Search results for: Statistical%20package%20IBM%20SPSS%2020

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: Siti Dewi Aisyah

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Islamic Modest Fashion has become one of the emerging industries. It is said that social media has making a role in its development. From designers, hijabi bloggers and then instagrammers, they are often seen posting their everyday outfits. They want to combine their faith with cutting-edge fashion trend. Muslim consumers has become a potential targeted market due to the increasing of people wearing hijab. Muslim consumers are projected to spend $327 bilion on clothing by 2020. Indonesia, as the biggest Muslim majority country, has targeted to be The World’s Center for Muslim Fashion in the world as its national branding by 2020. This study will examine how social media especially Blog and Instagram can lead the movement of Islamic Modest Fashion in Indonesia, how it also brings consumer culture to hijabi and as the result it triggers Indonesia to brand itself and how all the elements in Indonesia including the designers, bloggers or instagrammers and also Indonesian Agency for Creative Economy together work to make its dream come true. This research will be conducted through interviews with several elements mentioned, and internet, blog, Instagram and Youtube analysis through visual analysis that also examine the semiotic meaning behind the picture that are posted by the people on the social media especially about the Islamic Modest Fashion trend. This research also contains a literature review of a diverse group of works on topics related to the study. This research will be examined through several theoretical frameworks including the study of social media, fashion culture and consumer culture. Fashion and consumer culture are also two main topics because fashion furthermore leads to consumer culture. The possible benefit of this research is to be a reference literature of Islamic Modest Fashion and social media’s role especially in an Indonesian context.

Keywords: blog, instagram, consumer culture, modest fashion, social media, visual analysis

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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: 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: Chen ChihYu, Tang Wen Tzu, Chen Kuang Hui

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Aim —To compare the dismount skill between Taiwanese and elite international gymnastics in parallel bars following the 2017-2020 code of points. Methods—The gymnasts who advanced to the parallel bars event finals of these four competitions including World Championships, Universiade, the National Games of Taiwan, and the National Intercollegiate Athletic Games of Taiwan both 2017 and 2019 were selected in this study. The dismount skill of parallel bars was analyzed, and the average difficulty score was compared by one-way ANOVA. Descriptive statistics were applied to present the type of dismount skill and the difficulty of each gymnast in these four competitions. The data from World Championships and Universiade were combined as the international group (INT), and data of Taiwanese National Games and National Intercollegiate Athletic Games were also combined as the national group (NAT). The differences between INT and NAT were analyzed by the Chi-square test. The statistical significance of this study was set at α= 0.05. Results— i) There was a significant difference in the mean parallel bars dismount skill in these four competitions analyzed by one-way ANOVA. Both dismount scores of World Championships and Universiade were significantly higher than in Taiwanese National Games and National Intercollegiate Athletic Games (0.58±0.08 & 0.56±0.08 > 0.42±0.06 & 40±0.06, p < 0.05). ii) Most of the gymnasts in World Championships and Universiade selected the 0.6-point skill as the parallel bars dismount element, and for the Taiwanese National Games and the National Intercollegiate Athletic Games, most of the gymnasts performed the 0.4-point dismount skill. iii) The result of the Chi-square test has shown that there was a significant difference in the selection of parallel bars dismount skill. The INT group used the E or E+ difficulty element as the dismount skill, and the NAT group selected the D or D- difficulty element. Conclusion— The level of parallel bars dismount in Taiwanese gymnastics is inferior to elite international gymnastics. It is suggested that Taiwanese gymnastics must try to practice the F difficulty dismount (double salto forward tucked with half twist) in the future.

Keywords: Artistic Gymnastics World Championships, dismount, difficulty score, element

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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: Delband Yekta Moazami

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Background: For proper care and treatment of HIV patients and drug users, the medical staff and physicians must have a correct and positive attitude and knowledge towards such patients. We aimed to assess the attitudes in a sample of health care workers (HCW) working in different hospitals and clinics and medical students in Georgia towards HIV infected people and drug users in Tbilisi. Method: We conducted a cross-sectional study to assess attitudes of health care workers towards people living with HIV and drug users in hospitals and clinics in Tbilisi. The study was carried out from 1st of May 2020 till 30th of September 2020. Data were collected using a self-administered structured online questionnaire. With this tool we evaluated four facets of attitudes: Discrimination, Acceptance of HIV/AIDS patients, Acceptance of drug users and Fear. All data were imported and analyzed with the software SPSS 22 for windows. Results: In total data was collected from168 respondents, that among them 107 (65%) were women and majority of the participants were medical doctors. Women had more acceptance attitudes rather than men towards drug abusers. We found significant differences regarding expressing negative attitudes among HCW who were more than 50 years old comparing with other age groups in all four aspects. Medical doctors expressed more acceptances towards people with HIV and drug users comparing two other groups. Also our study revealed that the group with working experience 21 years and more, showed more discriminatory attitudes comparing other groups. Conclusion: Based on our study findings, there are significant differences regarding respondent’s attitudes based on gender, medical specialty and working experience in health care system. People struggling with HIV and drug use need nonjudgmental and positive behaviors from health care workers and physicians in order to help them for harm reduction and receiving appropriate treatment.

Keywords: hiv, addiction, attitudes, healthcare workers

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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: Aayush Anant, Roshni Thendiyath

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Aridity impacts on agriculture, as well as ecological, human health, and economic activities. In the present study, the effect of climate change on aridity index has been analysed in South Bihar for the past 30 year period by five types of aridity indices as Lang AI, De-Martonne AI, Erinc AI, Pinna combinative AI and UNEP AI. For the study of aridity index, the analysis of rainfall and temperature is significant. Rainfall was analysed for 30 year period from data of 23 gridded stations in for the period 1991-2020. The results show that rainfall pattern was decreasing with respect to previous decades for majority of stations. Trend of maximum, minimum and mean annual temperature has been observed, which shows increasing trend. Structural breakpoint was observed for mean annual temperature data series in year 2004. In period 1991-2004 mean annual temperature was 25.25 ºC, and in period 2005-2020, mean annual temperature was 25.7 ºC. Average aridity index has been calculated by all the above mentioned methods for whole 30 period. Lang AI shows that eastern part of study area is Humid type, and rest all is semi arid. De-Martonne AI also reveals that east part is humid, but rest of the study area is moist sub humid. According to Erinc AI and Pinna, combinative AI shows that whole south Bihar is dry sub humid and semi dry, respectively. UNEP AI shows most of the part as sub humid, and very small part in west is semi arid, while small part of east is humid. Temporal distribution of all the aridity indices shows a decreasing trend. This indicates a decrease in the humid areas in south Bihar for the selected time period.

Keywords: drought, aridity index, climate change, rainfall, temperature

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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: Aleksandra Dragojlov

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Since the election of Aleksandar Vučić and the Progressives, Serbia has witnessed a slow decline in media freedom, which has been worse than in the 1990s. Although the government adopted a package of three laws in August 2014 to bring the media landscape up to European standards, the implementation of the laws has been limited and marginal, with the progressives engaging in fake compliance. The adoption of the new media strategy for 2020-2025 in 2020 has not led to genuine domestic reform and compliance with EU conditionality. In fact, the EU Commission and journalists’ associations in Serbia have criticised the decline in Serbia’s media freedom citing continued attacks on journalists and indirect political and economic control through advertising and project co-financing, which continue to be features of the Serbian media landscape. In the absence of clear and credible EU conditionality, the decline of media freedom is in the eye of the beholder, where the gap between public engagements with Serbian politicians and the critical stance of progress reports regarding the degradation of the media have enabled Serbian elites to exploit this ambiguity to continue their strategy of fake compliance vis-a-vis rule of law. This study used a mixed methods approach combining both primary and secondary sources with those semi-structured interviews via Zoom, email, and in person with EU and Serbian officials and journalists. Our findings add to the studies where the lack of clear and credible conditionality has allowed Serbia politicians to exploit them in a manner that would suit their own interests, finding new means to retain their control over the media. We argued and concluded that it is this discrepancy between public engagements with Serbia and the progress reports in the area of freedom of expression that has not led to genuine domestic media reforms in Serbia and instead allowed Serbian elites to engage in a strategy of fake and even non-compliance towards media freedom conditionality.

Keywords: media freedom, EU conditionality, Serbia, fake compliance, EU integration, Chapter 23, justice and fundamental rights

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Authors: Wang Yichen, Haruka Yamashita

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In recent years, in the field of sports, decision making such as member in the game and strategy of the game based on then analysis of the accumulated sports data are widely attempted. In fact, in the NBA basketball league where the world's highest level players gather, to win the games, teams analyze the data using various statistical techniques. However, it is difficult to analyze the game data for each play such as the ball tracking or motion of the players in the game, because the situation of the game changes rapidly, and the structure of the data should be complicated. Therefore, it is considered that the analysis method for real time game play data is proposed. In this research, we propose an analytical model for "determining the optimal lineup composition" using the real time play data, which is considered to be difficult for all coaches. In this study, because replacing the entire lineup is too complicated, and the actual question for the replacement of players is "whether or not the lineup should be changed", and “whether or not Small Ball lineup is adopted”. Therefore, we propose an analytical model for the optimal player selection problem based on Small Ball lineups. In basketball, we can accumulate scoring data for each play, which indicates a player's contribution to the game, and the scoring data can be considered as a time series data. In order to compare the importance of players in different situations and lineups, we combine RNN (Recurrent Neural Network) model, which can analyze time series data, and NN (Neural Network) model, which can analyze the situation on the field, to build the prediction model of score. This model is capable to identify the current optimal lineup for different situations. In this research, we collected all the data of accumulated data of NBA from 2019-2020. Then we apply the method to the actual basketball play data to verify the reliability of the proposed model.

Keywords: recurrent neural network, players lineup, basketball data, decision making model

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Authors: Jogi Prayogo, Dwi Qaqa Prasetyatama, Rahmad Dwi Afandi, Kunto Arief Prasetyo, Viorel Herniza Leksono

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PT. Pertamina Trans Kontinental managed a fleet of 364 ships in 2018 - 2020. In that period, there were 8 incidents of ship damage, causing breakdown maintenance on 6 ships belonging to PT Pertamina Trans Kontinental throughout Indonesia's operational areas due to ropes entangled in propellers. The company's losses that were caused by the fouled propellers amounted to 306.35 Million Rupiah. Of the 8 incidents, Mooring Boat PSC I was taken as a pilot project for further analysis considering the location of the ship which is in Surabaya and Mooring Boat PSC I has experienced 2 incidents of rope entanglement that caused the company's losses due to the largest Breakdown Maintenance amounted to 200.99 Million Rupiah. After analyzing the rope entanglement in the ship's propeller based on the data of Mooring Boat PSC I related to the location of propellers that are often fouled in the conventional propulsion system, it was found that there is a suitable location for the implementation of SI KUMAN tool that serves to cut ropes to prevent the occurrence of rope entangled in ship propellers. The determination of SI KUMAN tool is based on the strength of the ship's material to be installed and a suitable design to prevent the occurrence of ropes being entangled in propellers. After the installation of the "SI KUMAN" tool and monitoring carried out for 1 year period (August 2020 - August 2021), it was found that SI KUMAN tool can eliminate the risk of fouled propeller incidents which previously occurred twice in one year so that the company's loss amounted to 200.99 Million Rupiah can be eliminated and SI KUMAN tool can still operate optimally.

Keywords: breakdown maintenance, mooring boat, fleet, fouled propeller, rope entangled, cut

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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: Mohammed A. Gharawi, Majed M. Khoja

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This paper is a report on the findings of a study conducted at the Institute of Public Administration (IPA) in Saudi Arabia. The paper applied both qualitative and quantitative research methods to assess the levels of basic computer applications’ skills among students enrolled in the preparatory programs of the institution. qualitative data have been collected from semi-structured interviews with the instructors who have previously been assigned to teach Introduction to information technology courses. Quantitative data were collected by executing a self-report questionnaire and a written statistical test. 380 enrolled students responded to the questionnaire and 142 accomplished the statistical test. The results indicate the lack of necessary skills to deal with computer applications among most of the students who are enrolled in the IPA’s preparatory programs.

Keywords: assessment, computer applications, computer literacy, Institute of Public Administration, Saudi Arabia

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Authors: Yi-Chu Liu, Hsiu-Huei Hung, Li-Hui Yang, Ming-Jyh Chen

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introduction: To promote environmental sustainability, the hospital formed a corporate volunteer team in 2016 to build the Green Experiential Education Center. Our green creation center utilizes attic space to achieve sustainability objectives such as energy efficiency and carbon reduction. Other than executing sustainable plans, the center emphasizes experiential education. We invite our community to actively participate in building a sustainable, economically viable environment. Since 2020, the China Medical University Hospital has provided medical care to the Tgbin community in Taichung City's Heping District. The tribe, primarily composed of Atayal people, the elderly comprise 18% of the total population, and these families' per capita income is relatively low compared to Taiwanese citizens elsewhere. Purpose / Methods: With the experiences at the Green Experiential Education Center, CMUH team identifies the following objectives: Create an aquaponic system to supply vulnerable local households with food. Create a solar renewable energy system to meet the electricity needs of vulnerable local households. Promote the purchase of green electricity certificates to reduce the hospital's carbon emissions and generate additional revenue for the local community. Materials and Methods: In March 2020, we visited the community and installed The aquaponic system in January 2021. CMUH spent 150,000NT (approximately 5000US dollars) in March 2021 to build a 100-square-meter aquaponic system. The production of vegetables and fish caught determines the number of vulnerable families that can be supported. The aquaponics system is a kind of Low energy consumption and environmentally friendly production method, and can simultaneously achieve energy saving, water saving, and fertilizer saving .In September 2023, CMUH will complete a solar renewable energy system. The system will cover an area of 308 square meters and costs approximately NT$240,000 (approximately US$8,000). The installation of electricity meters will enable statistical analysis of power generation. And complete the Taiwan National Renewable Energy Certificate application process. The green electricity certificate will be obtained based on the monthly power generation from the solar renewable energy system. Results: I Food availability and access are crucial considering the remote location and aging population. By creating a fish and vegetable symbiosis system, the vegetables and catches produced will enable economically disadvantaged families to lower food costs. In 2021 and 2022, the aquaponic system produced 52 kilograms of vegetables and 75 kilograms of catch. The production ensures the daily needs of 8 disadvantaged families. Conclusions: The hospital serves as a fortress for public health and the ideal setting for corporate social responsibility. China Medical University Hospital and the Green Experiential Education Center work to strengthen ties with rural communities and offer top-notch specialty medical care. We are committed to assisting people in escaping poverty and hunger as part of the 2030 Sustainable Development Goals.

Keywords: environmental education, sustainability, energy conservation, carbon emissions, rural area development

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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: 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: Gustavo Naranjo Maroto, Dolores Fernandez Martinez

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Context has always been essential to understand any reaction from every human being, and words, whether written or spoken, are definitely a powerful representative sample of human reaction. This study starts with an accurate breakdown of the context in which the current president of the US, Mr. Donald J. Trump is conveying his discourses in order to be able to judge them from a critical discourse analysis point of view. The present world’s scenario with a pandemic disease in form of Covid-19 that is threatening the world and certainly putting at risk the so called 'Welfare State', the role of the United States as the first superpower on earth nowadays, the very peculiar profile of President Trump not only as a politician but as a persona, and the fact of being on the verge of a very controversial presidential elections are without doubt a great and undeniable opportunity for the implementation of the critical discourse analysis methodology. Hence, this research will primarily analyze in detail some of the most interesting discourses delivered by Trump in different media since the very beginning of the outbreak of the coronavirus pandemic in the United States of America (February, 2020), sadly very often downplayed by President Trump, until the final result of the upcoming presidential election scheduled for Tuesday, November 3, 2020, where the political discourse has been dramatically downgraded to a very dangerous state, putting in jeopardy the fundamentals of the political fair play in terms of speech. Finally, the study will hopefully conclude with the final outcome of the data analyzed, allowing to picture how significant the context can be concerning linguistics on the one hand, in terms of shaping or altering the message that the issuer thought to convey in the first place, and on the other hand, generously assessing to what extend the recipients of the message are influenced by the message in terms of receptiveness.

Keywords: Covid-19, critical discourse analysis, Donald J. Trump, political discourse

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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: Huang Chiung Chiu

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This article is about the nursing experience of assisting an outpatient with premature menopause, osteoporosis and sarcopenia through a multi-discipline care model. The nursing period is from September 22nd, 2020, to December 7th, 2020, collecting data through interviews with the patient, observation, and physical assessment. It was found that the main health problems were insufficient nutrition, less physical need, insomnia, and potentially dangerous falls. As an outpatient nurse, the author observed that in recent years, the age group of women with premature menopause, osteoporosis and sarcopenia had shifted downward. Integrated multi-disciplinary interventions were provided upon the initial diagnosis of osteoporosis and sarcopenia. Under the outpatient care setting, the collaborative team works between the doctors, nutritionists, osteoporosis educators, rehabilitates, physical therapists and other specialized teams were applied to provide individualized, integrated multi-disciplinary care. Through empathy and the establishment of attentive care, companionship and trust, we discussed care plans and treatment guidelines with the case, providing accurate, complete disease information and feedback education to strengthen the patient’s knowledge and motivation for exercise. Nursing guidance regarding the dietary nutrition and adjustment of daily routine was provided to increase the self-care ability, improve the health problems of muscle weakness and insomnia, and prevent falls. For patients with postmenopausal osteoporosis and sarcopenia, it is recommended that the nurses coordinate the multi-discipline integrated care model, adjust patients’ lifestyle and diet, and establish a regular exercise plan so that the cases can be evaluated holistically to improve the quality of care and physical and mental comfort.

Keywords: multi-discipline care model, premature menopause, osteoporosis, sarcopenia, insomnia

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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: Hideaki Endo, Mika Goto

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The global outbreak of the COVID-19 pandemic has seriously affected railway businesses. The number of railway passengers decreased due to the decline in the number of commuters and business travelers to avoid crowded trains and a sharp drop in inbound tourists visiting Japan. This has affected not only railway businesses but also related businesses, including hotels, leisure businesses, and retail businesses at station buildings. In 2021, the companies were divided into profitable and loss-making companies. This division suggests that railway companies, particularly loss-making companies, needed to decrease operational inefficiency. To measure the impact of COVID-19 and discuss the sustainable management strategies of railway companies, we examine the cost inefficiency of Japanese listed railway companies by applying stochastic frontier analysis (SFA) to their operational and financial data. First, we employ the stochastic frontier cost function approach to measure inefficiency. The cost frontier function is formulated as a Cobb–Douglas type, and we estimated parameters and variables for inefficiency. This study uses panel data comprising 26 Japanese-listed railway companies from 2005 to 2020. This period includes several events deteriorating the business environment, such as the financial crisis from 2007 to 2008 and the Great East Japan Earthquake of 2011, and we compare those impacts with those of the COVID-19 pandemic after 2020. Second, we identify the characteristics of the best-practice railway companies and examine the drivers of cost inefficiencies. Third, we analyze the factors influencing cost inefficiency by comparing the profiles of the top 10 railway companies and others before and during the pandemic. Finally, we examine the relationship between cost inefficiency and the implementation of efficiency measures for each railway company. We obtained the following four findings. First, most Japanese railway companies showed the lowest cost inefficiency (most efficient) in 2014 and the highest in 2020 (least efficient) during the COVID-19 pandemic. The second worst occurred in 2009 when it was affected by the financial crisis. However, we did not observe a significant impact of the 2011 Great East Japan Earthquake. This is because no railway company was influenced by the earthquake in this operating area, except for JR-EAST. Second, the best-practice railway companies are KEIO and TOKYU. The main reason for their good performance is that both operate in and near the Tokyo metropolitan area, which is densely populated. Third, we found that non-best-practice companies had a larger decrease in passenger kilometers than best-practice companies. This indicates that passengers made fewer long-distance trips because they refrained from inter-prefectural travel during the pandemic. Finally, we found that companies that implement more efficiency improvement measures had higher cost efficiency and they effectively used their customer databases through proactive DX investments in marketing and asset management.

Keywords: COVID-19 pandemic, stochastic frontier analysis, railway sector, cost efficiency

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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: Dzul Fahmi Md. Nordin, Rosmini Omar

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This conceptual paper aims to explore the concept of National Talent Retention for a nation by extending the works on Talent Retention in organizations to the scope of nations. The objective of this paper is to explore the relationship of National Talent Retention as the dependent variable with the three explored value propositions namely Firm Value Proposition, Higher Education and Training Value Proposition and National Attractiveness Value Proposition as the independent variables. Life Satisfaction is introduced in this study as a moderating variable to explore possibilities of Life Satisfaction as a mediator for the relationship between National Value Proposition and National Talent Retention. Theories such as Migration, Value Propositions, Life Satisfaction, Human Resource Management and Resource Based View are referred to in order to understand and explore the concept of National Talent Retention. Malaysia is chosen as the background of this study since Malaysia represents a developing nation with progressive economic, education and national policy which presents an interesting background for this exploratory paper. Surprisingly, Malaysia is still facing the phenomenon of Brain Drain which if not handled properly will hinder its Vision 2020 to progress a fully developed nation by year 2020. Mixed methodology analysis is proposed in this paper to include both qualitative face-to-face interview as well as quantitative survey questionnaire to study on the value proposition factors explored. Target respondents are strictly confined to Malaysia’s local high skilled talents either residing in Malaysia or migrated abroad since this paper is mainly interested to study on the concept of National Talent Retention and how successful Malaysia is projecting its value propositions from the perception of high skilled talent Malaysians. It is hoped that this paper could contribute towards understanding National Talent Retention concept where, the model could be replicated to identify influential factors specific to other nations.

Keywords: national talent retention, national value proposition, life satisfaction, high skilled talents

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Authors: Rehana Khan

Abstract:

Background: The study investigates the experiences of Tiger Teams within the Sydney Local Health District during the COVID-19 pandemic. Aim: The aims were to understand the experiences of the Tiger Team members, to evaluate the effectiveness of Tiger Teams, and to elicit any learnings for future implementation of Tiger Teams in a similar context. Methods: Tiger Team members who worked from March 2020 to January 2022 were approached, with 23 members agreeing to participate in the study. Individual interviews were undertaken by a researcher on a virtual platform. Thematic analysis was used to analyse the data. Saturation was deemed to have been reached when no new themes or subthemes arose within the final three interviews. Results: Four themes emerged: diversity worked well in Tiger Teams; fear of the unknown and challenging conversations were the main challenges of Tiger Teams; improved use of resources and more structure around the strategy of the Tiger Team model would help in future implementations; and Sydney Local Health District’s response to the pandemic was uniformly considered effective in keeping the community safe. In relation to Sydney Local Health District’s response in future pandemics, participants suggested having a pool of staff in readiness to undertake Tiger Team duties when required; prioritise staff welfare at all levels of involvement during a pandemic; maintaining transparent communication and relationship building between Executive level, Tiger Team members and clinical floor level in relation to decision making; and improve documentation, including evaluations of the COVID-19 pandemic response. Implications: The study provides constructive insights into the experiences of Tiger Team members, and these findings will help inform future planning for surge and secondment of staff in public health emergencies.

Keywords: Tiger Team, pandemic response, future planning, COVID-19

Procedia PDF Downloads 58