Search results for: data communication

Authors: Jianqin Qu

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This paper proposes a rigid point set matching algorithm in arbitrary dimensions based on the idea of symmetric covariant function. A group of functions of the points in the set are formulated using rigid invariants. Each of these functions computes a pair of correspondence from the given point set. Then the computed correspondences are used to recover the unknown rigid transform parameters. Each computed point can be geometrically interpreted as the weighted mean center of the point set. The algorithm is compact, fast, and dimension free without any optimization process. It either computes the desired transform for noiseless data in linear time, or fails quickly in exceptional cases. Experimental results for synthetic data and 2D/3D real data are provided, which demonstrate potential applications of the algorithm to a wide range of problems.

Keywords: covariant point, point matching, dimension free, rigid registration

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Authors: Goutom K. Pall

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At the very heart of the power system, power transmission (PT) acts as an essential link between power generation and distribution. Timely completion of PT infrastructures is therefore crucial to support the development of power system as a whole. Yet despite the importance, studies on PT infrastructure development projects are embryonic and, hence, PT projects undergoing widespread delays worldwide. These delay factors are idiosyncratic and identifying the critical delay factors is essential if the PT industry professionals are to complete their projects efficiently and within the expected timeframes. This study identifies and categorizes 46 causes of PT project delay under ten major groups using six sector expert’s recommendations studied by a preliminary questionnaire survey. Based on the experts’ strong recommendations, two new groups are introduced in the final questionnaire survey: sector specific factors (SSF) and general factors (GF). SSF pertain to delay factors applicable only to the PT projects, while GF represents less biased samples with shared responsibilities of all project parties involved in a project. The study then uses 112 data samples from the contractors to rank the delay factors using relative importance index (RII). The results reveal that SSF, GF and external factors are the most critical groups, while the highest ranked delay factors include the right of way (RoW) problems of transmission lines (TL), delay in payments, frequent changes in TL routes, poor communication and coordination among the project parties and accessibility to TL tower locations. Finally, recommendations are made to minimize the identified delay. The findings are expected to be of substantial benefit to professionals in minimizing time overrun in PT projects implementation, as well as power generation, power distribution, and non-power linear construction projects worldwide.

Keywords: delay, project delay, power transmission projects, time-overruns

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Authors: Edith Lotachukwu Ochege

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Nations stay together when citizens share enough values and preferences and can communicate with each other. Homogeneity among people can be built with education, teaching a common language to facilitate communication, infrastructure for easier travel, but also by brute force such as prohibiting local cultures. This paper discusses the role of language education in nation building. It defines education, highlights the functions of language. Furthermore, it expresses socialization agents that aid culture which are all embodied in language, problems of nation building.

Keywords: nation building, language education, function of language, socialization

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Authors: Hossein Jafari, Xiangfang Li, Lijun Qian, Alexander Aved, Timothy Kroecker

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Traditionally in sensor networks and recently in the Internet of Things, numerous heterogeneous sensors are deployed in distributed manner to monitor a phenomenon that often can be model by an underlying stochastic process. The big time-series data collected by the sensors must be analyzed to detect change in the stochastic process as quickly as possible with tolerable false alarm rate. However, sensors may have different accuracy and sensitivity range, and they decay along time. As a result, the big time-series data collected by the sensors will contain uncertainties and sometimes they are conflicting. In this study, we present a framework to take advantage of Evidence Theory (a.k.a. Dempster-Shafer and Dezert-Smarandache Theories) capabilities of representing and managing uncertainty and conflict to fast change detection and effectively deal with complementary hypotheses. Specifically, Kullback-Leibler divergence is used as the similarity metric to calculate the distances between the estimated current distribution with the pre- and post-change distributions. Then mass functions are calculated and related combination rules are applied to combine the mass values among all sensors. Furthermore, we applied the method to estimate the minimum number of sensors needed to combine, so computational efficiency could be improved. Cumulative sum test is then applied on the ratio of pignistic probability to detect and declare the change for decision making purpose. Simulation results using both synthetic data and real data from experimental setup demonstrate the effectiveness of the presented schemes.

Keywords: CUSUM, evidence theory, kl divergence, quickest change detection, time series data

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Authors: Tania Chalton

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In June 2013, an independent review of the Liverpool Care Pathway (LCP) identified a number of problems with the implementation of the LCP in the UK and recommended that it be replaced by individual care plans for each patient. As a result of the UK findings, in November 2013 the Ministry of Health (MOH) commissioned the Palliative Care Council to initiate a programme of work to investigate an appropriate approach for the care of people in their last days of life in New Zealand (NZ). The Last Days of Life Working Group commenced a process to develop national consensus on the care of people in their last days of life in April 2014. In order to develop its advice for the future provision of care to people in their last days of life, the Working Group (WG) established a comprehensive work programme and as a result has developed a series of working papers. Specific areas of focus included: An analysis of the UK Independent Review findings and an assessment of these findings to the NZ context. A stocktake of services providing care to people in their last days of life, including aged residential care (ARC); hospices; hospitals; and primary care. International and NZ literature reviews of evidence and best practice. Survey of family to understand the consumer perspective on the care of people in their last days of life. Key aspects of care that required further considerations for NZ were: Terminology: clarify terminology used in the last days of life and in relation to death and dying. Evidenced based: including specific review of evidence regarding, spiritual, culturally appropriate care as well as dementia care. Diagnosis of dying: need for both guidance around the diagnosis of dying and communication with family. Workforce issues: access to an appropriate workforce after hours. Nutrition and hydration: guidance around appropriate approaches to nutrition and hydration. Symptom and pain management: guidance around symptom management. Documentation: documentation of the person’s care which is robust enough for data collection and auditing requirements, not ‘tick box’ approach to care. Education and training: improved consistency and access to appropriate education and training. Leadership: A dedicated team or person to support and coordinate the introduction and implementation of any last days of life model of care. Quality indicators and data collection: model of care to enable auditing and regular reviews to ensure on-going quality improvement. Cultural and spiritual: address and incorporate any cultural and spiritual aspects. A final document was developed incorporating all the evidence which provides guidance to the health sector on best practice for people at end of life: “Principles and guidance for the last days of life: Te Ara Whakapiri”.

Keywords: end of life, guidelines, New Zealand, palliative care

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Authors: Shohei Maruyama, Yasuo Matsuyama, Sachiyo Aburatani

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The development of the method to annotate unknown gene functions is an important task in bioinformatics. One of the approaches for the annotation is The identification of the metabolic pathway that genes are involved in. Gene expression data have been utilized for the identification, since gene expression data reflect various intracellular phenomena. However, it has been difficult to estimate the gene function with high accuracy. It is considered that the low accuracy of the estimation is caused by the difficulty of accurately measuring a gene expression. Even though they are measured under the same condition, the gene expressions will vary usually. In this study, we proposed a feature extraction method focusing on the variability of gene expressions to estimate the genes' metabolic pathway accurately. First, we estimated the distribution of each gene expression from replicate data. Next, we calculated the similarity between all gene pairs by KL divergence, which is a method for calculating the similarity between distributions. Finally, we utilized the similarity vectors as feature vectors and trained the multiclass SVM for identifying the genes' metabolic pathway. To evaluate our developed method, we applied the method to budding yeast and trained the multiclass SVM for identifying the seven metabolic pathways. As a result, the accuracy that calculated by our developed method was higher than the one that calculated from the raw gene expression data. Thus, our developed method combined with KL divergence is useful for identifying the genes' metabolic pathway.

Keywords: metabolic pathways, gene expression data, microarray, Kullback–Leibler divergence, KL divergence, support vector machines, SVM, machine learning

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Authors: Mohanad Elemary, Imose Itua, Rajeswari B. Matam

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Virologists and public health experts have been predicting potential pandemics from coronaviruses for decades. The viruses which caused the SARS and MERS pandemics and the Nipah virus led to many lost lives, but still, the COVID-19 pandemic caused by the SARS-CoV2 virus surprised many scientific communities, experts, and governments with its ease of transmission and its pathogenicity. Governments of various countries reacted by locking down entire populations to their homes to combat the devastation caused by the virus, which led to a loss of livelihood and economic hardship to many individuals and organizations. To revive national economies and support their citizens in resuming their lives, governments focused on the development and use of contact tracing apps as a digital way to track and trace exposure. Google and Apple introduced the Exposure Notification Systems (ENS) framework. Independent organizations and countries also developed different frameworks for contact tracing apps. The efficiency, popularity, and adoption rate of these various apps have been different across countries. In this paper, we present a critical analysis of the different contact tracing apps with respect to their efficiency, adoption rate and general perception, and the governmental strategies and policies, which led to the development of the applications. When it comes to the European countries, each of them followed an individualistic approach to the same problem resulting in different realizations of a similarly functioning application with differing results of use and acceptance. The study conducted an extensive review of existing literature, policies, and reports across multiple disciplines, from which a framework was developed and then validated through interviews with six key stakeholders in the field, including founders and executives in digital health startups and corporates as well as experts from international organizations like The World Health Organization. A framework of best practices and tactics is the result of this research. The framework looks at three main questions regarding the contact tracing apps; how to develop them, how to deploy them, and how to regulate them. The findings are based on the best practices applied by governments across multiple countries, the mistakes they made, and the best practices applied in similar situations in the business world. The findings include multiple strategies when it comes to the development milestone regarding establishing frameworks for cooperation with the private sector and how to design the features and user experience of the app for a transparent, effective, and rapidly adaptable app. For the deployment section, several tactics were discussed regarding communication messages, marketing campaigns, persuasive psychology, and the initial deployment scale strategies. The paper also discusses the data privacy dilemma and how to build for a more sustainable system of health-related data processing and utilization. This is done through principles-based regulations specific for health data to allow for its avail for the public good. This framework offers insights into strategies and tactics that could be implemented as protocols for future public health crises and emergencies whether global or regional.

Keywords: contact tracing apps, COVID-19, digital health applications, exposure notification system

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Authors: Tabinda Sadiq, Tehmina Ashfaq Qazi, Hoor Shumail

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Recently, the advent of emerging technology has created an emerging generation of restaurant marketing. It explores the aspects that influence customers’ decision-making process in selecting a restaurant after reading food bloggers' reviews online. The motivation behind this research is to investigate the correlation between the credibility of the source and their attitude toward restaurant visits. The researcher collected the data by distributing a survey questionnaire through google forms by employing the Source credibility theory. Non- probability purposive sampling technique was used to collect data. The questionnaire used a predeveloped and validated scale by Ohanian to measure the relationship. Also, the researcher collected data from 250 respondents in order to investigate the influence of food bloggers on Gen Z's decision-making process. SPSS statistical version 26 was used for statistical testing and analyzing the data. The findings of the survey revealed that there is a moderate positive correlation between the variables. So, it can be analyzed that food bloggers do have an impact on Generation Z's decision making process.

Keywords: credibility, decision making, food bloggers, generation z, e-wom

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Authors: Rinyu Shei Mercy

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Protected areas are the potential areas for the development of ecotourism because of their biodiversity, landscapes, waterfalls, lakes, caves, salt lick and cultural heritage of local or indigenous people. These potentials have not yet been valorized, so this study will enable to investigate the evaluation and possibilities of valorization of ecotourism potentials in the Mbam and Djerem National Park. Hence, this was done by employing a combination of field observations, examination, data collection and evaluation, using a SWOT analysis. The SWOT provides an analysis to determine the strengths, weaknesses, opportunities and threats, and strategic suggestions for ecological planning. The study helps to determine an ecotouristic inventory and mapping of ecotourism potentials of the park, evaluate the degree of valorization of these potentials and the possibilities of valorization. Finally, the study has proven that the park has much natural potentials such as rivers, salt licks, waterfall and rapids, lakes, caves and rocks, etc. Also, from the study, it was realized that as concerns the degree of valorization of these ecotourism potentials, 50% of the population visit the salt lick of Pkayere because it’s a biodiversity hotspot and rich in mineral salt attracting a lot of animals and the least is the lake Miyere with 1% due to the fact that it is sacred. Moreover, from the results, there are possibilities that these potentials can be valorized and put into use because of their attractive nature such as creating good roads and bridges, good infrastructural facilities, good communication network etc. So, the study recommends that, in this process, MINTOUR, WCS, tour operators must interact sufficiently in order to develop the potential interest to ecotourism, ecocultural tourism and scientific tourism.

Keywords: ecotourism, national park Mbam and Djerem, valorization of biodiversity, protected areas of Cameroon

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Authors: Pornpimol Chaiwuttisak

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The study aims to compare the performance of the logistics for Thailand’s wholesale and retail trade industries (except motor vehicles, motorcycle, and stalls) by using data (data envelopment analysis). Thailand Standard Industrial Classification in 2009 (TSIC - 2009) categories that industries into sub-group no. 45: wholesale and retail trade (except for the repair of motor vehicles and motorcycles), sub-group no. 46: wholesale trade (except motor vehicles and motorcycles), and sub-group no. 47: retail trade (except motor vehicles and motorcycles. Data used in the study is collected by the National Statistical Office, Thailand. The study consisted of four input factors include the number of companies, the number of personnel in logistics, the training cost in logistics, and outsourcing logistics management. Output factor includes the percentage of enterprises having inventory management. The results showed that the average relative efficiency of small-sized enterprises equals to 27.87 percent and 49.68 percent for the medium-sized enterprises.

Keywords: DEA, wholesales and retails, logistics, Thailand

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Authors: Yuta Nakano, Kozo Kajiwara, Atsushi Hori, Takeshi Fujita

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In association with the wave of electric vehicles (EV), low energy consumption systems have become more and more important. One of the key technologies to realize low energy consumption is a dynamic vision sensor (DVS), or we can call it an event sensor, neuromorphic vision sensor and so on. This sensor has several features, such as high temporal resolution, which can achieve 1 Mframe/s, and a high dynamic range (120 DB). However, the point that can contribute to low energy consumption the most is its sparsity; to be more specific, this sensor only captures the pixels that have intensity change. In other words, there is no signal in the area that does not have any intensity change. That is to say, this sensor is more energy efficient than conventional sensors such as RGB cameras because we can remove redundant data. On the other side of the advantages, it is difficult to handle the data because the data format is completely different from RGB image; for example, acquired signals are asynchronous and sparse, and each signal is composed of x-y coordinate, polarity (two values: +1 or -1) and time stamp, it does not include intensity such as RGB values. Therefore, as we cannot use existing algorithms straightforwardly, we have to design a new processing algorithm to cope with DVS data. In order to solve difficulties caused by data format differences, most of the prior arts make a frame data and feed it to deep learning such as Convolutional Neural Networks (CNN) for object detection and recognition purposes. However, even though we can feed the data, it is still difficult to achieve good performance due to a lack of intensity information. Although polarity is often used as intensity instead of RGB pixel value, it is apparent that polarity information is not rich enough. Considering this context, we proposed to use the timestamp information as a data representation that is fed to deep learning. Concretely, at first, we also make frame data divided by a certain time period, then give intensity value in response to the timestamp in each frame; for example, a high value is given on a recent signal. We expected that this data representation could capture the features, especially of moving objects, because timestamp represents the movement direction and speed. By using this proposal method, we made our own dataset by DVS fixed on a parked car to develop an application for a surveillance system that can detect persons around the car. We think DVS is one of the ideal sensors for surveillance purposes because this sensor can run for a long time with low energy consumption in a NOT dynamic situation. For comparison purposes, we reproduced state of the art method as a benchmark, which makes frames the same as us and feeds polarity information to CNN. Then, we measured the object detection performances of the benchmark and ours on the same dataset. As a result, our method achieved a maximum of 7 points greater than the benchmark in the F1 score.

Keywords: event camera, dynamic vision sensor, deep learning, data representation, object recognition, low energy consumption

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Authors: Parvin Ghafarian, Mohammadreza Mohammadpur Panchah, Mehri Fallahi

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Synoptic patterns from surface up to tropopause are very important for forecasting the weather and atmospheric conditions. There are many tools to prepare and analyze these maps. Reanalysis data and the outputs of numerical weather prediction models, satellite images, meteorological radar, and weather station data are used in world forecasting centers to predict the weather. The forecasting extreme precipitating on the southern coast of the Caspian Sea (CS) is the main issue due to complex topography. Also, there are different types of climate in these areas. In this research, we used two reanalysis data such as ECMWF Reanalysis 5th Generation Description (ERA5) and National Centers for Environmental Prediction /National Center for Atmospheric Research (NCEP/NCAR) for verification of the numerical model. ERA5 is the latest version of ECMWF. The temporal resolution of ERA5 is hourly, and the NCEP/NCAR is every six hours. Some atmospheric parameters such as mean sea level pressure, geopotential height, relative humidity, wind speed and direction, sea surface temperature, etc. were selected and analyzed. Some different type of precipitation (rain and snow) was selected. The results showed that the NCEP/NCAR has more ability to demonstrate the intensity of the atmospheric system. The ERA5 is suitable for extract the value of parameters for specific point. Also, ERA5 is appropriate to analyze the snowfall events over CS (snow cover and snow depth). Sea surface temperature has the main role to generate instability over CS, especially when the cold air pass from the CS. Sea surface temperature of NCEP/NCAR product has low resolution near coast. However, both data were able to detect meteorological synoptic patterns that led to heavy rainfall over CS. However, due to the time lag, they are not suitable for forecast centers. The application of these two data is for research and verification of meteorological models. Finally, ERA5 has a better resolution, respect to NCEP/NCAR reanalysis data, but NCEP/NCAR data is available from 1948 and appropriate for long term research.

Keywords: synoptic patterns, heavy precipitation, reanalysis data, snow

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Authors: Hung Lin-Zin, Lai Mei-Yen

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Prostate cancer is the most commonly diagnosed male cancer in the U.S. The prevalence is around 1 in 8. The etiology of prostate cancer is still unknown, but some predisposing factors, such as age, black race, family history, and obesity, may increase the risk of the disease. In 2020, a total of 7,178 Taiwanese people were nearly diagnosed with prostate cancer, accounting for 5.88% of all cancer cases, and the incidence rate ranked fifth among men. In that year, the total number of deaths from prostate cancer was 1,730, accounting for 3.45% of all cancer deaths, and the death rate ranked 6th among men, accounting for 94.34% of the cases of male reproductive organs. Looking for domestic and foreign literature on the use of OMOP (Observational Medical Outcomes Partnership, hereinafter referred to as OMOP) database analysis, there are currently nearly a hundred literature published related to nursing-related health problems and nursing measures built in the OMOP general data model database of medical institutions are extremely rare. The OMOP common data model construction analysis platform is a system developed by the FDA in 2007, using a common data model (common data model, CDM) to analyze and monitor healthcare data. It is important to build up relevant nursing information from the OMOP- CDM database to assist our daily practice. Therefore, we choose prostate cancer patients who are our popular care objects and use the OMOP- CDM database to explore the common associated health problems. With the assistance of OMOP-CDM database analysis, we can expect early diagnosis and prevention of prostate cancer patients' comorbidities to improve patient care.

Keywords: OMOP, nursing diagnosis, health problem, prostate cancer

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Authors: Argaw T. Gurmu, Muhammad N. Mahmood

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The objective of this research is to identify the architecture and construction management students’ learning challenges of the building measurement. This research used the survey data obtained collected from the students who completed the building measurement unit. NVivo qualitative data analysis software was used to identify relevant themes. The analysis of the qualitative data revealed the major learning difficulties such as inadequacy of practice questions for the examination, inability to work as a team, lack of detailed understanding of the prerequisite units, insufficiency of the time allocated for tutorials and incompatibility of lecture and tutorial schedules. The output of this research can be used as a basis for improving the teaching and learning activities in construction measurement units.

Keywords: building measurement, construction management, learning challenges, evaluate survey

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Authors: Ing-Jen Hung, Tzu-Chien Wang

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Nowadays, customers can interact with firms through miscellaneous online ads on different channels easily. In other words, customer now has innumerable options and limitless time to accomplish their commercial activities with firms, individualizing their own online customer journey. This kind of convenience emphasizes the importance of online advertisement allocation on different channels. Therefore, profound understanding of customer behavior can make considerable benefit from optimizing fund allocation on diverse ad channels. To achieve this objective, multiple firms utilize numerical methodology to create data-driven advertisement policy. In our research, we aim to exploit online customer click data to discover the correlations between each channel and their sequential relations. We use LSTM to deal with sequential property of our data and compare its accuracy with other non-sequential methods, such as CART decision tree, logistic regression, etc. Besides, we also classify our customers into several groups by their behavioral characteristics to perceive the differences between all groups as customer portrait. As a result, we discover distinct customer journey under each customer portrait. Our article provides some insights into marketing research and can help firm to formulate online advertising criteria.

Keywords: LSTM, customer journey, marketing, channel ads

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Authors: Saurabh Shukla, G. N. Pandey

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In recent times, oil exploration and monitoring in on-shore areas have gained much importance considering the fact that in India the oil import is 62 percent of the total imports. Thus, architectural model like wireless sensor network to monitor on-shore deep sea oil well is being developed to get better estimate of the oil prospects. The problem we are facing nowadays that we have very few restricted areas of oil left today. Countries like India don’t have much large areas and resources for oil and this problem with most of the countries that’s why it has become a major problem when we are talking about oil exploration in on-shore areas also the increase of oil prices has further ignited the problem. For this the use of wireless network system having relative simplicity, smallness in size and affordable cost of wireless sensor nodes permit heavy deployment in on-shore places for monitoring oil wells. Deployment of wireless sensor network in large areas will surely reduce the cost it will be very much cost effective. The objective of this system is to send real time information of oil monitoring to the regulatory and welfare authorities so that suitable action could be taken. This system architecture is composed of sensor network, processing/transmission unit and a server. This wireless sensor network system could remotely monitor the real time data of oil exploration and monitoring condition in the identified areas. For wireless sensor networks, the systems are wireless, have scarce power, are real-time, utilize sensors and actuators as interfaces, have dynamically changing sets of resources, aggregate behaviour is important and location is critical. In this system a communication is done between the server and remotely placed sensors. The server gives the real time oil exploration and monitoring conditions to the welfare authorities.

Keywords: sensor, wireless sensor network, oil, sensor, on-shore level

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Authors: Yalda Zarnegarnia, Shari Messinger

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Receiver operating characteristic (ROC) curves have been widely used in medical research to illustrate the performance of the biomarker in correctly distinguishing the diseased and non-diseased groups. Correlated biomarker data arises in study designs that include subjects that contain same genetic or environmental factors. The information about correlation might help to identify family members at increased risk of disease development, and may lead to initiating treatment to slow or stop the progression to disease. Approaches appropriate to a case-control design matched by family identification, must be able to accommodate both the correlation inherent in the design in correctly estimating the biomarker’s ability to differentiate between cases and controls, as well as to handle estimation from a matched case control design. This talk will review some developed methods for ROC curve estimation in settings with correlated data from case control design and will discuss the limitations of current methods for analyzing correlated familial paired data. An alternative approach using Conditional ROC curves will be demonstrated, to provide appropriate ROC curves for correlated paired data. The proposed approach will use the information about the correlation among biomarker values, producing conditional ROC curves that evaluate the ability of a biomarker to discriminate between diseased and non-diseased subjects in a familial paired design.

Keywords: biomarker, correlation, familial paired design, ROC curve

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Authors: Adeela Abu Bakar, Minder Kaur, Parthaman Singh

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In the Malaysian education system, a formal setting of English language learning takes place in a content-based classroom (CBC). Until recently, there is less study in Malaysia, which researched the effects of code-switching (CS) behaviour towards the students’ knowledge sharing (KS) with their peers. The aim of this study is to investigate the frequency, reasons, and effect that CS, from the English language to Bahasa Melayu, has among local STEM and N-STEM undergraduates towards KS in a content-based classroom. The study implies a mixed-method research design with questionnaire and interviews as the instruments. The data is collected through distribution of questionnaires and interviews with the undergraduates. The quantitative data is analysed using SPSS in simple frequencies and percentages, whereas qualitative data involves organizing the data into themes, followed by analysis. Findings found that N-STEM undergraduates code-switch more as compared to STEM undergraduates. In addition to that, both the STEM and N-STEM undergraduates agree that CS acts as a catalyst towards KS in a content-based classroom. However, they also acknowledge that excess use of CS can be a hindrance towards KS. The findings of the study can benefit STEM and N-STEM undergraduates, education policymakers, language teachers, university educators, and students with significant insights into the role of CS towards KS in a content-based classroom. Some of the recommendations that can be applied for future studies are that the number of participants can be increased, an observation to be included for the data collection.

Keywords: switching, content-based classroom, content and language integrated learning, knowledge sharing, STEM and N-STEM undergraduates

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Authors: Ana Nemsadze

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Contemporary era and society are called postindustrial era and postindustrial society and/or informational era and informational society. Today science intends to define concept of information and comprehend informations role and function in contemporary society. Organization of social environment and governance of public processes on the base of information and tools of communication are main characteristics of informational era. This was defined by technological changes which were accomplished in culture in the second half of twentieth century. Today Georgia as an independent state needs to create an informational discourse of the country and therefore it is very important to study political and social cases which accomplished in the country after collapse of the Soviet Union because they start to define the present and the future of the country. The purpose of this study is to analyze political cases of the latest history of Georgia in terms of culture and information, concretely to elucidate which political cases transformed social life of post Soviet Georgia most of all who accomplished these political cases which visual and verbal messages was each political case spread with. The research is conducted on the base of interview. Participants of the interview are people of various specializations. Their professional activity is related to reflections on culture and theme of visual communication. They are philosophers sociologists a journalist media researcher a politologist a painter. The participants of the interview enumerated political cases and characterized them separately. Every expert thinks that declaration of independence of Georgia is the most important fact among all facts which were implemented in Georgia after collapse of the Soviet Union. The research revealed important social and political cases. Most of the cases are related to independence and territorial integrity of the state. Presidents of Georgia Zviad Gamsakhurdia Eduard Shevardnadze Mikheil Saakashvili Catholocos-Patriarch of All Georgia, the Archbishop of Mtskheta Tbilisi and Metropolitan bishop of Bichvinta and Tskhum Abkhazia Ilia II, businessman Bidzina Ivanishvili assumed dominating roles in cases. Verbal narrative of the cases accomplished during Zviad Gamsakhurdia presidential term expresses national freedom and visual part of cases of the same period expresses ruin of social-political structure. Verbal narrative of the cases accomplished during Eduard Sevardnadze presidential term expresses Free State and stability and reestablishment of Georgias political function in international relations and visual part of cases of the same period describes the most important moment of his presidential term and Eduard Shevardnadzes face appears too. Verbal narrative of the cases accomplished during Mikheil Saakashvilis presidential term expresses social renewal and visual part of cases of the same period describes August war and Mikheil Saakashvilis face appears too. The results of the study also reveal other details of visual verbal narrative of political and social cases of post Soviet Georgia. This gives a chance to start further reflection.

Keywords: culture, narrative, post soviet, visual communication

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Authors: Jolly Puri, Shiv Prasad Yadav

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Multi-component data envelopment analysis (MC-DEA) is a popular technique for measuring aggregate performance of the decision making units (DMUs) along with their components. However, the conventional MC-DEA is limited to crisp input and output data which may not always be available in exact form. In real life problems, data may be imprecise or fuzzy. Therefore, in this paper, we propose (i) a fuzzy MC-DEA (FMC-DEA) model in which shared and undesirable fuzzy resources are incorporated, (ii) the proposed FMC-DEA model is transformed into a pair of crisp models using cut approach, (iii) fuzzy aggregate performance of a DMU and fuzzy efficiencies of components are defined to be fuzzy numbers, and (iv) a numerical example is illustrated to validate the proposed approach.

Keywords: multi-component DEA, fuzzy multi-component DEA, fuzzy resources, decision making units (DMUs)

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Authors: Semeh Ben Salem, Sami Naouali, Moetez Sallami

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The increasing amount of collected data has limited the performance of the current analyzing algorithms. Thus, developing new cost-effective algorithms in terms of complexity, scalability, and accuracy raised significant interests. In this paper, a modified effective k-means based algorithm is developed and experimented. The new algorithm aims to reduce the computational load without significantly affecting the quality of the clusterings. The algorithm uses the City Block distance and a new stop criterion to guarantee the convergence. Conducted experiments on a real data set show its high performance when compared with the original k-means version.

Keywords: pattern recognition, global terrorism database, Manhattan distance, k-means clustering, terrorism data analysis

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Authors: Adel Francis

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Most of scheduling methods and software apply the critical path logic. This logic schedule activities, apply constraints between these activities and try to optimize and level the allocated resources. The extensive use of this logic produces a complex an erroneous network hard to present, follow and update. Planning and management building projects should tackle the coordination of works and the management of limited spaces, traffic, and supplies. Activities cannot be performed without the resources available and resources cannot be used beyond the capacity of workplaces. Otherwise, workspace congestion will negatively affect the flow of works. The objective of the space planning is to link the spatial and temporal aspects, promote efficient use of the site, define optimal site occupancy rates, and ensures suitable rotation of the workforce in the different spaces. The Chronographic scheduling modelling belongs to this category and models construction operations as well as their processes, logical constraints, association and organizational models, which help to better illustrate the schedule information using multiple flexible approaches. The model defined three categories of areas (punctual, surface and linear) and four different layers (space creation, systems, closing off space, finishing, and reduction of space). The Chronographical modelling is a more complete communication method, having the ability to alternate from one visual approach to another by manipulation of graphics via a set of parameters and their associated values. Each individual approach can help to schedule a certain project type or specialty. Visual communication can also be improved through layering, sheeting, juxtaposition, alterations, and permutations, allowing for groupings, hierarchies, and classification of project information. In this way, graphic representation becomes a living, transformable image, showing valuable information in a clear and comprehensible manner, simplifying the site management while simultaneously utilizing the visual space as efficiently as possible.

Keywords: building projects, chronographic modelling, CPM, critical path, precedence diagram, scheduling

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Authors: Zarine Avetisyan

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The paradigm of Modern Linguistics incorporates disciplines which allow to analyze both language and discourse units and to demonstrate the multi-layeredness of lingo-cultural consciousness. By implementing lingo-cognitive approach to discourse and communication studies, the present paper tries to create the integral linguistic picture of the concept of joy and to analyze the lexico-semantic groups and relevant lexico-semantic variants of its realization in the context of Modern English fiction.

Keywords: concept of joy, lexico-semantic variant, semantic sign, cognition

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Authors: Ishara Madusanka, So Morikawa

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Natural disasters, particularly floods, pose severe challenges globally, affecting both developed and developing countries. In many regions, especially Asia, riverine floods are prevalent and devastating. Integrated flood management incorporates structural and non-structural measures, with preventive relocation emerging as a cost-effective and proactive strategy for areas repeatedly impacted by severe flooding. However, preventive relocation is often hindered by economic, psychological, social, and institutional barriers. This study investigates the factors influencing resistance to preventive relocation and evaluates the role of flood risk information in shaping relocation decisions through risk perception. A conceptual model was developed, incorporating variables such as Flood Risk Information (FRI), Place Attachment (PA), Good Living Conditions (GLC), and Adaptation to Flooding (ATF), with Flood Risk Perception (FRP) serving as a mediating variable. The research was conducted in Welipitiya in the Polwatta river basin, Matara district, Sri Lanka, a region experiencing recurrent flood damage. For this study, an experimental design involving a structured questionnaire survey was utilized, with 185 households participating. The treatment group received flood risk information, including flood risk maps and historical data, while the control group did not. Data were collected in 2023 and analyzed using independent sample t-tests and Partial Least Squares Structural Equation Modeling (PLS-SEM). PLS-SEM was chosen for its ability to model latent variables, handle complex relationships, and suitability for exploratory research. Multi-group Analysis (MGA) assessed variations across different flood risk areas. Findings indicate that flood risk information had a limited impact on flood risk perception and relocation decisions, though its effect was significant in specific high-risk areas. Place attachment was a significant factor influencing relocation decisions across the sample. One potential reason for the limited impact of flood risk information on relocation decisions could be the lack of specificity in the information provided. The results suggest that while flood risk information alone may not significantly influence relocation decisions, it is crucial in specific contexts. Future studies and practitioners should focus on providing more detailed risk information and addressing psychological factors like place attachments to enhance preventive relocation efforts.

Keywords: flood risk communication, flood risk perception, place attachment, preventive relocation, structural equation modeling

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Authors: Suelane Garcia Fontes, Silvio Luiz Stanzani, Pedro L. Pizzigatti Corrła Ronaldo G. Morato

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Environmental changes and major natural disasters are most prevalent in the world due to the damage that humanity has caused to nature and these damages directly affect the lives of animals. Thus, the study of animal behavior and their interactions with the environment can provide knowledge that guides researchers and public agencies in preservation and conservation actions. Exploratory analysis of animal movement can determine the patterns of animal behavior and with technological advances the ability of animals to be tracked and, consequently, behavioral studies have been expanded. There is a lot of research on animal movement and behavior, but we note that a proposal that combines resources and allows for exploratory analysis of animal movement and provide statistical measures on individual animal behavior and its interaction with the environment is missing. The contribution of this paper is to present the framework AniMoveMineR, a unified solution that aggregates trajectory analysis and data mining techniques to explore animal movement data and provide a first step in responding questions about the animal individual behavior and their interactions with other animals over time and space. We evaluated the framework through the use of monitored jaguar data in the city of Miranda Pantanal, Brazil, in order to verify if the use of AniMoveMineR allows to identify the interaction level between these jaguars. The results were positive and provided indications about the individual behavior of jaguars and about which jaguars have the highest or lowest correlation.

Keywords: data mining, data science, trajectory, animal behavior

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Authors: Rei-Heng Cheng, Wen-Pinn Fang

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A wireless sensor network (WSN) is composed by a large number of sensors and one or a few base stations, where the sensor is responsible for detecting specific event information, which is sent back to the base station(s). However, how to save electricity consumption to extend the network lifetime is a problem that cannot be ignored in the wireless sensor networks. Since the sensor network is used to monitor a region or specific events, how the information can be reliably sent back to the base station is surly important. Network coding technique is often used to enhance the reliability of the network transmission. When a node needs to send out M data packets, it encodes these data with redundant data and sends out totally M + R packets. If the receiver can get any M packets out from these M + R packets, it can decode and get the original M data packets. To transmit redundant packets will certainly result in the excess energy consumption. This paper will explore relationship between the quality of wireless transmission and the number of redundant packets. Hopefully, each sensor can overhear the nearby transmissions, learn the wireless transmission quality around it, and dynamically determine the number of redundant packets used in network coding.

Keywords: energy consumption, network coding, transmission reliability, wireless sensor networks

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Authors: Su-Hyun Jung, Chang-Bin Ha, Hyoung-Kyu Song

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Recently, increasing the quality of experience (QoE) is an important issue. Since performance degradation at cell edge extremely reduces the QoE, several techniques are defined at LTE/LTE-A standard to remove inter-cell interference (ICI). However, the conventional techniques have disadvantage because there is a trade-off between resource allocation and reliable communication. The proposed scheme reduces the ICI more efficiently by using channel state information (CSI) smartly. It is shown that the proposed scheme can reduce the ICI with less resources.

Keywords: adaptive beamforming, CoMP, LTE-A, ICI reduction

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Authors: Chun-Yuan Chen, Ming-Chang Li, Xiu-Hui Wen, Yi-Ching Tu

Abstract:

The objective of this study explores GPS (Global Positioning System) applied to trace construction vehicles such as trucks or cranes, help to pattern the earth-dumping stations of traffic construction in Taiwan. Traffic construction in this research is defined as the engineering of high-speed railways, expressways, and which that distance more than kilometers. Audit the location and check the compliance with regulations of earth-dumping stations is one of important tasks in Taiwan EPA. Basically, the earth-dumping station was known as one source of particulate matter from air pollution during construction process. Due to GPS data can be analyzed quickly and be used conveniently, this study tried to find out dumping stations by modeling vehicles tracks from GPS data during work cycle of construction. The GPS data updated from 13 vehicles related to an expressway construction in central Taiwan. The GPS footprints were retrieved to Keyhole Markup Language (KML) files so that can pattern the tracks of trucks by computer applications, the data was collected about eight months- from Feb. to Oct. in 2017. The results of GPS footprints identified dumping station and outlined the areas of earthwork had been passed to the Taiwan EPA for on-site inspection. Taiwan EPA had issued advice comments to the agency which was in charge of the construction to prevent the air pollution. According to the result of this study compared to the commonly methods in inspecting environment by manual collection, the GPS with KML patterning and modeling method can consumes less time. On the other hand, through monitoring the GPS data from construction vehicles could be useful for administration to development and implementation of strategies in environmental management.

Keywords: automatic management, earth-dumping station, environmental management, Global Positioning System (GPS), particulate matter, traffic construction

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Authors: Gurcharan Singh Buttar

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It has been discovered that although these two areas, statistics, and information theory, are independent in their nature, they can be combined to create applications in multidisciplinary mathematics. This is due to the fact that where in the field of statistics, statistical parameters (measures) play an essential role in reference to the population (distribution) under investigation. Information measure is crucial in the study of ambiguity, assortment, and unpredictability present in an array of phenomena. The following communication is a link between the two, and it has been demonstrated that the well-known conventional statistical measures can be used as a measure of information.

Keywords: probability distribution, entropy, concavity, symmetry, variance, central tendency

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Authors: Javad Sadidi, Ehsan Babaei, Hani Rezayan

Abstract:

The advent of web 2.0 gives a possibility to scale down the costs of data collection and mapping, specifically if the process is done by volunteers. Every volunteer can be thought of as a free and ubiquitous sensor to collect spatial, descriptive as well as multimedia data for tourist services. The lack of large-scale information, such as real-time climate and weather conditions, population density, and other related data, can be considered one of the important challenges in developing countries for tourists to make the best decision in terms of time and place of travel. The current research aims to design and implement a spatiotemporal web map service using volunteer-submitted data. The service acts as a tourist-guide service in which tourists can search interested places based on their requested time for travel. To design the service, three tiers of architecture, including data, logical processing, and presentation tiers, have been utilized. For implementing the service, open-source software programs, client and server-side programming languages (such as OpenLayers2, AJAX, and PHP), Geoserver as a map server, and Web Feature Service (WFS) standards have been used. The result is two distinct browser-based services, one for sending spatial, descriptive, and multimedia volunteer data and another one for tourists and local officials. Local official confirms the veracity of the volunteer-submitted information. In the tourist interface, a spatiotemporal search engine has been designed to enable tourists to find a tourist place based on province, city, and location at a specific time of interest. Implementing the tourist-guide service by this methodology causes the following: the current tourists participate in a free data collection and sharing process for future tourists, a real-time data sharing and accessing for all, avoiding a blind selection of travel destination and significantly, decreases the cost of providing such services.

Keywords: VGI, tourism, spatiotemporal, browser-based, web mapping

Procedia PDF Downloads 89