students have a positive attitude towards the mentally ill generally. This could be attributed to the fact that all students in the abnormal psychology course are majoring in psychology and research has shown that interest in psychology can affect one’s attitude towards mental illness. The students continuously held the view that people with mental illness are unlikely to improve as evidenced by a high score for Pessimistic prediction domain for both pre and post-test. Students initially had no stereotyping attitude towards the mentally ill, but at the end of the course, they were of the opinion that people with mental illness can be defined in a certain behavioural pattern and mental ability. This results could be an indication that students have learnt well how to differentiate abnormal from normal behaviour not necessarily that students had developed a negative attitude. Conclusion: A course in abnormal psychology does have an impact on the students’ attitudes towards the mentally ill. The impact does not solely depend on knowledge of mental illness but also on several other factors such as contact with the mentally ill, interest in psychology, and teaching methods. However, it should be noted that sometimes improved knowledge in mental illness can be misunderstood for a negative attitude. For example, stereotyping attitudes may be a reflection of the ability to differentiate between abnormal and normal behaviour.

Keywords: attitudes, mental illness, psychopathology, students

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Authors: Josip Vasilj, Petar Sarajcev, Damir Jakus

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One of the major difficulties introduced with wind power penetration is the inherent uncertainty in production originating from uncertain wind conditions. This uncertainty impacts many different aspects of power system operation, especially the balancing power requirements. For this reason, in power system development planing, it is necessary to evaluate the potential uncertainty in future wind power generation. For this purpose, simulation models are required, reproducing the performance of wind power forecasts. This paper presents a wind power forecast error simulation models which are based on the stochastic process simulation. Proposed models capture the most important statistical parameters recognized in wind power forecast error time series. Furthermore, two distinct models are presented based on data availability. First model uses wind speed measurements on potential or existing wind power plant locations, while the seconds model uses statistical distribution of wind speeds.

Keywords: wind power, uncertainty, stochastic process, Monte Carlo simulation

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Authors: Faisal AlShammari, Abdulmajid Addali, Mosab Alrashed

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It is widely acknowledged that bearing failures are the primary reason for breakdowns in rotating machinery. These failures are extremely costly, particularly in terms of lost production. Roller bearings are widely used in industrial machinery and need to be maintained in good condition to ensure the continuing efficiency, effectiveness, and profitability of the production process. The research presented here is an investigation of the use of acoustic emission (AE) to monitor bearing conditions at low speeds. Many machines, particularly large, expensive machines operate at speeds below 100 rpm, and such machines are important to the industry. However, the overwhelming proportion of studies have investigated the use of AE techniques for condition monitoring of higher-speed machines (typically several hundred rpm, or even higher). Few researchers have investigated the application of these techniques to low-speed machines ( < 100 rpm). This paper addressed this omission and has established which, of the available, AE techniques are suitable for the detection of incipient faults and measurement of fault growth in low-speed bearings. The first objective of this paper program was to assess the applicability of AE techniques to monitor low-speed bearings. It was found that the measured statistical parameters successfully monitored bearing conditions at low speeds (10-100 rpm). The second objective was to identify which commonly used statistical parameters derived from the AE signal (RMS, kurtosis, amplitude and counts) could identify the onset of a fault in the out race. It was found that these parameters effectually identify the presence of a small fault seeded into the outer races. Also, it is concluded that rotational speed has a strong influence on the measured AE parameters but that they are entirely independent of the load under such load and speed conditions.

Keywords: acoustic emission, condition monitoring, NDT, statistical analysis

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Authors: Siriporn Poolsuwan

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This research aims to explore the information needs, information usages, and problems of information usage of the older people club’s members in Dusit District, Bangkok. There are 12 clubs and 746 club’s members in this district. The research results use for older person service in this district. Data is gathered from 252 club’s members by using questionnaires. The quantitative approach uses in research by percentage, means and standard deviation. The results are as follows (1) The older people need Information for entertainment, occupation and academic in the field of short story, computer work, and religion and morality. (2) The participants use Information from various sources. (3) The Problem of information usage is their language skills because of the older people’s literacy problem.

Keywords: information behavior, older person, information seeking, knowledge discovery and data mining

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Authors: Jihad S. Daba, J. P. Dubois

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Understanding the statistics of non-isotropic scattering multipath channels that fade randomly with respect to time, frequency, and space in a mobile environment is very crucial for the accurate detection of received signals in wireless and cellular communication systems. In this paper, we derive stochastic models for the probability density function (PDF) of the shift in the carrier frequency caused by the Doppler Effect on the received illuminating signal in the presence of a dominant line of sight. Our derivation is based on a generalized Clarke’s and a two-wave partially developed scattering models, where the statistical distribution of the frequency shift is shown to be consistent with the power spectral density of the Doppler shifted signal.

Keywords: Doppler shift, filtered Poisson process, generalized Clark’s model, non-isotropic scattering, partially developed scattering, Rician distribution

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Authors: Sajad Shokohuyar, Mahsa Zomorrodi Anbaji, Saghar Pouyan Shad

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According to fast technology growth, modern banking tries to decrease going to banks’ branches and increase customers’ consent. One of the problems which banks face is securing customer’s password. The banks’ solution is one time password creation system. In this research by adapting from acceptance of technology model theory, assesses factors that are effective on banking in Iran especially in using one time password machine by one of the private banks of Iran customers. The statistical population is all of this bank’s customers who use electronic banking service and one time password technology and the questionnaires were distributed among members of statistical population in 5 selected groups of north, south, center, east and west of Tehran. Findings show that confidential preservation, education, ease of utilization and advertising and informing has positive relations and distinct hardware and age has negative relations.

Keywords: security, electronic banking, one time password, information technology

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Authors: Banca Patricia Pena Revuelta, Ramiro Gonzalez Avalos, Juan Leonardo Rocha Valdez, Jose Gonzalez Avalos, Karla Rodriguez Hernandez

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Probiotics are a promising alternative to improve productivity and animals' health. In addition, they can be part of the composition of different types of products, including foods (functional foods), medicines, and dietary supplements. The objective of the present work was to evaluate the effect of the feeding of Holstein calves supplemented with bacillus subtilis PB6 in morbidity and mortality. 60 newborn animals were used, randomly included in 1 of 3 treatments. The treatments were as follows: T1 = control, T2 = 10 g / calf / day. The first takes within 20 min after birth, T3 = 10 g / calf/day. The first takes between 12 and 24 h after birth. In all the treatments, 432 L of pasteurized whole milk divided into two doses/day 07:00 and 15:00, respectively, were given for 60 days. The addition of bacillus subtilis PB6 was carried out in the milk tub at the time of feeding them. The first colostrum intake (2 L • intake) was given within 2 h after birth, after which they were given a second 6 h after the first one. The diseases registered to monitor the morbidity and mortality of the calves were: diarrhea and pneumonia. The registry was carried out from birth to 60 days of life. The parameter evaluated was food consumption. The variable statistical analysis was performed using analysis of variance, and comparison of means was performed using the Tukey test. The value of P < 0.05 was used to consider the statistical difference. The results of the present study in relation to the consumption of food show no statistical difference P < 0.05 between treatments (14,762, 11,698, and 12,403 kg of food average, respectively). Calves group to which they were not provided Bacillus subtilis PB6 obtained higher feed intake. The addition of Bacillus subtilis PB6 in feeding calves does not increase feed intake.

Keywords: feeding, development, milk, probiotic

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Authors: Sachin Singh, Thomas Penzel, Dinesh Nandan

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Accurate identification of Sleep Apnea Hypopnea Syndrom Diagnosis is difficult problem for human expert because of variability among persons and unwanted noise. This paper proposes the diagonosis of Sleep Apnea Hypopnea Syndrome (SAHS) using airflow, ECG, Pulse and SaO2 signals. The features of each type of these signals are extracted using statistical methods and ANN learning methods. These extracted features are used to approximate the patient's Apnea Hypopnea Index(AHI) using sample signals in model. Advance signal processing is also applied to snore sound signal to locate snore event and SaO2 signal is used to support whether determined snore event is true or noise. Finally, Apnea Hypopnea Index (AHI) event is calculated as per true snore event detected. Experiment results shows that the sensitivity can reach up to 96% and specificity to 96% as AHI greater than equal to 5.

Keywords: neural network, AHI, statistical methods, autoregressive models

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Authors: Shweta Kumari, Parmjit S. Panesar, Manab B. Bera

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The hydrolysis of lactose using β-galactosidase is one of the most promising biotechnological applications, which has wide range of potential applications in food processing industries. However, due to intracellular location of the yeast enzyme, and expensive extraction methods, the industrial applications of enzymatic hydrolysis processes are being hampered. The use of permeabilization technique can help to overcome the problems associated with enzyme extraction and purification of yeast cells and to develop the economically viable process for the utilization of whole cell biocatalysts in food industries. In the present investigation, standardization of permeabilization process of novel yeast isolate was carried out using a statistical model approach known as Response Surface Methodology (RSM) to achieve maximal b-galactosidase activity. The optimum operating conditions for permeabilization process for optimal β-galactosidase activity obtained by RSM were 1:1 ratio of toluene (25%, v/v) and ethanol (50%, v/v), 25.0 oC temperature and treatment time of 12 min, which displayed enzyme activity of 1.71 IU /mg DW.

Keywords: β-galactosidase, optimization, permeabilization, response surface methodology, yeast

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Authors: Bekir Mugayitoglu

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This work shares pre-service teachers' experiences with the Book Creator application during the face-to-face class. Participants for this work were pre-service teachers in a semester-long instructional technology course who developed their own e-books. The work was conducted during the Fall of 2023. Eleven pre-service teachers completed the project, producing books appropriate to their area of concentration. Analysis of participant progress reports shows, that Exemplars showcase creative ways to prepare pre-service teachers to design their own books and have an opportunity to use mobile apps to create a variety of e-material options. The findings support future opportunities for pre-service teachers to design and implement technology-supported literacy applications to integrate into their own classroom pedagogy.

Keywords: scaffolding, e-book, classroom pedagogy, face-to-face class

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Authors: Raptis Sotirios

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Health and social care (HSc) services planning and scheduling are facing unprecedented challenges due to the pandemic pressure and also suffer from unplanned spending that is negatively impacted by the global financial crisis. Data-driven can help to improve policies, plan and design services provision schedules using algorithms assist healthcare managers’ to face unexpected demands using fewer resources. The paper discusses services packing using statistical significance tests and machine learning (ML) to evaluate demands similarity and coupling. This is achieved by predicting the range of the demand (class) using ML methods such as CART, random forests (RF), and logistic regression (LGR). The significance tests Chi-Squared test and Student test are used on data over a 39 years span for which HSc services data exist for services delivered in Scotland. The demands are probabilistically associated through statistical hypotheses that assume that the target service’s demands are statistically dependent on other demands as a NULL hypothesis. This linkage can be confirmed or not by the data. Complementarily, ML methods are used to linearly predict the above target demands from the statistically found associations and extend the linear dependence of the target’s demand to independent demands forming, thus groups of services. Statistical tests confirm ML couplings making the prediction also statistically meaningful and prove that a target service can be matched reliably to other services, and ML shows these indicated relationships can also be linear ones. Zero paddings were used for missing years records and illustrated better such relationships both for limited years and in the entire span offering long term data visualizations while limited years groups explained how well patients numbers can be related in short periods or can change over time as opposed to behaviors across more years. The prediction performance of the associations is measured using Receiver Operating Characteristic(ROC) AUC and ACC metrics as well as the statistical tests, Chi-Squared and Student. Co-plots and comparison tables for RF, CART, and LGR as well as p-values and Information Exchange(IE), are provided showing the specific behavior of the ML and of the statistical tests and the behavior using different learning ratios. The impact of k-NN and cross-correlation and C-Means first groupings is also studied over limited years and the entire span. It was found that CART was generally behind RF and LGR, but in some interesting cases, LGR reached an AUC=0 falling below CART, while the ACC was as high as 0.912, showing that ML methods can be confused padding or by data irregularities or outliers. On average, 3 linear predictors were sufficient, LGR was found competing RF well, and CART followed with the same performance at higher learning ratios. Services were packed only if when significance level(p-value) of their association coefficient was more than 0.05. Social factors relationships were observed between home care services and treatment of old people, birth weights, alcoholism, drug abuse, and emergency admissions. The work found that different HSc services can be well packed as plans of limited years, across various services sectors, learning configurations, as confirmed using statistical hypotheses.

Keywords: class, cohorts, data frames, grouping, prediction, prob-ability, services

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Authors: Faisal Alshammari, Abdulmajid Addali, Mosab Alrashed, Taihiret Alhashan

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The application of acoustic emission techniques is gaining popularity, as it can monitor the condition of gears and bearings and detect early symptoms of a defect in the form of pitting, wear, and flaking of surfaces. Early detection of these defects is essential as it helps to avoid major failures and the associated catastrophic consequences. Signal processing techniques are required for early defect detection – in this article, a time domain technique called the Energy Index (EI) is used. This article presents an investigation into the Energy Index’s effectiveness to detect early-stage defect initiation and deterioration, and compares it with the common r.m.s. index, Kurtosis, and the Kolmogorov-Smirnov statistical test. It is concluded that EI is a more effective technique for monitoring defect initiation and development than other statistical parameters.

Keywords: acoustic emission, signal processing, kurtosis, Kolmogorov-Smirnov test

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Authors: Nishi Bhuvandas, P. V. Timbadiya, P. L. Patel, P. D. Porey

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Recent perceived climate variability raises concerns with unprecedented hydrological phenomena and extremes. Distribution and circulation of the waters of the Earth become increasingly difficult to determine because of additional uncertainty related to anthropogenic emissions. According to the sixth Intergovernmental Panel on Climate Change (IPCC) Technical Paper on Climate Change and water, changes in the large-scale hydrological cycle have been related to an increase in the observed temperature over several decades. Although many previous research carried on effect of change in climate on hydrology provides a general picture of possible hydrological global change, new tools and frameworks for modelling hydrological series with nonstationary characteristics at finer scales, are required for assessing climate change impacts. Of the downscaling techniques, dynamic downscaling is usually based on the use of Regional Climate Models (RCMs), which generate finer resolution output based on atmospheric physics over a region using General Circulation Model (GCM) fields as boundary conditions. However, RCMs are not expected to capture the observed spatial precipitation extremes at a fine cell scale or at a basin scale. Statistical downscaling derives a statistical or empirical relationship between the variables simulated by the GCMs, called predictors, and station-scale hydrologic variables, called predictands. The main focus of the paper is on the need for using statistical downscaling techniques for projection of local hydrometeorological variables under climate change scenarios. The projections can be then served as a means of input source to various hydrologic models to obtain streamflow, evapotranspiration, soil moisture and other hydrological variables of interest.

Keywords: climate change, downscaling, GCM, RCM

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Authors: Rima T. Alfaraj, Murtadha J. Al Tammar, Khaqan Khan, Khalid M. Alruwaili

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OBJECTIVE/SCOPE (25-75): Caliper logging data provides critical information about wellbore shape and deformations, such as stress-induced borehole breakouts or washouts. Multiarm mechanical caliper logs are often run using wireline, which can be time-consuming, costly, and/or challenging to run in certain formations. To minimize rig time and improve operational safety, it is valuable to develop analytical solutions that can estimate caliper logs using available Logging-While-Drilling (LWD) data without the need to run wireline caliper logs. As a first step, the objective of this paper is to perform statistical analysis using an extensive datasetto identify important physical parameters that should be considered in developing such analytical solutions. METHODS, PROCEDURES, PROCESS (75-100): Caliper logs and LWD data of eleven wells, with a total of more than 80,000 data points, were obtained and imported into a data analytics software for analysis. Several parameters were selected to test the relationship of the parameters with the measured maximum and minimum caliper logs. These parameters includegamma ray, porosity, shear, and compressional sonic velocities, bulk densities, and azimuthal density. The data of the eleven wells were first visualized and cleaned.Using the analytics software, several analyses were then preformed, including the computation of Pearson’s correlation coefficients to show the statistical relationship between the selected parameters and the caliper logs. RESULTS, OBSERVATIONS, CONCLUSIONS (100-200): The results of this statistical analysis showed that some parameters show good correlation to the caliper log data. For instance, the bulk density and azimuthal directional densities showedPearson’s correlation coefficients in the range of 0.39 and 0.57, which wererelatively high when comparedto the correlation coefficients of caliper data with other parameters. Other parameters such as porosity exhibited extremely low correlation coefficients to the caliper data. Various crossplots and visualizations of the data were also demonstrated to gain further insights from the field data. NOVEL/ADDITIVE INFORMATION (25-75): This study offers a unique and novel look into the relative importance and correlation between different LWD measurements and wireline caliper logs via an extensive dataset. The results pave the way for a more informed development of new analytical solutions for estimating the size and shape of the wellbore in real-time while drilling using LWD data.

Keywords: LWD measurements, caliper log, correlations, analysis

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Authors: Patrik Jangl, Milan Mikuláštík

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The objective of the paper is to measure and compare market orientation of Swiss and Czech banks, as well as examine statistically the degree of influence it has on competitiveness of the institutions. The analysis of market orientation is based on the collecting, analysis and correct interpretation of the data. Descriptive analysis of market orientation describe current situation. Research of relation of competitiveness and market orientation in the sector of big international banks is suggested with the expectation of existence of a strong relationship. Partially, the work served as reconfirmation of suitability of classic methodologies to measurement of banks’ market orientation. Two types of data were gathered. Firstly, by measuring subjectively perceived market orientation of a company and secondly, by quantifying its competitiveness. All data were collected from a sample of small, mid-sized and large banks. We used numerical secondary character data from the international statistical financial Bureau Van Dijk’s BANKSCOPE database. Statistical analysis led to the following results. Assuming classical market orientation measures to be scientifically justified, Czech banks are statistically less market-oriented than Swiss banks. Secondly, among small Swiss banks, which are not broadly internationally active, small relationship exist between market orientation measures and market share based competitiveness measures. Thirdly, among all Swiss banks, a strong relationship exists between market orientation measures and market share based competitiveness measures. Above results imply existence of a strong relation of this measure in sector of big international banks. A strong statistical relationship has been proven to exist between market orientation measures and equity/total assets ratio in Switzerland.

Keywords: market orientation, competitiveness, marketing strategy, measurement of market orientation, relation between market orientation and competitiveness, banking sector

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Authors: Preetinder Kaur Randhawa

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The rural areas can be differentiated from urban areas in terms of their economic activities as rural areas are primarily involved in agricultural sector and provide natural resources whereas, urban areas are primarily involved in infrastructure sector and provide manufacturing services. Census of India defines a Census Town as an area which satisfies the following three criteria i.e. population exceeds 5000, at least 75 percent of male population engaged in non-agricultural sector and minimum population density of 400 persons per square kilometers. Urban areas can be attributed to the improvement of transport facilities, the massive decline in agricultural, especially male workers and workers shift to non-agricultural activities. This study examines the pattern, process of rural areas transformed into urban areas/ census town. The study has analyzed the various factors which are responsible for land transformation as well as the socio-economic transformation of the village population. Nilpur (CT) which belongs to Rajpura Tehsil in Patiala district, Punjab has been selected for the present study. The methodology adopted includes qualitative and quantitative research design, methods based on secondary data. Secondary data has been collected from unpublished revenue record office of Rajpura Tehsil and Primary Census Abstract of Patiala district, Census of India 2011. The results have showed that rate of transformation of a village to census town in Rajpura Tehsil has been one of highest among other villages. The census town has evolved through the evolutionary process of human settlement which grows in size, population and physical development. There must be a complete economic transformation and attainment of high level of technological development. Urban design and construction of buildings and infrastructure can be carried out better and faster and can be used to aid human habitation with the enhancement of quality of life. The study has concluded that in the selected area i.e Nilpur (CT) literacy rate has increased to 72.1 percent in year 2011 from 67.6 percent in year 2001. Similarly non-agricultural work force has increased to 95.2 percent in year 2011 from 81.1 percent in year 2001. It is very much clear that the increased literacy rate has put a positive impact on the involvement of non-agricultural workers have enhanced. The study has concluded that rural-urban linkages are important tools for understanding complexities of people livelihood and their strategies which involve mobility migration and the diversification of income sources and occupations.

Keywords: Census Town, India, Nilpur, Punjab

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Authors: Hyun-Woo Cho

Abstract:

Detection of incipient abnormal events in production processes is important to improve safety and reliability of manufacturing operations and reduce losses caused by failures. The construction of calibration models for predicting faulty conditions is quite essential in making decisions on when to perform preventive maintenance. This paper presents a multivariate calibration monitoring approach based on the statistical analysis of process measurement data. The calibration model is used to predict faulty conditions from historical reference data. This approach utilizes variable selection techniques, and the predictive performance of several prediction methods are evaluated using real data. The results shows that the calibration model based on supervised probabilistic model yielded best performance in this work. By adopting a proper variable selection scheme in calibration models, the prediction performance can be improved by excluding non-informative variables from their model building steps.

Keywords: calibration model, monitoring, quality improvement, feature selection

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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 105