Search results for: Big Data Movement

Authors: Samar M. Alqhtani, Suhuai Luo, Brian Regan

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Data fusion technology can be the best way to extract useful information from multiple sources of data. It has been widely applied in various applications. This paper presents a data fusion approach in multimedia data for event detection in twitter by using Dempster-Shafer evidence theory. The methodology applies a mining algorithm to detect the event. There are two types of data in the fusion. The first is features extracted from text by using the bag-ofwords method which is calculated using the term frequency-inverse document frequency (TF-IDF). The second is the visual features extracted by applying scale-invariant feature transform (SIFT). The Dempster - Shafer theory of evidence is applied in order to fuse the information from these two sources. Our experiments have indicated that comparing to the approaches using individual data source, the proposed data fusion approach can increase the prediction accuracy for event detection. The experimental result showed that the proposed method achieved a high accuracy of 0.97, comparing with 0.93 with texts only, and 0.86 with images only.

Keywords: data fusion, Dempster-Shafer theory, data mining, event detection

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Authors: Ioannis Iglezakis, Theodoros D. Trokanas, Panagiota Kiortsi

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This paper aims to explore major legal issues arising from the collection and processing of Health Big Data in the light of the new European secondary legislation for the protection of personal data of natural persons, placing emphasis on the General Data Protection Regulation 679/2016. Whether Big Health Data can be characterised as ‘personal data’ or not is really the crux of the matter. The legal ambiguity is compounded by the fact that, even though the processing of Big Health Data is premised on the de-identification of the data subject, the possibility of a combination of Big Health Data with other data circulating freely on the web or from other data files cannot be excluded. Another key point is that the application of some provisions of GPDR to Big Health Data may both absolve the data controller of his legal obligations and deprive the data subject of his rights (e.g., the right to be informed), ultimately undermining the fundamental right to the protection of personal data of natural persons. Moreover, data subject’s rights (e.g., the right not to be subject to a decision based solely on automated processing) are heavily impacted by the use of AI, algorithms, and technologies that reclaim health data for further use, resulting in sometimes ambiguous results that have a substantial impact on individuals. On the other hand, as the COVID-19 pandemic has revealed, Big Data analytics can offer crucial sources of information. In this respect, this paper identifies and systematises the legal provisions concerned, offering interpretative solutions that tackle dangers concerning data subject’s rights while embracing the opportunities that Big Health Data has to offer. In addition, particular attention is attached to the scope of ‘consent’ as a legal basis in the collection and processing of Big Health Data, as the application of data analytics in Big Health Data signals the construction of new data and subject’s profiles. Finally, the paper addresses the knotty problem of role assignment (i.e., distinguishing between controller and processor/joint controllers and joint processors) in an era of extensive Big Health data sharing. The findings are the fruit of a current research project conducted by a three-member research team at the Faculty of Law of the Aristotle University of Thessaloniki and funded by the Greek Ministry of Education and Religious Affairs.

Keywords: big health data, data subject rights, GDPR, pandemic

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Authors: Yong-Kyu Jung

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The fast growth in information technology has led to de-mands to access/process data. CPSs heavily depend on the time of hardware/software operations and communication over the network (i.e., real-time/parallel operations in CPSs (e.g., autonomous vehicles). Since data processing is an im-portant means to overcome the issue confronting data management, reducing the gap between the technological-growth and the data-complexity and channel-bandwidth. An adaptive perpetual data approximation method is intro-duced to manage the actual entropy of the digital spectrum. An ADAC implemented as an accelerator and/or apps for servers/smart-connected devices adaptively rescales digital contents (avg.62.8%), data processing/access time/energy, encryption/decryption overheads in AI/ML applications (facial ID/recognition).

Keywords: adaptive codec, AI, ML, HPC, cyber-physical, cybersecurity

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Authors: Mawloud Mosbah, Bachir Boucheham

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We present here the results for a comparative study of some techniques, available in the literature, related to the relevance feedback mechanism in the case of a short-term learning. Only one method among those considered here is belonging to the data mining field which is the K-Nearest Neighbours Algorithm (KNN) while the rest of the methods is related purely to the information retrieval field and they fall under the purview of the following three major axes: Shifting query, Feature Weighting and the optimization of the parameters of similarity metric. As a contribution, and in addition to the comparative purpose, we propose a new version of the KNN algorithm referred to as an incremental KNN which is distinct from the original version in the sense that besides the influence of the seeds, the rate of the actual target image is influenced also by the images already rated. The results presented here have been obtained after experiments conducted on the Wang database for one iteration and utilizing colour moments on the RGB space. This compact descriptor, Colour Moments, is adequate for the efficiency purposes needed in the case of interactive systems. The results obtained allow us to claim that the proposed algorithm proves good results; it even outperforms a wide range of techniques available in the literature.

Keywords: CBIR, category search, relevance feedback, query point movement, standard Rocchio’s formula, adaptive shifting query, feature weighting, original KNN, incremental KNN

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Authors: Veronica Kah Jo Wong, Yoke Mui Lim, Nurul Sakina Mokhtar Azizi

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The impact on the construction industry in Malaysia is unprecedented, as the government implemented a lockdown to restrict human movement in an effort to stop COVID-19 from spreading. Quantity surveyor (QS), as one of the key construction professionals, found that the working practices and environments for quantity surveyors today have changed due to the current pandemic. The QS profession must deal not only with changes in project issues but also with a different working environment in which most people are required to work from home and follow the standard operating procedures. Therefore, QS should be flexible, agile, and have the capability to adapt to the current working practices by strengthening their competencies. Adapting to the current and recovering environment of COVID-19 may result in the emergence of a new competence such as skill and knowledge for QS in order to maintain the quality of performance in the delivery of their professional services. Thus, this paper's objective is to investigate the changes in knowledge and skills in quantity surveyors. The data will be collected through interviews with registered professional QS to gain better insights that are specific in this industry, and the findings will be verified using the Delphi method. It is hoped that new knowledge and skill will be found from the study and will not only contribute to the betterment of the professional QS but also in guiding higher learning institutions to incorporate the new competencies into their curriculum.

Keywords: competency, COVID-19 pandemic, Malaysia, quantity surveying

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Authors: Patricia Sumod

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There is a unique movement of fashion that features a trend around secondhand clothing. This is especially observed in the lifestyles of the millennials, where the concept of reusing apparel and accessories is noticeable and, therefore, slowly diminishing the high consumption of fast fashion and generating environmental awareness. This paper will focus on how this clothing trend influences and engages consumers in buying secondhand clothing and creating fashionable looks simultaneously. To further examine the millennials’ motivation towards consumption and using secondhand fashion, a concept as a trendsetter, this paper will take a closer look at their idea of concern for the environment. Considering second-hand clothing is a sustainable consumption practice, it will investigate the role of social influencers, trendsetters, and millennials in overall fashion consumption in this context. This study aims to understand how secondhand clothing and millennials differ from other consumers regarding the perception of fast-depleting natural resources, price sensitivity, vintage attachments, and psychographics. Secondly, the paper will also present the connection of emotion between millennials and secondhand clothing that may not be necessarily purchased but received. This study will reflect on the already identified influences in increased purchase behavior and an uncharted positive relationship between the consumer and the products. This behavior will further formulate into a habit by consumer segments, creating an expanded market for secondhand clothing. There is no definite indication that fast fashion will cease to exist, but slowing its rapid movement is an attempt to work toward a sustainable future. The conclusion will present possibilities for consumers to engage in C2C online interaction, thereby reinforcing a notable change in consumer behavior and attitude in contradiction to today’s extreme consumerism and willingness to be adaptable to a minimalist way of life. Fashion brands will then begin a new forecast to actively accommodate the new millennial concept of fashion that will advertise more concern than insatiability. The research will be with literature from various authors, insights provided by researchers on this new wave of consumers, and a qualitative approach with face-to-face interviews with a sample group who are in the practice of secondhand clothing consumption.

Keywords: second-hand clothing, millennials, sustainability, consumption practice, fashion environment.

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Authors: Mohammad Zafar-ul Islam

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The breeding programme of Houbara bustard was started in Saudi Arabia in 1986 to undertake the restoration of native species such as Houbara through a programme of re-introduction, involving the release of captive-bred birds in the wild. Two sites were selected for houbara re-introduction, i.e., Mahazat as-Sayd and Saja Umm Ar-Rimth protected areas in 1988 and 1998 respectively. Both the areas are fenced fairly level, sandy plain with a few rock outcrops. Captive bred houbara have been released in Mahazat since 1992 by NWRC and those birds have been successfully breeding since then. The nesting season of the houbara at Mahazat recorded from February to May and on an average 20-25 nests are located each year but no nesting recorded in Saja. Houbara are monitored using radio transmitters through aerial tracking technique and also a vehicle for terrestrial tracking. Total population of houbara in Mahazat is roughly estimated around 300-400 birds, using the following: N = n1+n2+n3+n4+n5 (n1 = released or wild-born, radio, regularly monitored/checked; n2 = radio tagged missing; n3 = wild born chicks not recorded; n4 = wild born chicks, recorded but not tagged; n5 = immigrants). However, in Saja only 4-7 individuals of houbara have been survived since 2001 because most of the birds are predated immediately after the release. The mean annual home was also calculated using Kernel and Convex polygons methods with Range VII software. The minimum density of houbara was also calculated. In order to know the houbara movement or their migration to other regions, two captive-reared male houbara that were released into the wild and one wild born female were fitted with Platform Transmitter Terminals (PTT). The home range shows that wild-born female has larger movement than two males. More areas need to be selected for reintroduction programme to establish the network of sites to provide easy access to move these birds and mingle with the wild houbara. Some potential sites have been proposed which require more surveys to check the habitat suitability.

Keywords: re-introduction, survival rate, home range, Saudi Arabia

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Authors: Deniz Peksen

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This thesis aims to predict trend movement of closing price of stock and to maximize portfolio by utilizing the predictions. In this context, the study aims to define a stock portfolio strategy from models created by using Logistic Regression, Gradient Boosting and Random Forest. Recently, predicting the trend of stock price has gained a significance role in making buy and sell decisions and generating returns with investment strategies formed by machine learning basis decisions. There are plenty of studies in the literature on the prediction of stock prices in capital markets using machine learning methods but most of them focus on closing prices instead of the direction of price trend. Our study differs from literature in terms of target definition. Ours is a classification problem which is focusing on the market trend in next 20 trading days. To predict trend direction, fourteen years of data were used for training. Following three years were used for validation. Finally, last three years were used for testing. Training data are between 2002-06-18 and 2016-12-30 Validation data are between 2017-01-02 and 2019-12-31 Testing data are between 2020-01-02 and 2022-03-17 We determine Hold Stock Portfolio, Best Stock Portfolio and USD-TRY Exchange rate as benchmarks which we should outperform. We compared our machine learning basis portfolio return on test data with return of Hold Stock Portfolio, Best Stock Portfolio and USD-TRY Exchange rate. We assessed our model performance with the help of roc-auc score and lift charts. We use logistic regression, Gradient Boosting and Random Forest with grid search approach to fine-tune hyper-parameters. As a result of the empirical study, the existence of uptrend and downtrend of five stocks could not be predicted by the models. When we use these predictions to define buy and sell decisions in order to generate model-based-portfolio, model-based-portfolio fails in test dataset. It was found that Model-based buy and sell decisions generated a stock portfolio strategy whose returns can not outperform non-model portfolio strategies on test dataset. We found that any effort for predicting the trend which is formulated on stock price is a challenge. We found same results as Random Walk Theory claims which says that stock price or price changes are unpredictable. Our model iterations failed on test dataset. Although, we built up several good models on validation dataset, we failed on test dataset. We implemented Random Forest, Gradient Boosting and Logistic Regression. We discovered that complex models did not provide advantage or additional performance while comparing them with Logistic Regression. More complexity did not lead us to reach better performance. Using a complex model is not an answer to figure out the stock-related prediction problem. Our approach was to predict the trend instead of the price. This approach converted our problem into classification. However, this label approach does not lead us to solve the stock prediction problem and deny or refute the accuracy of the Random Walk Theory for the stock price.

Keywords: stock prediction, portfolio optimization, data science, machine learning

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Authors: Sašo Pečnik, Borut Žalik

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This paper presents a real-time visualization technique and filtering of classified LiDAR point clouds. The visualization is capable of displaying filtered information organized in layers by the classification attribute saved within LiDAR data sets. We explain the used data structure and data management, which enables real-time presentation of layered LiDAR data. Real-time visualization is achieved with LOD optimization based on the distance from the observer without loss of quality. The filtering process is done in two steps and is entirely executed on the GPU and implemented using programmable shaders.

Keywords: filtering, graphics, level-of-details, LiDAR, real-time visualization

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Authors: Hasik Lee, Seung-Young Kho

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Nowadays, automatic fare collection (AFC) system is widely used in many countries. However, smart card data from many of cities does not contain alighting information which is necessary to build OD matrices. Therefore, in order to utilize smart card data, destinations of passengers should be estimated. In this paper, kernel density estimation was used to forecast probabilities of alighting stations of bus passengers and applied to smart card data in Seoul, Korea which contains boarding and alighting information. This method was also validated with actual data. In some cases, stochastic method was more accurate than deterministic method. Therefore, it is sufficiently accurate to be used to build OD matrices.

Keywords: destination estimation, Kernel density estimation, smart card data, validation

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Authors: Qiong Hu

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From old English to modern English, the gender category has changed from grammatical gender system to natural gender system. The word classes that reflected gender has changed from pronouns, adjectives, and numerals in old English to only pronouns in modern English. In present-day English, the third person singular pronouns are the only paradigm that keeps an intact gender. 'He' and 'they' used as epicene pronouns are one of the two commonest phenomena of gender disagreement (the other being those against the natural gender). Considering the convenience of corpus concordance, epicene pronoun usage is selected in this study in which the anaphors are restricted to possessives (eg. his, their), and the antecedents are restricted to compound indefinite pronouns (eg. someone, somebody). Factors like writing form (eg. someone vs. some one), the semantics of the prefixes (eg. some- vs. any-), and suffixes (eg. -one vs. -body), as well as frequency, are taken into consideration. Statistics indicate that 'their' is increasingly used as the epicene pronoun compared with the decline of 'his' (when both writing forms are considered). This is influenced by social factors such as feminist movement, as well as the semantics and frequency of antecedents. Their (plural) used in anaphoric reference to various indefinite pronouns (singular in form) can also be treated as number variation in third person pronouns, and the trend that 'their' in place of his can also be treated as a change in number category. Among different candidates for the gender-neutral function, 'their' is proven to be the most promising one based on the diachronic data. This does not reject any new competitors in the future which still remains to be seen.

Keywords: language variation and change, epicene pronouns, gender, number

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Authors: Saeko Takahashi, Kazuo Hiraki

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Is it more fun to watch videos together than watching alone? Previous studies showed that synchronizing with others enhances subsequent prosocial behavior and affiliation, and conversely, prosocial individuals tend to coordinate with a partner to a greater extent. However, compared to adults, less is known about interpersonal coordination of young children in real-life situations because most studies have focused on children’s particular movement using specific tools or tasks in a laboratory setting. It has also been unclear if prosociality of young children affect the extent of interpersonal coordination within dyads. The present study examined data from motion capture of five body parts of 4-year-old dyads watching the same stimuli together or alone. A questionnaire survey including participants’ prosocial trait was also conducted. The wavelet coherence of each body parts within dyads was calculated as a measure of the extent of interpersonal coordination. Results showed that the dyads became significantly more coordinated in a social situation compared to a non-social situation. Moreover, dyads with averagely higher prosociality were more coordinated. These results shed some light on the development of interpersonal coordination in terms of social ability in young children. This study also offers a useful method for a study of spontaneous coordination in young children and infants without instructions or verbal responses.

Keywords: child development, interpersonal coordination, prosociality, synchrony, wavelet transform

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Authors: Jae Won Shin

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We develop an evaluated nuclear data based photonuclear reaction model of GEANT4 for a more accurate simulation of photon-induced neutron production. The evaluated photonuclear data libraries from the ENDF/B-VII.1 are taken as input. Incident photon energies up to 140 MeV which is the threshold energy for the pion production are considered. For checking the validity of the use of the data-based model, we calculate the photoneutron production cross-sections and yields and compared them with experimental data. The results obtained from the developed model are found to be in good agreement with the experimental data for (γ,xn) reactions.

Keywords: ENDF/B-VII.1, GEANT4, photoneutron, photonuclear reaction

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Authors: Rashi Bhalla, Russel Pears, M. Asif Naeem

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In this 'Information Explosion Era' analyzing data 'a critical commodity' and mining knowledge from vertically distributed data stream incurs huge communication cost. However, an effort to decrease the communication in the distributed environment has an adverse influence on the classification accuracy; therefore, a research challenge lies in maintaining a balance between transmission cost and accuracy. This paper proposes a method based on Bayesian inference to reduce the communication volume in a heterogeneous distributed environment while retaining prediction accuracy. Our experimental evaluation reveals that a significant reduction in communication can be achieved across a diverse range of dataset types.

Keywords: big data, bayesian inference, distributed data stream mining, heterogeneous-distributed data

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Authors: Benny Sand, Yotam Lurie, Shlomo Mark

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Medical Internet of Things (MIoT), AI, and data privacy are linked forever in a gordian knot. This paper explores the conflicts of interests between the stakeholders regarding data privacy in the MIoT arena. While patients are at home during healthcare hospitalization, MIoT can play a significant role in improving the health of large parts of the population by providing medical teams with tools for collecting data, monitoring patients’ health parameters, and even enabling remote treatment. While the amount of data handled by MIoT devices grows exponentially, different stakeholders have conflicting understandings and concerns regarding this data. The findings of the research indicate that medical teams are not concerned by the violation of data privacy rights of the patients' in-home healthcare, while patients are more troubled and, in many cases, are unaware that their data is being used without their consent. MIoT technology is in its early phases, and hence a mixed qualitative and quantitative research approach will be used, which will include case studies and questionnaires in order to explore this issue and provide alternative solutions.

Keywords: MIoT, data privacy, stakeholders, home healthcare, information privacy, AI

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Authors: S. F. Kanaan, Fatima Al-Kadi, H. Khrais

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Background: Fibromyalgia is a chronic condition that is characterized by chronic pain that limits physical and functional activities. To our best knowledge, there is currently no key physiotherapy approach recommended to reduce pain and improve function. In addition, there are scarce studies that investigated the effect of manual therapy in the management of Fibromyalgia, and no study investigated the efficacy of Mulligan´s mobilization with movement (MWM) in particular. Methods: A 51-year-old female diagnosed with Fibromyalgia for more than a year. The patient was complaining of generalized pain including neck, lower back, shoulders, elbows, hips, and knees. In addition, the patient reported severe limitation in activities and inability to complete her work as a lawyer. The Intervention provided for the patient consisted of 4 sessions (in two weeks) of MWM for neck, lower back, shoulders, elbows, sacroiliac joint, hips, and knees. The Visual Analogue Scale of pain (VAS), Range of Motion (ROM), 10-minute walk test, Roland Morris Low Back Pain and Disability Questionnaire (RMQ), Disability of the Arm, Shoulder and Hand Score (DASH) were collected at the baseline and at the end of treatment. Results: Average improvement of ROM in the neck, lower back, shoulder, elbows, hips, and knees was 45%. VAS scale changed from pre-treatment to post-treatment as the following: neck pain (9 to 0), lower back pain (8 to 1), shoulders pain (8 to 2), elbows pain (7 to 1), and knees pain (9 to 0). The patient demonstrated improvement in all functional scale from pre-intervention to post-intervention: 10-meter walk test (9.8 to 4.5 seconds), RMQ (21 to 11/24), and DASH (88.7% to 40.5%). The patient did not report any side effect of using this approach. Conclusion: Fibromyalgia can cause joint 'faulty position' leading to pain and dysfunction, which can be reversed by using MWM. MWM showed to have clinically significant improvement in ROM, pain, and ability to walk and a clinically significant reduction in disability in only 4 sessions. This work can be expanded in a larger sample.

Keywords: mobilization, fibromyalgia, dysfunction, manual therapy

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Authors: Cheryl-Ann Sarita Boodram

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Historically, the movement of people has been the subject of socio-political and economic regulatory policies which congeal to regulate human mobility and establish geopolitical and spatial identities and borderlands. As migratory practices evolved, so too has the problematization associated with movement, migration and citizenship. The emerging trends have led to active development of immigration technology governing human mobility and the naming of migratory practices. One such named phenomenon is ‘deportation’ or the forced removal of individuals from their adopted country. Deportation, has gained much attention within the human mobility landscape in the past twenty years following the September 2001 terrorist attack on the World Trade Centre in New York. In a reactionary move, several metropolitan countries, including Canada and the United Kingdom enacted or reviewed immigration laws which further enabled the removal of foreign born criminals to the land of their birth in the global south. Existing studies fall short of understanding the multiple textures of the forced returned migration experiences and the social injustices resulting from deportation displacement. This study brings together indigenous research methodologies through the use of participatory action research and social work with returned migrants in Trinidad and Tobago to uncover the experiences of displacement of deported nationals. The study explores the experiences of negotiating life as a ‘stranger’ and how return has influenced the construction of identities of returned nationals. Findings from this study reveal that deportation has led to inequalities and facilitated ‘othering’ of this group within their own country of birth. The study further highlighted that deportation leads to circuits of dispossession, and perpetuates inequalities. This study provides original insights into the way returned migrants negotiate, map and embody ‘strangeness’ and manage their return to a soil they consider unfamiliar and alien.

Keywords: stranger, alien geographies, displacement, deportation, negotiating strangeness, identity, otherness, alien landscapes

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Authors: Deepak Singh, Rail Kuliev

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The abstract highlights the critical importance of optimizing data integration and management strategies in the upstream oil and gas industry. With its complex and dynamic nature generating vast volumes of data, efficient data integration and management are essential for informed decision-making, cost reduction, and maximizing operational performance. Challenges such as data silos, heterogeneity, real-time data management, and data quality issues are addressed, prompting the proposal of several strategies. These strategies include implementing a centralized data repository, adopting industry-wide data standards, employing master data management (MDM), utilizing real-time data integration technologies, and ensuring data quality assurance. Training and developing the workforce, “reskilling and upskilling” the employees and establishing robust Data Management training programs play an essential role and integral part in this strategy. The article also emphasizes the significance of data governance and best practices, as well as the role of technological advancements such as big data analytics, cloud computing, Internet of Things (IoT), and artificial intelligence (AI) and machine learning (ML). To illustrate the practicality of these strategies, real-world case studies are presented, showcasing successful implementations that improve operational efficiency and decision-making. In present study, by embracing the proposed optimization strategies, leveraging technological advancements, and adhering to best practices, upstream oil and gas companies can harness the full potential of data-driven decision-making, ultimately achieving increased profitability and a competitive edge in the ever-evolving industry.

Keywords: master data management, IoT, AI&ML, cloud Computing, data optimization

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Authors: Farhad Asadi, Mohammad Javad Mollakazemi, Aref Ghafouri

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Recent research in neural networks science and neuroscience for modeling complex time series data and statistical learning has focused mostly on learning from high input space and signals. Local linear models are a strong choice for modeling local nonlinearity in data series. Locally weighted projection regression is a flexible and powerful algorithm for nonlinear approximation in high dimensional signal spaces. In this paper, different learning scenario of one and two dimensional data series with different distributions are investigated for simulation and further noise is inputted to data distribution for making different disordered distribution in time series data and for evaluation of algorithm in locality prediction of nonlinearity. Then, the performance of this algorithm is simulated and also when the distribution of data is high or when the number of data is less the sensitivity of this approach to data distribution and influence of important parameter of local validity in this algorithm with different data distribution is explained.

Keywords: local nonlinear estimation, LWPR algorithm, online training method, locally weighted projection regression method

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Authors: F. Amin, S. Feizi

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Big data has the potential to improve the quality of services; enable infrastructure that businesses depend on to adapt continually and efficiently; improve the performance of employees; help organizations better understand customers; and reduce liability risks. Analytics and marketing models of fixed and mobile operators are falling short in combating churn and declining revenue per user. Big Data presents new method to reverse the way and improve profitability. The benefits of Big Data and next-generation network, however, are more exorbitant than improved customer relationship management. Next generation of networks are in a prime position to monetize rich supplies of customer information—while being mindful of legal and privacy issues. As data assets are transformed into new revenue streams will become integral to high performance.

Keywords: big data, next generation networks, network transformation, strategy

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Authors: Ana Hol

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We live in a constantly changing environment where technology has become an integral component of our day to day life. We rely heavily on mobile devices, we search for data via web, we utilise smart home sensors to create the most suited ambiences and we utilise applications to shop, research, communicate and share data. Heavy reliance on technology therefore is creating new connections between STEM (Science, Technology, Engineering and Mathematics) fields which in turn rises a question of what the STEM education of the future should be like? This study was based on the reviews of the six Australian Information Systems students who undertook an international study tour to India where they were given an opportunity to network, communicate and meet local students, staff and business representatives and from them learn about the local business implementations, local customs and regulations. Research identifies that if we are to continue to implement and utilise electronic devices on the global scale, such as for example implement smart cars that can smoothly cross borders, we will need the workforce that will have the knowledge about the cars themselves, their parts, roads and transport networks, road rules, road sensors, road monitoring technologies, graphical user interfaces, movement detection systems as well as day to day operations, legal rules and regulations of each region and country, insurance policies, policing and processes so that the wide array of sensors can be controlled across country’s borders. In conclusion, it can be noted that allowing students to learn about the local conditions, roads, operations, business processes, customs and values in different countries is giving students a cutting edge advantage as such knowledge cannot be transferred via electronic sources alone. However once understanding of each problem or project is established, multidisciplinary innovative STEM projects can be smoothly conducted.

Keywords: STEM, curiosity, innovation, advancements

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Authors: Reiko Yamamoto

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This paper reports on a project to integrate Japanese (as a first language) and English (as a second language) education. This study focuses on the mutual effects of the two languages on the linguistic proficiency of elementary school students. The research team consisted of elementary school teachers and researchers at a university. The participants of the experiment were students between 3^rd and 6^th grades at an elementary school. The research process consisted of seven steps: 1) specifying linguistic proficiency; 2) developing the cross-curriculum of L1 and L2; 3) forming can-do statements; 4) creating a self-evaluation questionnaire; 5) executing the self-evaluation questionnaire at the beginning of the school year; 6) instructing L1 and L2 based on the curriculum; and 7) executing the self-evaluation questionnaire at the beginning of the next school year. In Step 1, the members of the research team brainstormed ways to specify elementary school students’ linguistic proficiency that can be observed in various scenes. It was revealed that the teachers evaluate their students’ linguistic proficiency on the basis of the students’ utterances, but also informed by their non-verbal communication abilities. This led to the idea that competency for understanding others’ minds through the use of physical movement or bodily senses in communication in L1 – to sympathize with others – can be transferred to that same competency in communication in L2. Based on the specification of linguistic proficiency that L1 and L2 have in common, a cross-curriculum of L1 and L2 was developed in Step 2. In Step 3, can-do statements based on the curriculum were also formed, building off of the action-oriented approach from the Common European Framework of Reference for Languages (CEFR) used in Europe. A self-evaluation questionnaire consisting of the main can-do statements was given to the students between 3^rd grade and 6^th grade at the beginning of the school year (Step 4 and Step 5), and all teachers gave L1 and L2 instruction based on the curriculum to the students for one year (Step 6). The same questionnaire was given to the students at the beginning of the next school year (Step 7). The results of statistical analysis proved the enhancement of the students’ linguistic proficiency. This verified the validity of developing the cross-curriculum of L1 and L2 and adapting it in elementary school. It was concluded that elementary school students do not distinguish between L1 and L2, and that they just try to understand others’ minds through physical movement or senses in any language.

Keywords: cross curriculum of L1 and L2, elementary school education, language proficiency, sympathy with others

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Authors: Ahmad Khoirul Umam

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This paper investigates the role of vested interests and its impacts on anti-corruption agenda in Indonesia following the collapse of authoritarian regime in 1998. A pervasive and rampant corruption has been believed as the main cause of the state economy’s fragility. Hence, anti-corruption measures were implemented by applying democratization and market liberalization since the establishment of a consolidated democracy which go hand in hand with a liberal market economy is convinced to be an efficacious prescription for effective anti-corruption. The reform movement has also mandated the establishment of the independent, neutral and professional special anti-corruption agency namely Corruption Eradication Commission (KPK) to more intensify the fight against the systemic corruption. This paper will examine whether these anti-corruption measures have been effective to combat corruption, and investigate to what extend have the anti-corruption efforts, especially those conducted by KPK, been impeded by the emergence of a nexus of vested interests as the side-effect of democratization and market liberalization. Based on interviews with key stakeholders from KPK, other law enforcement agencies, government, prominent scholars, journalists and NGOs in Indonesia, it is found that since the overthrow of Soeharto, anti-corruption movement in the country have become more active and serious. After gradually winning the hearth of people, KPK successfully touched the untouchable corruption perpetrators who were previously protected by political immunity, legal protection and bureaucratic barriers. However, these changes have not necessarily reduced systemic and structural corruption practices. Ironically, intensive and devastating counterattacks were frequently posed by the alignment of business actors, elites of political parties, government, and also law enforcement agencies by hijacking state’s instruments to make KPK deflated, powerless, and surrender. This paper concludes that attempts of democratization, market liberalization and the establishment of anti-corruption agency may have helped Indonesia to reduce corruption. However, it is still difficult to imply that such anti-corruption measures have fostered the more effective anti-corruption works in the newly democratized and weakly regulated liberal economic system.

Keywords: vested interests, democratization, market liberalization, anti-corruption, Indonesia

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Authors: Apkar Salatian

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To relieve the burden of reasoning on a point to point basis, in many domains there is a need to reduce large and noisy data sets into trends for qualitative reasoning. In this paper we propose and describe a new architectural design pattern called REDUCER for reducing large and noisy data sets that can be tailored for particular situations. REDUCER consists of 2 consecutive processes: Filter which takes the original data and removes outliers, inconsistencies or noise; and Compression which takes the filtered data and derives trends in the data. In this seminal article, we also show how REDUCER has successfully been applied to 3 different case studies.

Keywords: design pattern, filtering, compression, architectural design

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Authors: Mario M. Figueroa de la Cruz, Claudia I. Solorzano, Raul Acosta, Ignacio Funes

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This technological development project seeks to create a tool that allows companies, in need of implementing a Data Center, intelligently determining factors for allocating resources support cooling and power supply (UPS) in its conception. The results should show clearly the speed, robustness and reliability of a system designed for deployment in environments where they must manage and protect large volumes of data.

Keywords: telecommunications, data center, fuzzy logic, expert systems

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Authors: Amy Gooden, Meshandren Naidoo

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Genetic research is not confined to a particular jurisdiction. Using direct-to-consumer genetic testing (DTC-GT) as an example, this research assesses the status of data sharing into and out of South Africa (SA). While SA laws cover the sending of genetic data out of SA, prohibiting such transfer unless a legal ground exists, the position where genetic data comes into the country depends on the laws of the country from where it is sent – making the legal position less clear.

Keywords: cross-border, data, genetic testing, law, regulation, research, sharing, South Africa

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Authors: Rolando Volzone

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The Congregation of Saint Paul of Serra de Ossa (Ossa Mountain) was founded in 1482, originated by the eremitic movement of the homens da pobre vida (poor life men), which is documented since 1366. The community of hermits expanded up to the first half of the 15th century, mostly in southern Portugal in the Alentejo region. In 1578, following a process of institutionalization led by the Church, an autonomous congregation was set up, affiliated in the Hungarian Order of Saint Paul the First Hermit, until 1834, when the decree of dissolution of the religious orders disbanded all the convents and monasteries in Portugal. The architectural evidences that reached our days as a legacy of the hermitical movement in Serra de Ossa, although studied and analysed from an historical point of view, are still little known with respect to the architectural characteristics of its physical implantation and its relationship with the natural systems. This research intends to expose the appropriation process of the locus eremus as a starting point for the interpretation of this landscape, evidencing the close relationship between the religious experience and the physical space chosen to reach the perfection of the soul. The locus eremus is thus determined not only by practical aspects such as the absolute and relative location, orography, existence of water resources, or the King’s favoring to the religious and settlement action of the hermits, but also by spiritual aspects related to the symbolism of the physical elements present and the solitary walk of these men. These aspects, combined with the built architectural elements and other exerted human action, may be fertile ground for the definition of a hypothetical hermitical landscape based on the sufficiently distinctive characteristics that sustain it. The landscape built by these hermits is established as a cultural and material heritage, and its preservation is of utmost importance. They deeply understood this place and took advantage of its natural resources, manipulating them in an ecological and economically sustainable way, respecting the place, without overcoming its own genius loci but becoming part of it.

Keywords: architecture, congregation of Saint Paul of Serra de Ossa, heremitical landscape, locus eremus

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Authors: Alexis D'Agostino, Amanda Pomeroy

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Background: Resource availability is essential to effective implementation of national nutrition policies. To this end, the SPRING Project has collected and analyzed budget data from government ministries in Uganda, international donors, and other nutrition implementers to provide data for the first time on what funding is actually allocated to implement nutrition activities named in the national nutrition plan. Methodology: USAID’s SPRING Project used the Uganda Nutrition Action Plan (UNAP) as the starting point for budget analysis. Thorough desk reviews of public budgets from government, donors, and NGOs were mapped to activities named in the UNAP and validated by key informants (KIs) across the stakeholder groups. By relying on nationally-recognized and locally-created documents, SPRING provided a familiar basis for discussions to increase credibility and local ownership of findings. Among other things, the KIs validated the amount, source, and type (specific or sensitive) of funding. When only high-level budget data were available, KIs provided rough estimates of the percentage of allocations that were actually nutrition-relevant, allowing creation of confidence intervals around some funding estimates. Results: After validating data and narrowing in on estimates of funding to nutrition-relevant programming, researchers applied a formula to estimate overall nutrition allocations. In line with guidance by the SUN Movement and its three-step process, nutrition-specific funding was counted at 100% of its allocation amount, while nutrition sensitive funding was counted at 25%. The vast majority of nutrition funding in Uganda is off-budget, with over 90 percent of all nutrition funding is provided outside of the government system. Overall allocations are split nearly evenly between nutrition-specific and –sensitive activities. In FY 2013/14, the two-year study’s baseline year, on- and off-budget funding for nutrition was estimated to be around 60 million USD. While the 60 million USD allocations compare favorably to the 66 million USD estimate of the cost of the UNAP, not all activities are sufficiently funded. Those activities with a focus on behavior change were the most underfunded. In addition, accompanying qualitative research suggested that donor funding for nutrition activities may shift government funding into other areas of work, making it difficult to estimate the sustainability of current nutrition investments.Conclusions: Beyond providing figures, these estimates can be used together with the qualitative results of the study to explain how and why these amounts were allocated for particular activities and not others, examine the negotiation process that occurred, and suggest options for improving the flow of finances to UNAP activities for the remainder of the policy tenure. By the end of the PBN study, several years of nutrition budget estimates will be available to compare changes in funding over time. Halfway through SPRING’s work, there is evidence that country stakeholders have begun to feel ownership over the ultimate findings and some ministries are requesting increased technical assistance in nutrition budgeting. Ultimately, these data can be used within organization to advocate for more and improved nutrition funding and to improve targeting of nutrition allocations.

Keywords: budget, nutrition, financing, scale-up

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Authors: Baris Can Yalcin

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Motion sensors have been commonly used as a valuable component in mechatronic systems, however, many mechatronic designs and applications that need motion sensors cost enormous amount of money, especially high-tech systems. Design of a software for communication protocol between data acquisition card and motion sensor is another issue that has to be solved. This study presents how to design a low cost motion data acquisition setup consisting of MPU 6050 motion sensor (gyro and accelerometer in 3 axes) and Arduino Mega2560 microcontroller. Design parameters are calibration of the sensor, identification and communication between sensor and data acquisition card, interpretation of data collected by the sensor.

Keywords: design, mechatronics, motion sensor, data acquisition

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Authors: V. K. Srivastava

Abstract:

Graphene has recently attracted an increasing attention in nanocomposites applications because it has 200 times greater strength than steel, making it the strongest material ever tested. Graphene, as the fundamental two-dimensional (2D) carbon structure with exceptionally high crystal and electronic quality, has emerged as a rapidly rising star in the field of material science. Graphene, as defined, as a 2D crystal, is composed of monolayers of carbon atoms arranged in a honeycombed network with six-membered rings, which is the interest of both theoretical and experimental researchers worldwide. The name comes from graphite and alkene. Graphite itself consists of many graphite-sheets stacked together by weak van der Waals forces. This is attributed to the monolayer of carbon atoms densely packed into honeycomb structure. Due to superior inherent properties of graphene nanoplatelets (GnP) over other nanofillers, GnP particles were added in epoxy resin with the variation of weight percentage. It is indicated that the DMA results of storage modulus, loss modulus and tan δ, defined as the ratio of elastic modulus and imaginary (loss) modulus versus temperature were affected with addition of GnP in the epoxy resin. In epoxy resin, damping (tan δ) is usually caused by movement of the molecular chain. The tan δ of the graphene nanoplatelets/epoxy resin composite is much lower than that of epoxy resin alone. This finding suggests that addition of graphene nanoplatelets effectively impedes movement of the molecular chain. The decrease in storage modulus can be interpreted by an increasing susceptibility to agglomeration, leading to less energy dissipation in the system under viscoelastic deformation. The results indicates the tan δ increased with the increase of temperature, which confirms that tan δ is associated with magnetic field strength. Also, the results show that the nanohardness increases with increase of elastic modulus marginally. GnP filled epoxy resin gives higher value than the epoxy resin, because GnP improves the mechanical properties of epoxy resin. Debonding of GnP is clearly observed in the micrograph having agglomeration of fillers and inhomogeneous distribution. Therefore, DMA and nanohardness studies indiacte that the elastic modulus of epoxy resin is increased with the addition of GnP fillers.

Keywords: agglomeration, elastic modulus, epoxy resin, graphene nanoplatelet, loss modulus, nanohardness, storage modulus

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