Search results for: cloud data privacy and integrity

Authors: Mazharuddin Syed Ahmed

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This research presents a framework used to develop The Ara Polytechnic College of Architecture Studies building “Kahukura” which is Green Building certified. This framework integrates the development of a smart building digital twin by utilizing Building Information Modelling (BIM) and its BIM maturity levels, including Levels of Development (LOD), eight dimensions of BIM, Heritage-BIM (H-BIM) and Facility Management BIM (FM BIM). The research also outlines a structured approach to building performance analysis and integration with the circular economy, encapsulated within a five-level digital twin framework. Starting with Level 1, the Descriptive Twin provides a live, editable visual replica of the built asset, allowing for specific data inclusion and extraction. Advancing to Level 2, the Informative Twin integrates operational and sensory data, enhancing data verification and system integration. At Level 3, the Predictive Twin utilizes operational data to generate insights and proactive management suggestions. Progressing to Level 4, the Comprehensive Twin simulates future scenarios, enabling robust “what-if” analyses. Finally, Level 5, the Autonomous Twin, represents the pinnacle of digital twin evolution, capable of learning and autonomously acting on behalf of users.

Keywords: building information modelling, circular economy integration, digital twin, predictive analytics

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Authors: Asif Ali, Daud Salim Faruquie

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With the advancement of knowledge about the utility and impact of sustainability, its feasibility has been explored into different walks of life. Scientists, however; have established their knowledge in four areas viz environmental, economic, social and cultural, popularly termed as four pillars of sustainability. Aspects of environmental and economic sustainability have been rigorously researched and practiced and huge volume of strong evidence of effectiveness has been founded for these two sub-areas. For the social and cultural aspects of sustainability, dependable evidence of effectiveness is still to be instituted as the researchers and practitioners are developing and experimenting methods across the globe. Therefore, the present research aimed to identify globally used practices of social and cultural sustainability and through evidence synthesis assess their outcomes to determine the effectiveness of those practices. A PICO format steered the methodology which included all populations, popular sustainability practices including walkability/cycle tracks, social/recreational spaces, privacy, health & human services and barrier free built environment, comparators included ‘Before’ and ‘After’, ‘With’ and ‘Without’, ‘More’ and ‘Less’ and outcomes included Social well-being, cultural co-existence, quality of life, ethics and morality, social capital, sense of place, education, health, recreation and leisure, and holistic development. Search of literature included major electronic databases, search websites, organizational resources, directory of open access journals and subscribed journals. Grey literature, however, was not included. Inclusion criteria filtered studies on the basis of research designs such as total randomization, quasi-randomization, cluster randomization, observational or single studies and certain types of analysis. Studies with combined outcomes were considered but studies focusing only on environmental and/or economic outcomes were rejected. Data extraction, critical appraisal and evidence synthesis was carried out using customized tabulation, reference manager and CASP tool. Partial meta-analysis was carried out and calculation of pooled effects and forest plotting were done. As many as 13 studies finally included for final synthesis explained the impact of targeted practices on health, behavioural and social dimensions. Objectivity in the measurement of health outcomes facilitated quantitative synthesis of studies which highlighted the impact of sustainability methods on physical activity, Body Mass Index, perinatal outcomes and child health. Studies synthesized qualitatively (and also quantitatively) showed outcomes such as routines, family relations, citizenship, trust in relationships, social inclusion, neighbourhood social capital, wellbeing, habitability and family’s social processes. The synthesized evidence indicates slight effectiveness and efficacy of social and cultural sustainability on the targeted outcomes. Further synthesis revealed that such results of this study are due weak research designs and disintegrated implementations. If architects and other practitioners deliver their interventions in collaboration with research bodies and policy makers, a stronger evidence-base in this area could be generated.

Keywords: built environment, cultural sustainability, social sustainability, sustainable architecture

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Authors: Youngseok Kim, Chul Park, Jonghwa Yi, Sangsik Choi

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The 2-MHz Side Scan SONAR (SSS) attached to the boat for inspection of underwater structures is affected by shaking. It is difficult to determine the exact scale of damage of structure. In this study, a motion sensor is attached to the inside of the 2-MHz SSS to get roll, pitch, and yaw direction data, and developed the image stabilization tool to correct the sonar image. We checked that reliable data can be obtained with an average error rate of 1.99% between the measured value and the actual distance through experiment. It is possible to get the accurate sonar data to inspect damage in underwater structure.

Keywords: image stabilization, motion sensor, safety inspection, sonar image, underwater structure

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Authors: Reza Mehrafarin, Nafiseh Mirshekari, Mahyar Mehrafarin

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In 25 km southeast of Zabul (center of Sistan, in the east of Iran), a large hill can be seen. This hill, which is located next to the bend of the Sistan river, is known as the Tappeh Shahrestan. The length of the Tappeh Shahrestan is 1350 meters, its width is 360 meters, and its height is 20 meters, which in total reaches to 48 hectares. The capital of Sistan province was Ram Shahrestan in the Sassanid period, according to Iranian historical texts and Sassanid Pahlavi traditions. The city was abandoned because the nearby river dried up. Then another capital was built in Sistan called Zarang. But due to the long passage of time since the destruction of the city, its real location was forgotten and and some archaeologists have suggested different areas as the main location of the Ram Shahrestan. In 2018, the first archaeological field activities took place on and around the hillin order to answer this question: was Tappe Shahristan the same as Ram Shahristan, the capital of Sistan, during the Sassanid period? In order to answer this question, archaeological field activities were carried out on and around the hill. The field activities of the first season included the followings: 1- Preparation of hill topography and plan metric 3-Archaeogeophysics studies 3-Methodical study of archeology 4-Determining the range of the hill by soundings5-Documentation of the hill 6-Classification, typology, and comparison of pottery typology. The results of archaeological field activities in the first phase of Tappeh Shahrestan showed that this ancient site was the same city of Ram Shahrestan, the capital of Sistan, during the Sassanid period. The beginning of settlement in this city was the third century BC and the time of leaving was the end of the third century AD. The most important factors in the creation of the city was the abundant water of the Sistan River and its convenient location, and the most important reason for the abandonment of the city was the Sistan River, whose water completely dried up.

Keywords: archaeological surveys, archaeological soundings, ram shahrestan, sistan, tappeh shahrestan

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Authors: K. Parandhama Gowd

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The aim of this research paper is to conceptualize, discuss, analyze and propose alternate design methodologies for futuristic Black Box for flight safety. The proposal also includes global networking concepts for real time surveillance and monitoring of flight performance parameters including GPS parameters. It is expected that this proposal will serve as a failsafe real time diagnostic tool for accident investigation and location of debris in real time. In this paper, an attempt is made to improve the existing methods of flight data recording techniques and improve upon design considerations for futuristic FDR to overcome the trauma of not able to locate the block box. Since modern day communications and information technologies with large bandwidth are available coupled with faster computer processing techniques, the attempt made in this paper to develop a failsafe recording technique is feasible. Further data fusion/data warehousing technologies are available for exploitation.

Keywords: flight data recorder (FDR), black box, diagnostic tool, global networking, cockpit voice and data recorder (CVDR), air traffic control (ATC), air traffic, telemetry, tracking and control centers ATTTCC)

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Authors: Mouataz Zreika, Maria Estela Varua

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Stock investment decisions are often made based on current events of the global economy and the analysis of historical data. Conversely, visual representation could assist investors’ gain deeper understanding and better insight on stock market trends more efficiently. The trend analysis is based on long-term data collection. The study adopts a hybrid method that combines the Clustering algorithm and Force-directed algorithm to overcome the scalability problem when visualizing large data. This method exemplifies the potential relationships between each stock, as well as determining the degree of strength and connectivity, which will provide investors another understanding of the stock relationship for reference. Information derived from visualization will also help them make an informed decision. The results of the experiments show that the proposed method is able to produced visualized data aesthetically by providing clearer views for connectivity and edge weights.

Keywords: clustering, force-directed, graph drawing, stock investment analysis

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Authors: Manas Kotepui, Chatree Ratcha, Kwuntida Uthaisar

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Malaria infection is still to be considered a major public health problem in Thailand. This study, a retrospective data of patients in Surat Thani Province, Southern Thailand during 2012-2015 was retrieved and analyzed. These data include demographic data, clinical characteristics and laboratory diagnosis. Statistical analyses were performed to demonstrate the frequency, proportion, data tendency, and group comparisons. Total of 395 malaria patients were found. Most of patients were male (253 cases, 64.1%). Most of patients (262 cases, 66.3%) were admitted at 6 am-11.59 am of the day. Three hundred and fifty-five patients (97.5%) were positive with P. falciparum. Hemoglobin, hematocrit, and MCHC between P. falciparum and P. vivax were significant different (P value<0.05).During 2012-2015, prevalence of malaria was highest in 2013. Neutrophils, lymphocytes, and monocytes were significantly changed among patients with fever ≤ 3 days compared with patients with fever >3 days. This information will guide to understanding pathogenesis and characteristic of malaria infection in Sothern Thailand.

Keywords: prevalence, malaria, Surat Thani, Thailand

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Authors: Jinyan Li, Simon Fong, Raymond Wong, Mohammed Sabah, Fiaidhi Jinan

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Clinical data analysis and forecasting have make great contributions to disease control, prevention and detection. However, such data usually suffer from highly unbalanced samples in class distributions. In this paper, we target at the binary imbalanced dataset, where the positive samples take up only the minority. We investigate two different meta-heuristic algorithms, particle swarm optimization and bat-inspired algorithm, and combine both of them with the synthetic minority over-sampling technique (SMOTE) for processing the datasets. One approach is to process the full dataset as a whole. The other is to split up the dataset and adaptively process it one segment at a time. The experimental results reveal that while the performance improvements obtained by the former methods are not scalable to larger data scales, the later one, which we call Adaptive Swarm Balancing Algorithms, leads to significant efficiency and effectiveness improvements on large datasets. We also find it more consistent with the practice of the typical large imbalanced medical datasets. We further use the meta-heuristic algorithms to optimize two key parameters of SMOTE. Leading to more credible performances of the classifier, and shortening the running time compared with the brute-force method.

Keywords: Imbalanced dataset, meta-heuristic algorithm, SMOTE, big data

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Authors: Shivi Agarwal, Trilok Mathur

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This paper proposes the method to measure the total factor productivity (TFP) change by credibility theory for fuzzy input and output variables. Total factor productivity change has been widely studied with crisp input and output variables, however, in some cases, input and output data of decision-making units (DMUs) can be measured with uncertainty. These data can be represented as linguistic variable characterized by fuzzy numbers. Malmquist productivity index (MPI) is widely used to estimate the TFP change by calculating the total factor productivity of a DMU for different time periods using data envelopment analysis (DEA). The fuzzy DEA (FDEA) model is solved using the credibility theory. The results of FDEA is used to measure the TFP change for fuzzy input and output variables. Finally, numerical examples are presented to illustrate the proposed method to measure the TFP change input and output variables. The suggested methodology can be utilized for performance evaluation of DMUs and help to assess the level of integration. The methodology can also apply to rank the DMUs and can find out the DMUs that are lagging behind and make recommendations as to how they can improve their performance to bring them at par with other DMUs.

Keywords: chance-constrained programming, credibility theory, data envelopment analysis, fuzzy data, Malmquist productivity index

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Authors: P. Wlodarczak, J. Soar, M. Ally

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The dramatic rise in the use of Social Media (SM) platforms such as Facebook and Twitter provide access to an unprecedented amount of user data. Users may post reviews on products and services they bought, write about their interests, share ideas or give their opinions and views on political issues. There is a growing interest in the analysis of SM data from organisations for detecting new trends, obtaining user opinions on their products and services or finding out about their online reputations. A recent research trend in SM analysis is making predictions based on sentiment analysis of SM. Often indicators of historic SM data are represented as time series and correlated with a variety of real world phenomena like the outcome of elections, the development of financial indicators, box office revenue and disease outbreaks. This paper examines the current state of research in the area of SM mining and predictive analysis and gives an overview of the analysis methods using opinion mining and machine learning techniques.

Keywords: social media, text mining, knowledge discovery, predictive analysis, machine learning

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Authors: Chien-Hung Liu, Yu-Fen Chen

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This study used triangular laser probe and three-axial direction mobile platform for surface measurement, programmed it and applied it to real-time analytic statistics of different measured data. This structure was used to design a system integration program: using triangular laser probe for scattering or reflection non-contact measurement, transferring the captured signals to the computer through RS-232, and using RS-485 to control the three-axis platform for a wide range of measurement. The data captured by the laser probe are formed into a 3D surface. This study constructed an optical measurement application program in the concept of visual programming language. First, the signals are transmitted to the computer through RS-232/RS-485, and then the signals are stored and recorded in graphic interface timely. This programming concept analyzes various messages, and makes proper presentation graphs and data processing to provide the users with friendly graphic interfaces and data processing state monitoring, and identifies whether the present data are normal in graphic concept. The major functions of the measurement system developed by this study are thickness measurement, SPC, surface smoothness analysis, and analytical calculation of trend line. A result report can be made and printed promptly. This study measured different heights and surfaces successfully, performed on-line data analysis and processing effectively, and developed a man-machine interface for users to operate.

Keywords: laser probe, non-contact measurement, triangulation measurement principle, statistical process control, labVIEW

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Authors: Archana Singh, Jyoti Agarwal, Ajay Rana

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Data Mining is an efficient technology to discover patterns in large databases. Association Rule Mining techniques are used to find the correlation between the various item sets in a database, and this co-relation between various item sets are used in decision making and pattern analysis. In recent years, the problem of finding association rules from large datasets has been proposed by many researchers. Various research papers on association rule mining (ARM) are studied and analyzed first to understand the existing algorithms. Apriori algorithm is the basic ARM algorithm, but it requires so many database scans. In DIC algorithm, less amount of database scan is needed but complex data structure lattice is used. The main focus of this paper is to propose a new optimized algorithm (Friendly Algorithm) and compare its performance with the existing algorithms A data set is used to find out frequent itemsets and association rules with the help of existing and proposed (Friendly Algorithm) and it has been observed that the proposed algorithm also finds all the frequent itemsets and essential association rules from databases as compared to existing algorithms in less amount of database scan. In the proposed algorithm, an optimized data structure is used i.e. Graph and Adjacency Matrix.

Keywords: association rules, data mining, dynamic item set counting, FP-growth, friendly algorithm, graph

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Authors: Mark Salisbury

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The arrival of artificially intelligent avatars and the automation they bring is worrying many of us, not only for our livelihood but for the jobs that may be lost to our kids. We worry about what our place will be as human beings in this new economy where much of it will be conducted online in the metaverse – in a network of 3D virtual worlds – working with intelligent machines. The Future of Leadership was written to address these fears and show what our place will be – the right place – in this new economy of AI avatars, automation, and 3D virtual worlds. But to be successful in this new economy, our job will be to bring wisdom to our workplace and the marketplace. And we will use AI avatars and 3D virtual worlds to do it. However, this book is about more than AI and the avatars that we will work with in the metaverse. It’s about building Organizational intelligence (OI) -- the capability of an organization to comprehend and create knowledge relevant to its purpose; in other words, it is the intellectual capacity of the entire organization. To increase organizational intelligence requires a new kind of knowledge worker, a wisdom worker, that requires a new kind of leadership. This book begins your story for how to become a leader of wisdom workers and be successful in the emerging wisdom economy. After this presentation, conference participants will be able to do the following: Recognize the characteristics of the new generation of wisdom workers and how they differ from their predecessors. Recognize that new leadership methods and techniques are needed to lead this new generation of wisdom workers. Apply personal and professional values – personal integrity, belief in something larger than yourself, and keeping the best interest of others in mind – to improve your work performance and lead others. Exhibit an attitude of confidence, courage, and reciprocity of sharing knowledge to increase your productivity and influence others. Leverage artificial intelligence to accelerate your ability to learn, augment your decision-making, and influence others.Utilize new technologies to communicate with human colleagues and intelligent machines to develop better solutions more quickly.

Keywords: metaverse, generative artificial intelligence, automation, leadership, organizational intelligence, wisdom worker

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Authors: Xin-Yan Ji

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The historical failures data of the spacecraft is very useful to improve the spacecraft design and the test philosophies and reduce the spacecraft flight risk. A study of spacecraft failures data was performed, which is the most comprehensive statistics of spacecrafts in China. 2593 on-orbit failures data and 1298 ground data that occurred on 150 spacecraft launched from 2000 to 2016 were identified and collected, which covered the navigation satellites, communication satellites, remote sensing deep space exploration manned spaceflight platforms. In this paper, the failures were analyzed to compare different spacecraft subsystem and estimate their impact on the mission, then the development of spacecraft in China was evaluated from design, software, workmanship, management, parts, and materials. Finally, the lessons learned from the past years show that electrical and mechanical failures are responsible for the largest parts, and the key solution to reduce in-orbit failures is improving design technology, enough redundancy, adequate space environment protection measures, and adequate ground testing.

Keywords: spacecraft anomalies, anomalies mechanism, failure cause, spacecraft testing

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Authors: Salim Yusif

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Fiber optic technology has revolutionized telecommunications and data transmission, providing unmatched speed, bandwidth, and reliability. This paper presents the latest advancements in fiber optic technology, focusing on innovations in fiber materials, transmission techniques, and network architectures that enhance the performance of high-speed data transmission systems. Key advancements include the development of ultra-low-loss optical fibers, multi-core fibers, advanced modulation formats, and the integration of fiber optics into next-generation network architectures such as Software-Defined Networking (SDN) and Network Function Virtualization (NFV). Additionally, recent developments in fiber optic sensors are discussed, extending the utility of optical fibers beyond data transmission. Through comprehensive analysis and experimental validation, this research offers valuable insights into the future directions of fiber optic technology, highlighting its potential to drive innovation across various industries.

Keywords: fiber optics, high-speed data transmission, ultra-low-loss optical fibers, multi-core fibers, modulation formats, coherent detection, software-defined networking, network function virtualization, fiber optic sensors

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Authors: Iñaki Aliende, Tom Webb, Lorenzo Escot

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There is a concern about the decrease in football referees globally. A study in Spain has analyzed the factors affecting a referee's career over the past 30 years through a survey of 758 referees. Results showed the impact of factors such as threats, education, initial vocation, and dependents on a referee's career. To improve the situation, the federation needs to provide better information, support young referees, monitor referees, and raise public awareness of violence toward referees. The study also formed a comprehensive model for federations to enhance their officiating policies by means of data-driven techniques that can serve other federations to improve referees' careers.

Keywords: data science, football referees, sport management, sport careers, survival analysis

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Authors: O. A. Ajigini, E. N. Mwim

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Cybersecurity is the protection of computers, programs, networks, and data from attack, damage, unauthorised, unintended access, change, or destruction. Organisations collect, process and store their confidential and sensitive information on computers and transmit this data across networks to other computers. Moreover, the advent of internet technologies has led to various cyberattacks resulting in dangerous consequences for organisations. Therefore, with the increase in the volume and sophistication of cyberattacks, there is a need to develop models and make recommendations for the management of cybersecurity threats in organisations. This paper reports on various threats that cause malicious damage to organisations in cyberspace and provides measures on how these threats can be eliminated or reduced. The paper explores various aspects of protection measures against cybersecurity threats such as handling of sensitive data, network security, protection of information assets and cybersecurity awareness. The paper posits a model and recommendations on how to manage cybersecurity threats in organisations effectively. The model and the recommendations can then be utilised by organisations to manage the threats affecting their cyberspace. The paper provides valuable information to assist organisations in managing their cybersecurity threats and hence protect their computers, programs, networks and data in cyberspace. The paper aims to assist organisations to protect their information assets and data from cyberthreats as part of the contributions toward community engagement.

Keywords: confidential information, cyberattacks, cybersecurity, cyberspace, sensitive information

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Authors: Philippe Larvet

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This paper presents the concept of an object-based programming language where tests (if... then... else) and control structures (while, repeat, for...) disappear and are replaced by conditions on data. According to the object paradigm, by using this concept, data are still embedded inside objects, as variable-value couples, but object methods are expressed into the form of logical propositions (‘conditions on data’ or COD).For instance : variable1 = value1 AND variable2 > value2 => variable3 = value3. Implementing this approach, a central inference engine turns and examines objects one after another, collecting all CODs of each object. CODs are considered as rules in a rule-based system: the left part of each proposition (left side of the ‘=>‘ sign) is the premise and the right part is the conclusion. So, premises are evaluated and conclusions are fired. Conclusions modify the variable-value couples of the object and the engine goes to examine the next object. The paper develops the principles of writing CODs instead of complex algorithms. Through samples, the paper also presents several hints for implementing a simple mechanism able to process this ‘COD language’. The proposed approach can be used within the context of simulation, process control, industrial systems validation, etc. By writing simple and rigorous conditions on data, instead of using classical and long-to-learn languages, engineers and specialists can easily simulate and validate the functioning of complex systems.

Keywords: conditions on data, logical proposition, programming without code, object-oriented programming, system simulation, system validation

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Authors: Stanley Fore, Sharon Chipeperekwa

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The start of the 2011 academic year in South Africa saw a number of Institutions of Higher Learning introducing online registration for their students. The efficiency and effectiveness of Information Systems are increasingly becoming a necessity and not an option for many organizations. An information system should be able to allow end users to access information easily and navigate with ease. The selected University of Technology (UoT) in this research is one of the largest public institution of higher learning in the Western Cape Province and boasts of an enrolment of more than 30000 students per academic year. An observation was made that, during registration students’ stand in long queues waiting to register or for assistance to register. The system tends to ‘freeze’ whilst students are registering and students are in most cases unfamiliar with the system interface. They constantly have to enquire what to do next when going through online registration process. A mixed method approach will be adopted which comprises of quantitative and qualitative approaches. The study uses constructs of the updated DeLone and McLean IS success model (2003) to analyse and explain the student’s perceptions of the online registration system. The research was undertaken to establish the student’s perceptions of the online registration system. This research seeks to identify and analyse the challenges and success factors of introducing an online registration system whilst highlighting the extent to which this system has been able to solve the numerous problems associated with the manual era. The study will assist management and those responsible for managing the current system to determine how well the system is working or not working to achieve user satisfaction. It will also assist them going forward on what to consider before, during and after implementation of an information system. Respondents will be informed of the objectives of the research, and their consent to participate will be sought. Ethical considerations that will be applied to this study include; informed consent and protection from harm, right to privacy and involvement of the research.

Keywords: online registration, information systems, University of Technology, end-users

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Authors: Aby Nesan Raj, Sumil K. Raj, Sumesh Jayan

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The objective of the study is to formulate a self-regulation model that shall enhance the usage of Intelligent Transportation Systems by understanding the theory of self-efficacy. The core logic of the self-regulation model shall monitor driver's behavior based on the situations related to the various sources of Self Efficacy like enactive mastery, vicarious experience, verbal persuasion and physiological arousal in addition to the vehicle data. For this study, four different vehicle data, speed, drowsiness, diagnostic data and surround camera views are considered. This data shall be given to the self-regulation model for evaluation. The oddness, which is the output of self-regulation model, shall feed to Intelligent Transportation Systems where appropriate actions are being taken. These actions include warning to the user as well as the input to the related transportation systems. It is also observed that the usage of vehicle as a sensor reduces the wastage of resource utilization or duplication. Altogether, this approach enhances the intelligence of the transportation systems especially in safety, productivity and environmental performance.

Keywords: emergency management, intelligent transportation system, self-efficacy, traffic management

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Authors: Nino Tsamalaidze

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Cold plasma is an ionized neutral gas with a temperature of 30-40 degrees, but the impact of HP includes not only gas, but also active molecules, charged particles, heat and UV radiation of low power The main goal of the technology we describe is to launch the natural function of skin regeneration and improve the metabolism inside, which leads to a huge effect of rejuvenation. In particular: eliminate fine mimic wrinkles; get rid of wrinkles around the mouth (purse-string wrinkles); reduce the overhang of the upper eyelid; eliminate bags under the eyes; provide a lifting effect on the oval of the face; reduce stretch marks; shrink pores; even out the skin, reduce the appearance of acne, scars; remove pigmentation. A clear indication of the major findings of the study is based on the current patients practice. The method is to use combination of cold plasma and liquid threats. The advantage of cold plasma is undoubtedly its efficiency, the result of its implementation can be compared with the result of a surgical facelift, despite the fact that the procedure is non-invasive and the risks are minimized. Another advantage is that the technique can be applied on the most sensitive skin of the face - these are the eyelids and the space around the eyes. Cold plasma is one of the few techniques that eliminates bags under the eyes and overhanging eyelids, while not violating the integrity of the tissues. In addition to rejuvenation and lifting effect, among the benefits of cold plasma is also getting rid of scars, kuperoze, stretch marks and other skin defects, plasma allows to get rid of acne, seborrhea, skin fungus and even heals ulcers. The cold plasma method makes it possible to achieve a result similar to blepharoplasty. Carried out on the skin of the eyelids, the procedure allows non-surgical correction of the eyelid line in 3-4 sessions. One of the undoubted advantages of this method is a short rehabilitation and rapid healing of the skin.

Keywords: wrinkles, telangiectasia, pigmentation, pore closing

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Authors: Chhabi Nigam, S. Ramakrishnan

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This paper brings out the analysis of the airborne Synthetic Aperture Radar (SAR) data to study the impact of Doppler centroid on Image quality and geocoding accuracy from the perspective of Stripmap mode of data acquisition. Although in Stripmap mode of data acquisition radar beam points at 90 degrees broad side (side looking), shift in the Doppler centroid is invariable due to platform motion. In-accurate estimation of Doppler centroid leads to poor image quality and image miss-registration. The effect of Doppler centroid is analyzed in this paper using multiple sets of data collected from airborne platform. Occurrences of ghost (ambiguous) targets and their power levels have been analyzed that impacts appropriate choice of PRF. Effect of aircraft attitudes (roll, pitch and yaw) on the Doppler centroid is also analyzed with the collected data sets. Various stages of the RDA (Range Doppler Algorithm) algorithm used for image formation in Stripmap mode, range compression, Doppler centroid estimation, azimuth compression, range cell migration correction are analyzed to find the performance limits and the dependence of the imaging geometry on the final image. The ability of Doppler centroid estimation to enhance the imaging accuracy for registration are also illustrated in this paper. The paper also tries to bring out the processing of low squint SAR data, the challenges and the performance limits imposed by the imaging geometry and the platform dynamics on the final image quality metrics. Finally, the effect on various terrain types, including land, water and bright scatters is also presented.

Keywords: ambiguous target, Doppler Centroid, image registration, Airborne SAR

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Authors: Tshaudi Motsima

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Class attendance is key at all levels of education. At tertiary level many students develop a tendency of not attending all classes without being aware of the repercussions of not attending all classes. It is important for all students to attend all classes as they can receive first-hand information and they can benefit more. The student who attends classes is likely to perform better academically than the student who does not. The aim of this paper is to assess the relationship between class attendance and academic performance of industrial engineering students. The data for this study were collected through the attendance register of students and the other data were accessed from the Integrated Tertiary Software and the Higher Education Data Analyzer Portal. Data analysis was conducted on a sample of 93 students. The results revealed that students with medium predicate scores (OR = 3.8; p = 0.027) and students with low predicate scores (OR = 21.4, p < 0.001) were significantly likely to attend less than 80% of the classes as compared to students with high predicate scores. Students with examination performance of less than 50% were likely to attend less than 80% of classes than students with examination performance of 50% and above, but the differences were not statistically significant (OR = 1.3; p = 0.750).

Keywords: class attendance, examination performance, final outcome, logistic regression

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Authors: Kristian Bautista, Ruben A. Idoy

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A bio-inspired metaheuristic algorithm inspired by the theory of collective animal behavior (CAB) was integrated to density-based clustering modeled as multimodal optimization problem. The algorithm was tested on synthetic, Iris, Glass, Pima and Thyroid data sets in order to measure its effectiveness relative to CDE-based Clustering algorithm. Upon preliminary testing, it was found out that one of the parameter settings used was ineffective in performing clustering when applied to the algorithm prompting the researcher to do an investigation. It was revealed that fine tuning distance δ3 that determines the extent to which a given data point will be clustered helped improve the quality of cluster output. Even though the modification of distance δ3 significantly improved the solution quality and cluster output of the algorithm, results suggest that there is no difference between the population mean of the solutions obtained using the original and modified parameter setting for all data sets. This implies that using either the original or modified parameter setting will not have any effect towards obtaining the best global and local animal positions. Results also suggest that CDE-based clustering algorithm is better than CAB-density clustering algorithm for all data sets. Nevertheless, CAB-density clustering algorithm is still a good clustering algorithm because it has correctly identified the number of classes of some data sets more frequently in a thirty trial run with a much smaller standard deviation, a potential in clustering high dimensional data sets. Thus, the researcher recommends further investigation in the post-processing stage of the algorithm.

Keywords: clustering, metaheuristics, collective animal behavior algorithm, density-based clustering, multimodal optimization

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Authors: G. B. Hong

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Liquid-Liquid Equilibrium (LLE) data are measured for the ternary mixtures of water + 1-butanol + butyl acetate and quaternary mixtures of water + 1-butanol + butyl acetate + glycerol at atmospheric pressure at 313.15 K. In addition, isothermal Vapor–Liquid–Liquid Equilibrium (VLLE) data are determined experimentally at 333.15 K. The region of heterogeneity is found to increase as the hydrophilic agent (glycerol) is introduced into the aqueous mixtures. The experimental data are correlated with the NRTL model. The predicted results from the solution model with the model parameters determined from the constituent binaries are also compared with the experimental values.

Keywords: LLE, VLLE, hydrophilic agent, NRTL

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Authors: Piotr J. Balwierz, Mikhail Pachkov, Phil Arnold, Andreas J. Gruber, Mihaela Zavolan, Erik van Nimwegen

Abstract:

Understanding the key players and interactions in the regulatory networks that control gene expression and chromatin state across different cell types and tissues in metazoans remains one of the central challenges in systems biology. Our laboratory has pioneered a number of methods for automatically inferring core gene regulatory networks directly from high-throughput data by modeling gene expression (RNA-seq) and chromatin state (ChIP-seq) measurements in terms of genome-wide computational predictions of regulatory sites for hundreds of transcription factors and micro-RNAs. These methods have now been completely automated in an integrated webserver called ISMARA that allows researchers to analyze their own data by simply uploading RNA-seq or ChIP-seq data sets and provides results in an integrated web interface as well as in downloadable flat form. For any data set, ISMARA infers the key regulators in the system, their activities across the input samples, the genes and pathways they target, and the core interactions between the regulators. We believe that by empowering experimental researchers to apply cutting-edge computational systems biology tools to their data in a completely automated manner, ISMARA can play an important role in developing our understanding of regulatory networks across metazoans.

Keywords: gene expression analysis, high-throughput sequencing analysis, transcription factor activity, transcription regulation

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Authors: Charles Lee

Abstract:

The Principal Orthogonal Decomposition (POD) technique has been used as a model reduction tool for many applications in engineering and science. In principle, one begins with an ensemble of data, called snapshots, collected from an experiment or laboratory results. The beauty of the POD technique is that when applied, the entire data set can be represented by the smallest number of orthogonal basis elements. It is the such capability that allows us to reduce the complexity and dimensions of many physical applications. Mathematical formulations and numerical schemes for the POD method will be discussed along with applications in NASA’s Deep Space Large Antenna Arrays, Satellite Image Reconstruction, Cancer Detection with DNA Microarray Data, Maximizing Stock Return, and Medical Imaging.

Keywords: reduced-order methods, principal component analysis, cancer detection, image reconstruction, stock portfolios

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Authors: Van Huong Mai, Kanokwan Nithiratphat, Adool Booncham

Abstract:

The Movement of Contemporary Life consisted of two purposes, which were to study the movement and development of the modern life and to create the visual arts, which were paintings expressed via the form of apartment buildings was used from mixed media (digital printing and acrylic painting on canvas) which conveyed the rapid pace of modern life leading to diverse movements in viewer’s feeling. The operation of this creation was collected field data, documentary data, and influence from creative work. The data analysis was analyzed in order to theme, form, technique, and process to satisfy of concept and special character of the pieces.

Keywords: movement, contemporary life, visual art, acrylic painting, digital art, urban space

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Authors: Kunyanuth Kularbphettong, Cholticha Tongsiri

Abstract:

This paper aims to create the model for student in choosing an emphasized track of student majoring in computer science at Suan Sunandha Rajabhat University. The objective of this research is to develop the suggested system using data mining technique to analyze knowledge and conduct decision rules. Such relationships can be used to demonstrate the reasonableness of student choosing a track as well as to support his/her decision and the system is verified by experts in the field. The sampling is from student of computer science based on the system and the questionnaire to see the satisfaction. The system result is found to be satisfactory by both experts and student as well.

Keywords: data mining technique, the decision support system, knowledge and decision rules, education

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Authors: Reem Osama Yousif Ali, Osama Yousif Ali Al Gibali

Abstract:

Introduction: Balanced nutrition is undeniably essential for maintaining health, body functions, and integrity of cell metabolism; however, some sick patients cannot tolerate oral or enteral feeding to meet their nutritional needs, so partial or total parenteral nutrition (PN) may be the most suitable alternative route in such situations. Dietitians are fundamental personnel among the medical team to ensure the proper provision of PN service, which was introduced in Sudan in the 1980s. Objective: The study aimed to recognize the dietitians' awareness of parenteral nutrition and their role in providing this service in Sudan – Khartoum State. Methodology: Formulated questionnaire forms composed of twelve questions were distributed to the dietitians working in four tertiary level hospitals. Results: The majority (75%) of the responded dietitians had reasonable knowledge about the importance of PN, its advantages, and its indications. Sixty percent of them were mindful of the PN side effects. Most of the dietitians were aware of the different assessment measurements and PN calculations and were exposed in their clinical practice to patients who were in need of PN, but only a few of them (about 30%) had the actual chance to participate in the formulation and application of PN therapy. The unavailability of the multidisciplinary team, lack of the required equipment and financial support, and associated complications were basic obstacles to the provision of long-term PN service in Khartoum state hospitals. Conclusion: Although dietitians in Khartoum state hospitals have good information about PN definition, indications, accesses, and assessment measures, they do not have enough knowledge and clinical exposure that make them confident to provide the PN service. Establishing a few models of parenteral nutrition units in tertiary hospitals will be of great help, as well as providing the dietitian's training in the area of parenteral nutrition. Further study can explore more requirements to run this service.

Keywords: nutrition support, dietitian, Sudan, parenteral nutrition, nutrition support team

Procedia PDF Downloads 88