Search results for: secure data sharing

Authors: Carolina Silva, João Nuno Oliveira, Rui Sousa, João Paulo Silva

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This study uses genetic algorithms to solve a job scheduling problem in a weaving factory. The underline problem regards an NP-Hard problem concerning unrelated parallel machines, with sequence-dependent setup times. This research uses real data regarding a weaving industry located in the North of Portugal, with a capacity of 96 looms and a production, on average, of 440000 meters of fabric per month. Besides, this study includes a high level of complexity once most of the real production constraints are applied, and several real data instances are tested. Topics such as data analyses and algorithm performance are addressed and tested, to offer a solution that can generate reliable and due date results. All the approaches will be tested in the operational environment, and the KPIs monitored, to understand the solution's impact on the production, with a particular focus on the total number of weeks of late deliveries to clients. Thus, the main goal of this research is to develop a solution that allows for the production of automatically optimized production plans, aiming to the tardiness minimizing.

Keywords: genetic algorithms, textile industry, job scheduling, optimization

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Authors: Francisco M. Silva

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Technology is evolving, creating an impact on our everyday lives and the telehealth industry. Telehealth encapsulates the provision of healthcare services and information via a technological approach. There are several benefits of using web-based methods to provide healthcare help. Nonetheless, few health and psychological help approaches combine this method with wearable sensors. This paper aims to create an online platform for users to receive self-care help and information using wearable sensors. In addition, researchers developing a similar project obtain a solid foundation as a reference. This study provides descriptions and analyses of the software and hardware architecture. Exhibits and explains a heart rate dynamic and efficient algorithm that continuously calculates the desired sensors' values. Presents diagrams that illustrate the website deployment process and the webserver means of handling the sensors' data. The goal is to create a working project using Arduino compatible hardware. Heart rate sensors send their data values to an online platform. A microcontroller board uses an algorithm to calculate the sensor heart rate values and outputs it to a web server. The platform visualizes the sensor's data, summarizes it in a report, and creates alerts for the user. Results showed a solid project structure and communication from the hardware and software. The web server displays the conveyed heart rate sensor's data on the online platform, presenting observations and evaluations.

Keywords: Arduino, heart rate BPM, microcontroller board, telehealth, wearable sensors, web-based healthcare

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Authors: Khadeeja Munawar, Shamsul Haque

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We examined the plausibility of transition theory suggesting that memories of transitional events, which give rise to a significant and persistent change in the fabric of daily life, are organized around the historically defined autobiographical periods (H-DAPs). 141 Pakistani older adults retrieved 10 autobiographical memories (AMs) each to 10 cue words. As the history of Pakistan is dominated by various political and nationwide transitional events, it was expected that the participants would recall memories with H-DAPs references. The content analysis revealed that 0.7% of memories had H-DAP references and 0.4% memories mentioned major transitional events such as War/Natural Disaster. There was a vivid reminiscence bump between 10 - 20 years of age in lifespan distribution of AMs. There were 67.9% social-focused AMs. Significantly more self-focused memories were reported by individuals who endorsed themselves as conservatives. Only a few H-DAPs were reported, although the history of Pakistan was dominated by numerous political, historical and nationwide transitional events. Memories within and outside of the bump period were mostly positive. The participants rarely used historical/political or nationwide significant events or periods to date the memories elicited. The intense and nationwide (as well as region-wise) significant historical/political events spawned across decades in the lives of participants of the present study but these events did not produce H-DAPs. The findings contradicted the previous studies on H-DAPs and transition theory. The dominance of social-focused AMs in the present study is in line with the past studies comparing the memories of collectivist and individualist cultures (i.e., European Americans vs. Asian, African and Latin-American cultures). The past empirical evidence shows that conservative values and beliefs are adopted as a coping strategy to feel secure in the face of danger when future is dominated with uncertainty and to connect to likeminded others. In the present study, conservative political ideology is somehow assisting the participants in living a stable life midst of their complex social worlds. The reminiscence bump, as well as dominance of positive memories within and outside the bump period, are in line with the narrative/identity account which states that the events and experiences during adolescence and early adulthood assimilate into a person’s lifelong narratives. Hence these events are used as identity markers and are more easily recalled later in life. Also, according to socioemotional theory and the positivity effect, the participants evaluated past events more positively as they grow up and the intensity of negative emotions decreased with time.

Keywords: autobiographical memory, historically defined autobiographical periods, narrative/identity account, Pakistan, reminiscence bump, SMS framework, transition theory

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Authors: Runglaksamee Rodkam

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The purpose of this research was to study the influence of accountants’ potential performance on their working process, a case study of Government Savings Banks in the northeast of Thailand. The independent variables included accounting knowledge, accounting skill, accounting value, accounting ethics, and accounting attitude, while the dependent variable included the success of the working process. A total of 155 accountants working for Government Savings Banks were selected by random sampling. A questionnaire was used as a tool for collecting data. Descriptive statistics in this research included percentage, mean, and multiple regression analyses. The findings revealed that the majority of accountants were female with an age between 35-40 years old. Most of the respondents had an undergraduate degree with ten years of experience. Moreover, the factors of accounting knowledge, accounting skill, accounting a value and accounting ethics and accounting attitude were rated at a high level. The findings from regression analysis of observation data revealed a causal relationship in that the observation data could explain at least 51 percent of the success in the accountants’ working process.

Keywords: influence, potential performance, success, working process

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Authors: Zichun Chu

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The issue of tribal poverty has always attracted attentions. Due to social and economic difficulties, the indigenous people's personal development and tribal development have been greatly restricted. Past studies have pointed out that poverty may come from a lack of education. The United Nations Sustainable Development Goals (SDGs) also stated that if we are to solve the poverty problem, providing education widely is an important key. According to the theory of intellectual capital adaptation, “being capable” and “willing to do” are the keys of development. Therefore, we can say that the "ability" and "will" of tribal residents for their tribal development is the core concern of the tribal development. This research was designed to investigate the career choice development model of indigenous tribe people by investigating the current status of human capital, social capital, and cultural capital of tribal residents. This study collected 327 questionnaires (70% of total households) from Truku tribe to answer the research question: Did education help them for job choosing decisions from the aspects of human capital, social capital, and cultural capital in tribal status. This project highlighted the ‘single tribal research approach’ to gain an in-depth understanding of the human capital formed under the unique culture of the tribe (Truku tribe). The results show that the education level of most research participants was high school, very few high school graduates chose to further their education to college level; due to the lack of education of their parents, the social capital was limited to support them for jobs choice, most of them work for labor and service industries; however, their culture capital was comparably rich for works, the sharing culture of Taiwanese indigenous people made their work status stable. The results suggested that we should emphasize more on the development of vocational education based on the tribe’s location and resources. The self-advocacy of indigenous people should be developed so that they would gain more power on making career decisions. This research project is part of a pilot project called “INDIGENOUS PEOPLES, POVERTY, AND DEVELOPMENT,” sponsored by the National Science and Technology Council of Taiwan. If this paper were accepted to present in the 2023 ICIP, it would be lovely if a panel is formed for me and other co-researchers (Chuanju Cheng, Chih-Yuan Weng, and YiXuan Chen), for the audience will be able to get a full picture of this pilot project.

Keywords: career choices, career model, indegenous career development, indigenous education, tribe

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Authors: Ahmed El-Banbi, Ahmed El-Maraghi

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PVT properties are needed as input data in all reservoir, production, and surface facilities engineering calculations. In the absence of PVT reports on valid reservoir fluid samples, engineers rely on PVT correlations to generate the required PVT data. The accuracy of PVT correlations varies, and no correlation group has been found to provide accurate results for all oil types. The effect of inaccurate PVT data can be significant in engineering calculations and is well documented in the literature. Bubble point pressure can sometimes be obtained from external sources. In this paper, we show how to utilize the known bubble point pressure to improve the accuracy of calculated PVT properties from correlations. We conducted a systematic study using around 250 reservoir oil samples to quantify the effect of pre-knowledge of bubble point pressure. The samples spanned a wide range of oils, from very volatile oils to black oils and all the way to low-GOR oils. A method for shifting both undersaturated and saturated sections of the PVT properties curves to the correct bubble point is explained. Seven PVT correlation families were used in this study. All PVT properties (e.g., solution gas-oil ratio, formation volume factor, density, viscosity, and compressibility) were calculated using the correct bubble point pressure and the correlation estimated bubble point pressure. Comparisons between the calculated PVT properties and actual laboratory-measured values were made. It was found that pre-knowledge of bubble point pressure and using the shifting technique presented in the paper improved the correlation-estimated values by 10% to more than 30%. The most improvement was seen in the solution gas-oil ratio and formation volume factor.

Keywords: PVT data, PVT properties, PVT correlations, bubble point pressure

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Authors: Yiu K. C. Jacky, Tang S. K. Eric, W. Y. Tsang, C. Y. Li, C. K. Leung

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Objectives : (1) To enhance the competence of nurses on using IPMOE for drug administration; (2) To ensure the transition on implementation of IPMOE in safer and smooth way hospital-wide. Methodology: (1) Well-structured Governance: To make provision for IPMOE implementation, multidisciplinary governance structure at Corporate and Local levels are well established. (2) Staff Engagement: A series of staff engagement events were conducted including Staff Forum, IPMOE Hospital Visit, Kick-off Ceremony and establishment of IPMOE Webpage for familiarizing the forthcoming implementation with frontline staff. (3) Well-organized training program: from Workshop to Workplace Two different IPMOE training programs were tailor-made which aimed at introducing the core features of administration module. Fifty-five identical training classes and six train-the-trainer workshops were organized at 2-3Q 2015. Lending Scheme on IPMOE hardware for hands-on practicing was launched and further extended the training from workshop to workplace. (4) Standard Guidelines and Workflow: the related workflow and guidelines are developed which facilitates users to acquire the competence towards IPMOE and fully familiarize with the standardized contingency plan. (5) Facilities and Equipment: The installations of IPMOE hardware were promptly arranged for rollout. Besides, IPMOE training venue was well-established for staff training. (6) Risk Management Strategy: UCH Medication Safety Forum is organized in December 2015 for sharing “Tricks & Tips” on IPMOE which further disseminate at webpage for arousal of medication safety. Hospital-wide annual audit on drug administration was planned to figure out the compliance and deliberate the rooms for improvement. Results: Through the comprehensive training plan, over 1,000 UCH nurses attended the training program with positive feedback. They agreed that their competence on using IPMOE was enhanced. By the end of November 2015, 28 wards (over 1,000 Inpatient-bed) involving departments of M&G, SUR, O&T and O&G have been successfully rolled out IPMOE in 5-month. A smooth and safe transition of implementation of IPMOE was achieved. Eventually, we all get prepared for embedding IPMOE into daily nursing and work altogether for medication safety at UCH.

Keywords: drug administration, inpatient medication order entry system, medication safety, nursing informatics

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Authors: Khlood F. Salman, Richard Zoucha, Hani Nawafleh

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Introduction: Jordan ranks the fourth highest breast cancer prevalence after Lebanon, Bahrain, and Kuwait. Considerable evidence showed that cultural, ethnic, and economic differences influence a woman’s practice to early detection and prevention of breast cancer. Objectives: To understand women’s health beliefs and values in relation to early detection of breast cancer; and to explore the impact of these beliefs on their decisions regarding reluctance or acceptance of early detection measures such as mammogram screening. Design: A qualitative focused ethnography was used to collect data for this study. Settings: The study was conducted in the second largest city surrounded by a large rural area in Ma’an- Jordan. Participants: A total of twenty seven women, with no history of breast cancer, between the ages of 18 and older, who had prior health experience with health providers, and were willing to share elements of personal health beliefs related to breast health within the larger cultural context. The participants were recruited using the snowball method and words of mouth. Data collection and analysis: A short questionnaire was designed to collect data related to socio demographic status (SDQ) from all participants. A Semi-structured interviews guide was used to elicit data through interviews with the informants. Nvivo10 a data manager was utilized to assist with data analysis. Leininger’s four phases of qualitative data analysis was used as a guide for the data analysis. The phases used to analyze the data included: 1) Collecting and documenting raw data, 2) Identifying of descriptors and categories according to the domains of inquiry and research questions. Emic and etic data is coded for similarities and differences, 3) Identifying patterns and contextual analysis, discover saturation of ideas and recurrent patterns, and 4) Identifying themes and theoretical formulations and recommendations. Findings: Three major themes were emerged within the cultural and religious context; 1. Fear, denial, embarrassment and lack of knowledge were common perceptions of Ma’anis’ women regarding breast health and screening mammography, 2. Health care professionals in Jordan were not quick to offer information and education about breast cancer and screening, and 3. Willingness to learn about breast health and cancer prevention. Conclusion: The study indicated the disparities between the infrastructure and resourcing in rural and urban areas of Jordan, knowledge deficit related to breast cancer, and lack of education about breast health may impact women’s decision to go for a mammogram screening. Cultural beliefs, fear, embarrassments as well as providers lack of focus on breast health were significant contributors against practicing breast health. Health providers and policy makers should provide resources for the establishment health education programs regarding breast cancer early detection and mammography screening. Nurses should play a major role in delivering health education about breast health in general and breast cancer in particular. A culturally appropriate health awareness messages can be used in creating educational programs which can be employed at the national levels.

Keywords: breast health, beliefs, cultural context, ethnography, mammogram screening

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Authors: G. Anjan Babu, G. Sumana, M. Rajasekhar

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Many inherited diseases and non-hereditary disorders are common in the development of renal cystic diseases. Polycystic kidney disease (PKD) is a disorder developed within the kidneys in which grouping of cysts filled with water like fluid. PKD is responsible for 5-10% of end-stage renal failure treated by dialysis or transplantation. New experimental models, application of molecular biology techniques have provided new insights into the pathogenesis of PKD. Researchers are showing keen interest for developing an automated system by applying computer aided techniques for the diagnosis of diseases. In this paper a multi-layered feed forward neural network with one hidden layer is constructed, trained and tested by applying back propagation learning rule for the diagnosis of PKD based on physical symptoms and test results of urinanalysis collected from the individual patients. The data collected from 50 patients are used to train and test the network. Among these samples, 75% of the data used for training and remaining 25% of the data are used for testing purpose. Furthermore, this trained network is used to implement for new samples. The output results in normality and abnormality of the patient.

Keywords: dialysis, hereditary, transplantation, polycystic, pathogenesis

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Authors: Vishwa Joshi

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The study of mood recognition in the field of music has gained a lot of momentum in the recent years with machine learning and data mining techniques and many audio features contributing considerably to analyze and identify the relation of mood plus music. In this paper we consider the same idea forward and come up with making an effort to build a system for automatic recognition of mood underlying the audio song’s clips by mining their audio features and have evaluated several data classification algorithms in order to learn, train and test the model describing the moods of these audio songs and developed an open source framework. Before classification, Preprocessing and Feature Extraction phase is necessary for removing noise and gathering features respectively.

Keywords: music, mood, features, classification

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Authors: Soha A. Bahanshal, Vaibhav Verdhan, Bayong Kim

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Graduation rates at six-year colleges are becoming a more essential indicator for incoming fresh students and for university rankings. Predicting student graduation is extremely beneficial to schools and has a huge potential for targeted intervention. It is important for educational institutions since it enables the development of strategic plans that will assist or improve students' performance in achieving their degrees on time (GOT). A first step and a helping hand in extracting useful information from these data and gaining insights into the prediction of students' progress and performance is offered by machine learning techniques. Data analysis and visualization techniques are applied to understand and interpret the data. The data used for the analysis contains students who have graduated in 6 years in the academic year 2017-2018 for science majors. This analysis can be used to predict the graduation of students in the next academic year. Different Predictive modelings such as logistic regression, decision trees, support vector machines, Random Forest, Naïve Bayes, and KNeighborsClassifier are applied to predict whether a student will graduate. These classifiers were evaluated with k folds of 5. The performance of these classifiers was compared based on accuracy measurement. The results indicated that Ensemble Classifier achieves better accuracy, about 91.12%. This GOT prediction model would hopefully be useful to university administration and academics in developing measures for assisting and boosting students' academic performance and ensuring they graduate on time.

Keywords: prediction, decision trees, machine learning, support vector machine, ensemble model, student graduation, GOT graduate on time

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Authors: Syed Basit Ali Shah Bukhari, Yan Qiang, Saad Abdul Rauf, Syed Saqlaina Bukhari

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Text Classification is the methodology to classify any given text into the respective category from a given set of categories. It is highly important and vital to use proper set of pre-processing , feature selection and classification techniques to achieve this purpose. In this paper we have used different ensemble techniques along with variance in feature selection parameters to see the change in overall accuracy of the result and also on some other individual class based features which include precision value of each individual category of the text. After subjecting our data through pre-processing and feature selection techniques , different individual classifiers were tested first and after that classifiers were combined to form ensembles to increase their accuracy. Later we also studied the impact of decreasing the classification categories on over all accuracy of data. Text classification is highly used in sentiment analysis on social media sites such as twitter for realizing people’s opinions about any cause or it is also used to analyze customer’s reviews about certain products or services. Opinion mining is a vital task in data mining and text categorization is a back-bone to opinion mining.

Keywords: Natural Language Processing, Ensemble Classifier, Bagging Classifier, AdaBoost

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Authors: Mohammad K. Abedin, Mohammad Shahjahan, Zeenat Sultana, Tawfique Jahan, Jesmin Akter

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To strengthen social and behavior change communication (SBCC) capacity of Ministry of Health and Family Welfare (MoHFW) of the Government of Bangladesh, BCCP/BKMI developed two eLearning courses providing opportunities for professional development of SBCC Program Managers who have no access to training or refreshers training. The two eLearning courses – Message and Material Development (MMD) and Monitoring and Evaluation (MandE) of SBCC programs – went online in September 2015, where all users could register their participation so results could be monitored. Methodology: To assess the uses of these courses a randomly selected sample was collected to run a pre and post-test analyses and a phone survey were conducted. Systematic random sampling was used to select a sample of 75 MandE and 25 MMD course participants from a sampling frame of 179 and 51 respectively. Results: As of September 2016, more than 179 learners have completed the MandE course, and 49 learners have completed the MMD course. The users of these courses are program managers, university faculty members, and students. Encouraging results were revealed from the analysis of pre and post-test scores and a phone survey three months after course completion. Test scores suggested a substantial increase in knowledge. The pre-test scores findings suggested that about 19% learners scored high on the MandE. The post-test scores finding indicated a high score (92%) of the sample across 4 modules of MandE. For MMD course in pre-test scoring, 30% of the learners scored high, and 100% scored high at the post-test. It was found that all the learners in the phone survey have discussed the courses. Most of the sharing occurred with colleagues and friends, usually through face to face (70%) interaction. The learners reported that they did recommend the two courses to concerned people. About 67% MandE and 76% MMD learners stated that the concepts that they had to learn during the course were put into practice in their work settings. The respondents for both MandE and MMD courses have provided a valuable set of suggestions that would further strengthen the courses. Conclusions: The study showed that the initiative offered ample opportunities to build capacity in various ways in which the eLearning courses were used. It also highlighted the importance of scaling up these efforts to further strengthen the outcomes.

Keywords: e-learning course, message & material development, monitoring & evaluation, social and behavior change communication

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Authors: Zahra Amirhosseini, Mahtab Nameni

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The aim of this study was to investigate the relationship between growth, beta, and Company's cash. We calculate cash as dependent variable and growth opportunity and beta as independent variables. This study was based on an analysis of panel data. Population of the study is the companies which listed in Tehran Stock exchange and a financial data of 215 companies during the period 2010 to 2015 have been selected as the sample through systematic sampling. The results of the first hypothesis showed there is a significant relationship between growth opportunities cash holdings. Also according to the analysis done in the second hypothesis, we determined that there is an inverse relation between company risk and cash holdings.

Keywords: growth, beta, liquidity, company

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Authors: Diana Codat

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Tweets' analysis is part of text mining. Each document is a written text. It's possible to apply the usual text search techniques, in particular by switching to the bag-of-words representation. But the tweets induce peculiarities. Some may enrich the analysis. Thus, their length is calibrated (at least as far as public messages are concerned), special characters make it possible to identify authors (@) and themes (#), the tweet and retweet mechanisms make it possible to follow the diffusion of the information. Conversely, other characteristics may disrupt the analyzes. Because space is limited, authors often use abbreviations, emoticons to express feelings, and they do not pay much attention to spelling. All this creates noise that can complicate the task. The tweets carry a lot of potentially interesting information. Their exploitation is one of the main axes of the analysis of the social networks. We show how to access Twitter-related messages. We will initiate a study of the properties of the tweets, and we will follow up on the exploitation of the content of the messages. We will work under R with the package 'twitteR'. The study of tweets is a strong focus of analysis of social networks because Twitter has become an important vector of communication. This example shows that it is easy to initiate an analysis from data extracted directly online. The data preparation phase is of great importance.

Keywords: data mining, language R, social networks, Twitter

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Authors: Fu-Pei Hsiao, Fung-Chung Tu, Chien-Kuo Chiu

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In this work, to develop a method for detailed assesses of post-earthquake seismic performance for RC buildings in Taiwan, experimental data for several column specimens with various failure modes (flexural failure, flexural-shear failure, and shear failure) are used to derive reduction factors of seismic capacity for specified damage states. According to the damage states of RC columns and their corresponding seismic reduction factors suggested by experimental data, this work applies the detailed seismic performance assessment method to identify the seismic capacity of earthquake-damaged RC buildings. Additionally, a post-earthquake emergent assessment procedure is proposed that can provide the data needed for decision about earthquake-damaged buildings in a region with high seismic hazard. Finally, three actual earthquake-damaged school buildings in Taiwan are used as a case study to demonstrate application of the proposed assessment method.

Keywords: seismic assessment, seismic reduction factor, residual seismic ratio, post-earthquake, reinforced concrete, building

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Authors: Basiliyos Tilahun Betru, Charles Awono Onana, Bernabe Batchakui

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Recommender systems have become increasingly popular in recent years, and are utilized in numerous areas. Nowadays many web services provide several information for users and recommender systems have been developed as critical element of these web applications to predict choice of preference and provide significant recommendations. With the help of the advantage of deep learning in modeling different types of data and due to the dynamic change of user preference, building a deep model can better understand users demand and further improve quality of recommendation. In this paper, deep neural network models for recommender system are evaluated. Most of deep neural network models in recommender system focus on the classical collaborative filtering user-item setting. Deep learning models demonstrated high level features of complex data can be learned instead of using metadata which can significantly improve accuracy of recommendation. Even though deep learning poses a great impact in various areas, applying the model to a recommender system have not been fully exploited and still a lot of improvements can be done both in collaborative and content-based approach while considering different contextual factors.

Keywords: big data, decision making, deep learning, recommender system

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Authors: Jung Lee

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The last decade has witnessed more people than ever before using social media and broadening their social circles. Social media users connect not only with their friends but also with professional acquaintances, primarily coworkers, and clients; personal and professional social circles are mixed within the same social media platform. Considering the positive aspect of social media in facilitating communication and mutual understanding between individuals, we infer that social media interactions with co-workers could indeed benefit one’s professional life. However, given privacy issues, sharing all personal details with one’s co-workers is not necessarily the best practice. Should one connect with coworkers via social media? Will social media connections with coworkers eventually benefit one’s long-term career? Will the benefit differ across cultures? To answer, this study examines how social media can contribute to organizational communication by tracing the foundation of user motivation based on social capital theory, leader-member exchange (LMX) theory and expectancy theory of motivation. Although social media was originally designed for personal communication, users have shown intentions to extend social media use for professional communication, especially when the proper incentive is expected. To articulate the user motivation and the mechanism of the incentive expectation scheme, this study applies those three theories and identify six antecedents and three moderators of social media use motivation including social network flaunt, shared interest, perceived social inclusion. It also hypothesizes that the moderating effects of those constructs would significantly differ based on the relationship hierarchy among the workers. To validate, this study conducted a survey of 329 active social media users with acceptable levels of job experiences. The analysis result confirms the specific roles of the three moderators in social media adoption for organizational communication. The present study contributes to the literature by developing a theoretical modeling of ambivalent employee perceptions about establishing social media connections with co-workers. This framework shows not only how both positive and negative expectations of social media connections with co-workers are formed based on expectancy theory of motivation, but also how such expectations lead to behavioral intentions using career success model. It also enhances understanding of how various relationships among employees can be influenced through social media use and such usage can potentially affect both performance and careers. Finally, it shows how cultural factors induced by social media use can influence relations among the coworkers.

Keywords: the social network, workplace, social capital, motivation

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Authors: Rusnardi Rahmat Putra, Junji Kiyono, Aiko Furukawa

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Several powerful earthquakes have struck Padang during recent years, one of the largest of which was an M 7.6 event that occurred on September 30, 2009 and caused more than 1000 casualties. Following the event, we conducted a 12-site microtremor array investigation to gain a representative determination of the soil condition of subsurface structures in Padang. From the dispersion curve of array observations, the central business district of Padang corresponds to relatively soft soil condition with Vs30 less than 400 m/s. because only one accelerometer existed, we simulated the 2009 Padang earthquake to obtain peak ground acceleration for all sites in Padang city. By considering the damage data of the 2009 Padang earthquake, we produced seismic risk vulnerability estimation of non-engineered houses for rock, medium and soft soil condition. We estimated the loss ratio based on the ground response, seismic hazard of Padang and the existing damaged to non-engineered structure houses due to Padang earthquake in 2009 data for several return periods of earthquake events.

Keywords: profile, Padang earthquake, microtremor array, seismic vulnerability

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Authors: Alina Murtishcheva

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The development of an effective system of administrative supervision is a prerequisite for the functioning of local self-government on the basis of the rule of law. Administrative supervision of local self-government is of particular importance in the EU countries due to the influence of integration processes. The central authorities act on the international level; however, subnational authorities also have to implement European legislation in order to strengthen integration. Therefore, the central authority, being the connecting link between supranational and subnational authorities, should bear responsibility, including financial responsibility, for possible mistakes of subnational authorities. Consequently, the state should have sufficient mechanisms of control over local and regional authorities in order to correct their mistakes. At the same time, the control mechanisms do not deny the autonomy of local self-government. The paper analyses models of administrative supervision of local self-government in Ukraine, Poland, Lithuania, Belgium, Great Britain, Italy, and France. The research methods used in this paper are theoretical methods of analysis of scientific literature, constitutions, legal acts, Congress of Local and Regional Authorities of the Council of Europe reports, and constitutional court decisions, as well as comparative and logical analysis. The legislative basis of administrative supervision was scrutinized, and the models of administrative supervision were classified, including a priori control and ex-post control or their combination. The advantages and disadvantages of these models of administrative supervision are analysed. Compliance with Article 8 of the European Charter of Local Self-Government is of great importance for countries achieving common goals and sharing common values. However, countries under study have problems and, in some cases, demonstrate non-compliance with provisions of Article 8. Such non-conformity as the endorsement of a mayor by the Flemish Government in Belgium, supervision with a view to expediency in Great Britain, and the tendency to overuse supervisory power in Poland are analysed. On the basis of research, the tendencies of administrative supervision of local authorities’ activities in selected European countries are described. Several recommendations for Ukraine as a country that had been granted the EU candidate status are formulated. Having emphasised its willingness to become a member of the European community, Ukraine should not only follow the best European practices but also avoid the mistakes of countries that have long-term experience in developing the local self-government institution. This project has received funding from the Research Council of Lithuania (LMTLT), agreement № P-PD-22-194

Keywords: administrative supervision, decentralisation, legality, local authorities, local self-government

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Authors: Ammar Alali, Mahmoud Abughaban, William Contreras Otalvora

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Optimizing the drilling process for cost and efficiency requires the optimization of the rate of penetration (ROP). ROP is the measurement of the speed at which the wellbore is created, in units of feet per hour. It is the primary indicator of measuring drilling efficiency. Maximization of the ROP can indicate fast and cost-efficient drilling operations; however, high ROPs may induce unintended events, which may lead to nonproductive time (NPT) and higher net costs. The proposed ROP optimization solution is a hybrid, data-driven system that aims to improve the drilling process, maximize the ROP, and minimize NPT. The system consists of two phases: (1) utilizing existing geological and drilling data to train the model prior, and (2) real-time adjustments of the controllable dynamic drilling parameters [weight on bit (WOB), rotary speed (RPM), and pump flow rate (GPM)] that direct influence on the ROP. During the first phase of the system, geological and historical drilling data are aggregated. After, the top-rated wells, as a function of high instance ROP, are distinguished. Those wells are filtered based on NPT incidents, and a cross-plot is generated for the controllable dynamic drilling parameters per ROP value. Subsequently, the parameter values (WOB, GPM, RPM) are calculated as a conditioned mean based on physical distance, following Inverse Distance Weighting (IDW) interpolation methodology. The first phase is concluded by producing a model of drilling best practices from the offset wells, prioritizing the optimum ROP value. This phase is performed before the commencing of drilling. Starting with the model produced in phase one, the second phase runs an automated drill-off test, delivering live adjustments in real-time. Those adjustments are made by directing the driller to deviate two of the controllable parameters (WOB and RPM) by a small percentage (0-5%), following the Constrained Random Search (CRS) methodology. These minor incremental variations will reveal new drilling conditions, not explored before through offset wells. The data is then consolidated into a heat-map, as a function of ROP. A more optimum ROP performance is identified through the heat-map and amended in the model. The validation process involved the selection of a planned well in an onshore oil field with hundreds of offset wells. The first phase model was built by utilizing the data points from the top-performing historical wells (20 wells). The model allows drillers to enhance decision-making by leveraging existing data and blending it with live data in real-time. An empirical relationship between controllable dynamic parameters and ROP was derived using Artificial Neural Networks (ANN). The adjustments resulted in improved ROP efficiency by over 20%, translating to at least 10% saving in drilling costs. The novelty of the proposed system lays is its ability to integrate historical data, calibrate based geological formations, and run real-time global optimization through CRS. Those factors position the system to work for any newly drilled well in a developing field event.

Keywords: drilling optimization, geological formations, machine learning, rate of penetration

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Authors: T. N. Goh, M. Hashmi, O. Hussain

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Temporomandibular joint (TMJ) dysfunction (TMD) is a condition that may affect patients via restricted mouth opening, significant pain during normal functioning, and/or reproducible joint noise. TMD includes myofascial pain, TMJ functional derangements (internal derangement, dislocation), and TMJ degenerative/inflammatory joint disease. Internal derangement (ID) is the most common cause of TMD-related clicking and locking. These patients are managed in a stepwise approach, from patient education (homecare advice and analgesia), splint therapy, physiotherapy, botulinum toxin treatment, to arthrocentesis. Arthrotomy is offered when the aforementioned treatment options fail to alleviate symptoms and improve quality of life. The aim of this prospective study was to review the outcomes of jaw joint open surgery in TMD patients. Patients who presented from 2015-2022 at the Oral and Maxillofacial Surgery Department in the Doncaster NHS Foundation Trust, UK, with a Wilkes classification of III -V were included. These patients underwent either i) discopexy with bone-anchoring suture (9); ii) intrapositional temporalis flap (ITF) with bone-anchoring suture (3); iii) eminoplasty and discopexy with suturing to the capsule (3); iii) discectomy + ITF with bone-anchoring suture (1); iv) discoplasty + bone-anchoring suture (1); v) ITF (1). Maximum incisal opening (MIO) was assessed pre-operatively and at each follow-up. Pain score, determined via the visual analogue scale (VAS, with 0 being no pain and 10 being the worst pain), was also recorded. A total of 18 eligible patients were identified with a mean age of 45 (range 22 - 79), of which 16 were female. The patients were scored by Wilkes Classification as III (14), IV (1), or V (4). Twelve patients had anterior disc displacement without reduction (66%) and six had degenerative/arthritic changes (33%) to the TMJ. The open joint procedure resulted in an increase in MIO and reduction in pain VAS and for the majority of patients, across all Wilkes Classifications. Pre-procedural MIO was 22.9 ± 7.4 mm and VAS was 7.8 ± 1.5. At three months post-procedure there was an increase in MIO to 34.4 ± 10.4 mm (p < 0.01) and a decrease in the VAS to 1.5 ± 2.9 (p < 0.01). Three patients were lost to follow-up prior to six months. Six were discharged at six month review and five patients were discharged at 12 months review as they were asymptomatic with good mouth opening. Four patients are still attending for annual botulinum toxin treatment. Two patients (Wilkes III and V) subsequently underwent TMJ replacement (11%). One of these patients (Wilkes III) had improvement initially to MIO of 40 mm, but subsequently relapsed to less than 20 mm due to lack of compliance with jaw rehabilitation device post-operatively. Clinical improvements in 89% of patients within the study group were found, with a return to near normal MIO range and reduced pain score. Intraoperatively, the operator found bone-anchoring suture used for discopexy/discoplasty more secure than the soft tissue anchoring suturing technique.

Keywords: bone anchoring suture, open temporomandibular joint surgery, temporomandibular joint, temporomandibular joint dysfunction

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Authors: Kumar Sambhav Pandey, Anamika Singh

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The continuous researches in the field of computer architecture basically aims at accelerating the computational speed and to gain enhanced performance. In this era, the superscalar, sub-scalar concept has not gained enough attention for improving the computation performance. In this paper, we have presented a sub-scalar approach to utilize the parallelism present with in the data while processing. The main idea is to split the data into individual smaller entities and these entities are processed with a defined known set of instructions. This sub-scalar approach to the MIPS architecture can bring out significant improvement in the computational speedup. MIPS-I is the basic design taken in consideration for the development of sub-scalar MIPS64 for increasing the instruction level parallelism (ILP) and resource utilization.

Keywords: dataword, MIPS, processor, sub-scalar

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Authors: Shelley Harrington

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As a result of increasingly dynamic business environments, the creation and fostering of dynamic capabilities, [those capabilities that enable sustained competitive success despite of dynamism through the awareness and reconfiguration of internal and external competencies], supported by organisational learning [a dynamic capability] has gained increased and prevalent momentum in the research arena. Presenting findings funded by the Economic Social Research Council, this paper investigates the extent to which Senior Management Team (SMT) personality (at the trait and facet level) is associated with the creation of dynamic managerial capabilities at the team level, and effective organisational learning/knowledge sharing within the firm. In doing so, this research highlights the importance of micro-foundations in organisational psychology and specifically dynamic capabilities, a field which to date has largely ignored the importance of psychology in understanding these important and necessary capabilities. Using a direct measure of personality (NEO PI-3) at the trait and facet level across 32 high technology and finance firms in the UK, their CEOs (N=32) and their complete SMTs [N=212], a new measure of dynamic managerial capabilities at the team level was created and statistically validated for use within the work. A quantitative methodology was employed with regression and gap analysis being used to show the empirical foundations of personality being positioned as a micro-foundation of dynamic capabilities. The results of this study found that personality homogeneity within the SMT was required to strengthen the dynamic managerial capabilities of sensing, seizing and transforming, something which was required to reflect strong organisational learning at middle management level [N=533]. In particular, it was found that the greater the difference [t-score gaps] between the personality profiles of a Chief Executive Officer (CEO) and their complete, collective SMT, the lower the resulting self-reported nature of dynamic managerial capabilities. For example; the larger the difference between a CEOs level of dutifulness, a facet contributing to the definition of conscientiousness, and their SMT’s level of dutifulness, the lower the reported level of transforming, a capability fundamental to strategic change in a dynamic business environment. This in turn directly questions recent trends, particularly in upper echelons research highlighting the need for heterogeneity within teams. In doing so, it successfully positions personality as a micro-foundation of dynamic capabilities, thus contributing to recent discussions from within the strategic management field calling for the need to empirically explore dynamic capabilities at such a level.

Keywords: dynamic managerial capabilities, senior management teams, personality, dynamism

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Authors: Dipti Govil, Nidhi Khosla

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Couple-level reports of contraception are important as wives and husbands may give different reports about contraceptive use. Using matched couple-data (N=62910), from India's NFHS–IV (2015-16), this paper examines concordance in spousal reports of current contraceptive use and its differentials. Reporting of contraceptive use was higher among wives (59%) than husbands (25%). Concordance was low; 16.5% of couples reported the use of the same method, while 21% reported the use of any method. There existed a huge denial from husbands on the use of female sterilization. Reconstruction of contraceptive use among men increased concordance by 10%. Multivariate analysis shows that concordance was low in urban and Southern India, among younger women and women with lower wealth-index. Men's control over household decision-making and negative attitudes towards contraception were associated with a lower concordance. Findings highlight the importance of using couple-level data to estimate contraceptive prevalence, the role of education programs to inculcate positive attitudes towards contraception, fostering gender equality, and involving men into family planning efforts. The results also raise the issue of data quality as the questions were asked differently from men and women, which might have contributed to wide discordance.

Keywords: concordance, contraceptive use, couple, female sterilisation, India

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Authors: Mohammad A. Al-Madi, Nagham A. Al-Madi, Fanan A. Al-Madi

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The current concept of the technology of cloud computing libraries has been increasing where users can store their data in a virtual space and can be retrieved from anywhere whilst using the network. By using cloud computing technology, industries and individuals save money, time, and space. Moreover, data and information about libraries can be placed in the cloud. This paper discusses the meaning of cloud computing along with its types. Further, the focus has been given to the application of cloud computing in modern libraries. Additionally, the advantages of cloud computing and the areas in which cloud computing be applied with current usage are discussed. Finally, the present situation of the Jordanian libraries is considered and discussed in further detail.

Keywords: cloud computing, community cloud, hybrid cloud, private cloud, public cloud

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Authors: Cagri Baris Kasap

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In this study, how interface designers can be viewed as producers of culture in the current era will be interrogated from a critical theory perspective. Walter Benjamin was a German Jewish literary critical theorist who, during 1930s, was engaged in opposing and criticizing the Nazi use of art and media. ‘The Author as Producer’ is an essay that Benjamin has read at the Communist Institute for the Study of Fascism in Paris. In this article, Benjamin relates directly to the dialectics between base and superstructure and argues that authors, normally placed within the superstructure should consider how writing and publishing is production and directly related to the base. Through it, he discusses what it could mean to see author as producer of his own text, as a producer of writing, understood as an ideological construct that rests on the apparatus of production and distribution. So Benjamin concludes that the author must write in ways that relate to the conditions of production, he must do so in order to prepare his readers to become writers and even make this possible for them by engineering an ‘improved apparatus’ and must work toward turning consumers to producers and collaborators. In today’s world, it has become a leading business model within Web 2.0 services of multinational Internet technologies and culture industries like Amazon, Apple and Google, to transform readers, spectators, consumers or users into collaborators and co-producers through platforms such as Facebook, YouTube and Amazon’s CreateSpace Kindle Direct Publishing print-on-demand, e-book and publishing platforms. However, the way this transformation happens is tightly controlled and monitored by combinations of software and hardware. In these global-market monopolies, it has become increasingly difficult to get insight into how one’s writing and collaboration is used, captured, and capitalized as a user of Facebook or Google. In the lens of this study, it could be argued that this criticism could very well be considered by digital producers or even by the mass of collaborators in contemporary social networking software. How do software and design incorporate users and their collaboration? Are they truly empowered, are they put in a position where they are able to understand the apparatus and how their collaboration is part of it? Or has the apparatus become a means against the producers? Thus, when using corporate systems like Google and Facebook, iPhone and Kindle without any control over the means of production, which is closed off by opaque interfaces and licenses that limit our rights of use and ownership, we are already the collaborators that Benjamin calls for. For example, the iPhone and the Kindle combine a specific use of technology to distribute the relations between the ‘authors’ and the ‘prodUsers’ in ways that secure their monopolistic business models by limiting the potential of the technology.

Keywords: interface designer, cultural producer, Walter Benjamin, materialist aesthetics, dialectical thinking

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Authors: Farhad Imanshoar

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The regime or equilibrium geometry of alluvial rivers remains a topic of fundamental scientific and engineering interest. There are several approaches to analyze the problem, namely: empirical formulas, semi-theoretical methods and rational (extreme) procedures. However, none of them is widely accepted at present, due to lack of knowledge of some physical processes associated with channel formation and the simplification hypotheses imposed in order to reduce the high quantity of involved variables. The study presented in this paper shows a new approach to estimate stable width and depth of sand-bed rivers by using developed stream power equation (DSPE). At first, a new procedure based on theoretical analysis and by considering DSPE and ultimate sediment concentration were developed. Then, experimental data for regime condition in sand-bed rivers (flow depth, flow width, sediment feed rate for several cases) were gathered. Finally, the results of this research (regime equations) are compared with the field data and other regime equations. A good agreement was observed between the field data and the values resulted from developed regime equation.

Keywords: regime equations, developed stream power equation, sand-bed rivers, semi-theoretical methods

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Authors: Mira Trebar

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Logistics processes of perishable food in the supply chain include the distribution activities and the real time temperature monitoring to fulfil the cold chain requirements. The paper presents the use of RFID (Radio Frequency Identification) technology as an identification tool of receiving and shipping activities in the cold store. At the same time, the use of RFID data loggers with temperature sensors is presented to observe and store the temperatures for the purpose of analyzing the processes and having the history data available for traceability purposes and efficient recall management.

Keywords: logistics, warehouse, RFID device, cold chain

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Authors: Marina Shakleina, Konstantin Shaklein, Stanislav Yakiro

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The digitalization of modern human life over the last decade has facilitated the acquisition, storage, and processing of data, which are used to detect changes in consumer preferences and to improve the internal efficiency of the production process. This emerging trend has attracted academic interest in the use of big data in research. The study focuses on modeling the social comfort of the Russian population for the period 2010-2021 using big data. Big data provides enormous opportunities for understanding human interactions at the scale of society with plenty of space and time dynamics. One of the most popular big data sources is Google Trends. The methodology for assessing social comfort using big data involves several steps: 1. 574 words were selected based on the Harvard IV-4 Dictionary adjusted to fit the reality of everyday Russian life. The set of keywords was further cleansed by excluding queries consisting of verbs and words with several lexical meanings. 2. Search queries were processed to ensure comparability of results: the transformation of data to a 10-point scale, elimination of popularity peaks, detrending, and deseasoning. The proposed methodology for keyword search and Google Trends processing was implemented in the form of a script in the Python programming language. 3. Block and summary integral indicators of social comfort were constructed using the first modified principal component resulting in weighting coefficients values of block components. According to the study, social comfort is described by 12 blocks: ‘health’, ‘education’, ‘social support’, ‘financial situation’, ‘employment’, ‘housing’, ‘ethical norms’, ‘security’, ‘political stability’, ‘leisure’, ‘environment’, ‘infrastructure’. According to the model, the summary integral indicator increased by 54% and was 4.631 points; the average annual rate was 3.6%, which is higher than the rate of economic growth by 2.7 p.p. The value of the indicator describing social comfort in Russia is determined by 26% by ‘social support’, 24% by ‘education’, 12% by ‘infrastructure’, 10% by ‘leisure’, and the remaining 28% by others. Among 25% of the most popular searches, 85% are of negative nature and are mainly related to the blocks ‘security’, ‘political stability’, ‘health’, for example, ‘crime rate’, ‘vulnerability’. Among the 25% most unpopular queries, 99% of the queries were positive and mostly related to the blocks ‘ethical norms’, ‘education’, ‘employment’, for example, ‘social package’, ‘recycling’. In conclusion, the introduction of the latent category ‘social comfort’ into the scientific vocabulary deepens the theory of the quality of life of the population in terms of the study of the involvement of an individual in the society and expanding the subjective aspect of the measurements of various indicators. Integral assessment of social comfort demonstrates the overall picture of the development of the phenomenon over time and space and quantitatively evaluates ongoing socio-economic policy. The application of big data in the assessment of latent categories gives stable results, which opens up possibilities for their practical implementation.

Keywords: big data, Google trends, integral indicator, social comfort

Procedia PDF Downloads 198