Search results for: data driven decision making

Authors: D. Prangchumpol

Abstract:

This research presents a forecasting method of requisition document demands for Military units by using Exponential Smoothing methods to analyze data. The data used in the forecast is an actual data requisition document of The Adjutant General Department. The results of the forecasting model to forecast the requisition of the document found that Holt–Winters’ trend and seasonality method of α=0.1, β=0, γ=0 is appropriate and matches for requisition of documents. In addition, the researcher has developed a requisition online system to improve the performance of requisition documents of The Adjutant General Department, and also ensuring that the operation can be checked.

Keywords: requisition, holt–winters, time series, royal thai army

Procedia PDF Downloads 312

Authors: A. W. J. Wong, I. H. Ibrahim

Abstract:

Increasing urbanisation has driven building designers to incorporate natural ventilation in the designs of sustainable buildings. This project utilises Computational Fluid Dynamics (CFD) to investigate the natural ventilation of an academic building, SIT@SP, using an assessment criterion based on daily mean temperature and mean velocity. The areas of interest are the pedestrian level of first and fourth levels of the building. A reference case recommended by the Architectural Institute of Japan was used to validate the simulation model. The validated simulation model was then used for coupled simulations on SIT@SP and neighbouring geometries, under two wind speeds. Both steady and transient simulations were used to identify differences in results. Steady and transient results are agreeable with the transient simulation identifying peak velocities during flow development. Under a lower wind speed, the first level was sufficiently ventilated while the fourth level was not. The first level has excessive wind velocities in the higher wind speed and the fourth level was adequately ventilated. Fourth level flow velocity was consistently lower than those of the first level. This is attributed to either simulation model error or poor building design. SIT@SP is concluded to have a sufficiently ventilated first level and insufficiently ventilated fourth level. Future works for this project extend to modifying the urban geometry, simulation model improvements, evaluation using other assessment metrics and extending the area of interest to the entire building.

Keywords: buildings, CFD Simulations, natural ventilation, urban airflow

Procedia PDF Downloads 224

Authors: Peter Schnell, Phillip Haag

Abstract:

In the course of the structural transformation of the construction industry, the integration of industrialization and digitization has led to the development of construction methods with an increased degree of prefabrication, such as system or modular construction. Compared to conventional construction, these innovative construction methods are characterized by modified structural and procedural properties and expand the range of construction services. Faced with the supply side, it is possible to identify construction-specific customer types with different characteristics and certain preferences as far as the choice of construction method is concerned. The basis for this finding was qualitative expert interviews. By evaluating the stereotypical customer needs, a corresponding segmentation of the demand side can be made along with the basic orientation and decision behavior. This demarcation supports the target- and needs-oriented customer approach and contributes to cooperative and successful project management.

Keywords: differentiation of customer types, modular construction methods, conventional construction methods, stereotypical customer types

Procedia PDF Downloads 114

Authors: George Hadjinicola, Andreas Soteriou

Abstract:

This paper examines the relationship between the number of price promotions that a firm should conduct per year and the level of safety stocks that the firm should maintain. Price promotions result in temporary sales increases, which affect the operations function through (1) an increase in the quantities demanded and (2) an increase in safety stocks required to maintain the desired service level. We propose a modeling framework where both price promotions and improved service levels, operationalized through higher safety stocks, can affect sales. We treat the annual number of promotions as a decision variable. We identify market conditions where the operations function, through improved safety stocks, can complement price promotions or even play the leading role in sales increases.

Keywords: price promotions, safety stocks, marketing/operations interface, mathematical model

Procedia PDF Downloads 101

Authors: Ibrahim Mohammed, Suleiman Taofiq, Muhammad Naziru Yahya

Abstract:

Geoelectrical measurements using Schlumberger Vertical Electrical Sounding (VES) method were carried out in Waziri Umaru Federal Polytechnic, Birnin Kebbi, Nigeria, with the aim of determining the groundwater potential in the area. Twelve (12) Vertical Electric Sounding (VES) data were collected using Terrameter (ABEM SAS 300c) and analyzed using computer software (IPI2win), which gives an automatic interpretation of the apparent resistivity. The results of the interpretation of VES data were used in the characterization of three to five geo-electric layers from which the aquifer units were delineated. Data analysis indicated that water bearing formation exists in the third and fourth layers having resistivity range of 312 to 767 Ωm and 9.51 to 681 Ωm, respectively. The thickness of the formation ranges from 14.7 to 41.8 m, while the depth is from 8.22 to 53.7 m. Based on the result obtained from the interpretation of the data, five (5) VES stations were recommended as the most viable locations for groundwater exploration in the study area. The VES stations include VES A4, A5, A6, B1, and B2. The VES results of the entire area indicated that the water bearing formation occurs at maximum depth of 53.7 m at the time of this survey.

Keywords: aquifer, depth, groundwater, resistivity, Schlumberger

Procedia PDF Downloads 170

Authors: Kim Anema, Matthias Max, Chris Zevenbergen

Abstract:

For any flood risk manager the 'safety paradox' has to be a familiar concept: low probability leads to a sense of safety, which leads to more investments in the area, which leads to higher potential consequences: keeping the aggregated risk (probability*consequences) at the same level. Therefore, it is important to mitigate potential consequences apart from probability. However, when the (perceived) probability is so low that there is no recognizable trend for society to adapt to, addressing the potential consequences will always be the lagging point on the agenda. Preparedness programs fail because of lack of interest and urgency, policy makers are distracted by their day to day business and there's always a more urgent issue to spend the taxpayer's money on. The leading question in this study was how to address the social consequences of flooding in a context of (perceived) low probability. Disruptions of everyday urban life, large or small, can be caused by a variety of (un)expected things - of which flooding is only one possibility. Variability like this is typically addressed with resilience - and we used the concept of Community Resilience as the framework for this study. Drawing on face to face interviews, an extensive questionnaire and publicly available statistical data we explored the 'whole society response' to two recent urban flood events; the Brisbane Floods (AUS) in 2011 and the Dresden Floods (GE) in 2013. In Brisbane, we studied how the societal impacts of the floods were counteracted by both authorities and the public, and in Dresden we were able to validate our findings. A large part of the reactions, both public as institutional, to these two urban flood events were not fuelled by preparedness or proper planning. Instead, more important success factors in counteracting social impacts like demographic changes in neighborhoods and (non-)economic losses were dynamics like community action, flexibility and creativity from authorities, leadership, informal connections and a shared narrative. These proved to be the determining factors for the quality and speed of recovery in both cities. The resilience of the community in Brisbane was good, due to (i) the approachability of (local) authorities, (ii) a big group of ‘secondary victims’ and (iii) clear leadership. All three of these elements were amplified by the use of social media and/ or web 2.0 by both the communities and the authorities involved. The numerous contacts and social connections made through the web were fast, need driven and, in their own way, orderly. Similarly in Dresden large groups of 'unprepared', ad hoc organized citizens managed to work together with authorities in a way that was effective and speeded up recovery. The concept of community resilience is better fitted than 'social adaptation' to deal with the potential consequences of an (im)probable flood. Community resilience is built on capacities and dynamics that are part of everyday life and which can be invested in pre-event to minimize the social impact of urban flooding. Investing in these might even have beneficial trade-offs in other policy fields.

Keywords: community resilience, disaster response, social consequences, preparedness

Procedia PDF Downloads 354

Authors: Ruanzhenghao Shi

Abstract:

Student movements have persisted in mainland China, especially in elite universities since the Tiananmen Prodemocracy Movement, contrary to the lack of studies on them. However, the participants' repertoire, mobilization and mode of interaction with authorities are vastly different from their predecessors in the 1980s as well as their western counterparts. In most of the cases, agents, cognizant of the high cost of action and their vulnerability to the authorities, consciously curtailed certain repertoire and themes of resistance. Thus these movements, without appreciable organized force, were self-interested, fragmentally mobilized, lowly integrated and limited within the campus. This study documents the 2014 protest against Yanching Academy program at Peking University, a top-tier Chinese university that played the leading role in the 1989 protest. The 2014 case is different from abovementioned trend of submissive resistance in the last twenty years, insofar as it is a value-oriented and emotion-driven collective action with the resurgence of some repertoire. The participants perceived the university's contemporary ineffectiveness and clumsiness in control and administration, higher Party authorities' indifference to less-political themes, and an increasing number of potential advocates, including students, intellectuals and social media. It shows that resisters' perception of their relative strength to their opponents - in this case, the university and its system for controlling students - under specific circumstances, not merely political opportunities or institutional changes, stimulates the participants and thus contributes to the mobilization and organization of a collective action, even under severe social control.

Keywords: collective action, China, university students, resistance

Procedia PDF Downloads 154

Authors: Dalvin D. Hill, Hector M. Castro Garcia

Abstract:

A growing number of individuals utilize wearable devices on a daily basis. The usage and functionality of these wearable devices vary from user to user. One popular usage of said devices is to track health-related activities that are typically stored on a device’s memory or uploaded to an account in the cloud; based on the current trend, the data accumulated from the wearable device are stored in a standalone location. In many of these cases, this health related datum is not a factor when considering the holistic view of a user’s health lifestyle or record. This health-related data generated from wearable and Internet of Things (IoT) devices can serve as empirical information to a medical provider, as the standalone data can add value to the holistic health record of a patient. This paper proposes a solution to incorporate the data gathered from these wearable and IoT devices, with that a patient’s Personal Health Record (PHR) stored within the confines of a Health Information Exchange (HIE).

Keywords: electronic health record, health information exchanges, internet of things, personal health records, wearable devices, wearables

Procedia PDF Downloads 133

Authors: Chao Yu, Qing-Guo Wang, Dan Zhang

Abstract:

The outlier detection problem for dynamic systems is formulated as a matrix decomposition problem with low-rank, sparse matrices and further recast as a semidefinite programming (SDP) problem. A fast algorithm is presented to solve the resulting problem while keeping the solution matrix structure and it can greatly reduce the computational cost over the standard interior-point method. The computational burden is further reduced by proper construction of subsets of the raw data without violating low rank property of the involved matrix. The proposed method can make exact detection of outliers in case of no or little noise in output observations. In case of significant noise, a novel approach based on under-sampling with averaging is developed to denoise while retaining the saliency of outliers and so-filtered data enables successful outlier detection with the proposed method while the existing filtering methods fail. Use of recovered “clean” data from the proposed method can give much better parameter estimation compared with that based on the raw data.

Keywords: outlier detection, system identification, matrix decomposition, low-rank matrix, sparsity, semidefinite programming, interior-point methods, denoising

Procedia PDF Downloads 311

Authors: Walter Bernhofer, Peter Haber, Tobias Mayer, Manfred Mayr, Markus Ziegler

Abstract:

Current preventive maintenance measures are cost intensive and not efficient. With the available sensor data of state of the art internet of things devices new possibilities of automated data processing emerge. Current advances in data science and in machine learning enable new, so called predictive maintenance technologies, which empower data scientists to forecast possible system failures. The goal of this approach is to cut expenses in preventive maintenance by automating the detection of possible failures and to improve efficiency and quality of maintenance measures. Additionally, a centralization of the sensor data monitoring can be achieved by using this approach. This paper describes the approach of three students to define a reference architecture for a predictive maintenance solution in the internet of things domain with a connected smartphone app for service technicians. The reference architecture is validated by a case study. The case study is implemented with current Microsoft Azure cloud technologies. The results of the case study show that the reference architecture is valid and can be used to achieve a system for predictive maintenance execution with the cloud components of Microsoft Azure. The used concepts are technology platform agnostic and can be reused in many different cloud platforms. The reference architecture is valid and can be used in many use cases, like gas station maintenance, elevator maintenance and many more.

Keywords: case study, internet of things, predictive maintenance, reference architecture

Procedia PDF Downloads 256

Authors: N. Dlamini, Mpumelelo G. Ndlela, Philisiwe Dlamini, Nicholus Kisyeri, Bhekizitha Sithole

Abstract:

Accessing health services during the COVID-19 pandemic have exacerbated scarcity to routine medication. To ensure continuous accessibility to services, Eswatini launched Community Health Commodities Distribution (CHCD). Eligible Antiretroviral Therapy(ART) stable clients (VL<1,000) and patients on Non-Communicable Disease (NCD) medications were attended at community pick up points (PUP) based on distance between clients’ residence and the public health facility. Services provided includes ART and Pre-Exposure prophylaxis (PrEP) refills and NCD drug refills). The number of community PUP was 14% higher than health facility visits. Among all medications and commodities distributed between April and October 2020 at the PUP, 64% were HIV-related (HIV rapid test, HIVST, VL test, PrEP meds), and 36% were NCD related. The rapid roll out of CHCD during COVID-19 pandemic reduced the risk of COVID-19 transmission to clients as travel to health facilities was eliminated. It Additionally increased access to commodities during COVID-19-driven lockdown, decongested health facilities, integrated model of care, and increase service coverage. It was also noted that CHCD added different curative and HIV related services based on client specific needs and availability of the commodities.

Keywords: community health commodities distribution, pick up points, antiretroviral therapy, pre-exposure prophylaxis

Procedia PDF Downloads 143

Authors: O. S. Omorogiuwa, E. J. Omozusi

Abstract:

The monitoring of spectrum usage and signal identification, using cognitive radio, is done to identify frequencies that are vacant for reuse. It has been established that ‘internet of things’ device uses secondary frequency which is free, thereby facing the challenge of interference from other users, where some primary frequencies are not being utilised. The design was done by analysing a specific frequency spectrum, checking if all the frequency stations that range from 87.5-108 MHz are presently being used in Benin City, Edo State, Nigeria. From the results, it was noticed that by using Software Defined Radio/Simulink, we were able to identify vacant frequencies in the range of frequency under consideration. Also, we were able to use the significance of energy detection threshold to reuse this vacant frequency spectrum, when the cognitive radio displays a zero output (that is decision H0), meaning that the channel is unoccupied. Hence, the analysis was able to find the spectrum hole and identify how it can be reused.

Keywords: spectrum, interference, telecommunication, cognitive radio, frequency

Procedia PDF Downloads 230

Authors: William Castillo, Hugo Viza, Arturo Vargas

Abstract:

The Pacific Alliance is a trade bloc that is composed of four emerging economies: Chile, Colombia, Peru, and Mexico. These economies have gained macroeconomic stability in the past decade and as a consequence present future economic progress. Under this positive scenario, international business firms have flourished. However, the literature in this region has been widely unexamined. Therefore, it is critical to fill this theoretical gap, especially considering that Latin America is starting to become a global player and it possesses a different institutional context than developed markets. This paper analyzes the effect of international entrepreneurial orientation and institutionalism on international performance, for the Pacific Alliance small-to-medium enterprises (SMEs). The literature considers international entrepreneurial orientation to be a powerful managerial capability – along the resource based view- that firms can leverage to obtain a satisfactory international performance. Thereby, obtaining a competitive advantage through the correct allocation of key resources to exploit the capabilities here involved. Entrepreneurial Orientation is defined around five factors: innovation, proactiveness, risk-taking, competitive aggressiveness, and autonomy. Nevertheless, the institutional environment – both local and foreign, adversely affects International Performance; this is especially the case for emerging markets with uncertain scenarios. In this way, the study analyzes an Entrepreneurial Orientation, key endogenous variable of international performance, and Institutionalism, an exogenous variable. The survey data consists of Pacific Alliance SMEs that have foreign operations in at least another country in the trade bloc. Findings are still in an ongoing research process. Later, the study will undertake a structural equation modeling (SEM) using the variance-based partial least square estimation procedure. The software that is going to be used is the SmartPLS. This research contributes to the theoretical discussion of a largely postponed topic: SMEs in Latin America, that has had limited academic research. Also, it has practical implication for decision-makers and policy-makers, providing insights into what is behind international performance.

Keywords: institutional theory, international entrepreneurial orientation, international performance, SMEs, Pacific Alliance

Procedia PDF Downloads 253

Authors: Hung Manh Nguyen, Duong Dai Nguyen

Abstract:

Objective: To evaluate the effects of Tai Chi exercise on cognitive performance of community-dwelling elderly in Vinh city, Vietnam. Design: A randomized controlled trial. Participants: One hundred and two subjected were recruited. Intervention: Subjects were divided randomly into two groups. Tai Chi group was assigned 6-months Tai Chi training. Control group was instructed to maintain their routine daily activities. Outcome measures: Trail Making Test (TMT) is primary outcome measure. Results: Participants in Tai Chi group reported significant improvement in TMT (part A) F(1, 71) = 78.37, p < .001, and in TMT (part B) F(1, 71)= 175.00, p < .001 in comparison with Control group. Conclusion: Tai Chi is beneficial to improve cognitive performance of the elderly.

Keywords: cognitive, elderly, Vietnam, Tai Chi

Procedia PDF Downloads 532

Authors: Judith Mwakalonge, Geophrey Mbatta, Saidi Siuhi, Gurcan Comert, Cuthbert Ruseruka

Abstract:

Transportation agencies worldwide continuously monitor their roads' conditions to minimize road maintenance costs and maintain public safety and rideability quality. Existing methods for carrying out road condition surveys involve manual observations of roads using standard survey forms done by qualified road condition surveyors or engineers either on foot or by vehicle. Automated road condition survey vehicles exist; however, they are very expensive since they require special vehicles equipped with sensors for data collection together with data processing and computing devices. The manual methods are expensive, time-consuming, infrequent, and can hardly provide real-time information for road conditions. This study contributes to this arena by utilizing built-in vehicle technologies, drones, and deep learning to automate road condition surveys while using low-cost technology. A single model is trained to capture flexible pavement distresses (Potholes, Rutting, Cracking, and raveling), thereby providing a more cost-effective and efficient road condition monitoring approach that can also provide real-time road conditions. Additionally, data fusion is employed to enhance the road condition assessment with data from vehicles and drones.

Keywords: road conditions, built-in vehicle technology, deep learning, drones

Procedia PDF Downloads 130

Authors: Thien Van Ngo

Abstract:

The engineering design process is a systematic approach to solving problems. It involves identifying a problem, brainstorming solutions, prototyping and testing solutions, and evaluating the results. The engineering design process can be used to teach students how to solve problems in a creative and innovative way. The research aim of this study was to investigate the effectiveness of using the engineering design process to enhance student learning outcomes in a physics course. A mixed research method was used in this study. The quantitative data were collected using a pretest-posttest control group design. The qualitative data were collected using semi-structured interviews. The sample was 150 first-year students in the Department of Mechanical Engineering Technology at Cao Thang Technical College in Vietnam in the 2022-2023 school year. The quantitative data were collected using a pretest-posttest control group design. The pretest was administered to both groups at the beginning of the study. The posttest was administered to both groups at the end of the study. The qualitative data were collected using semi-structured interviews with a sample of eight students in the experimental group. The interviews were conducted after the posttest. The quantitative data were analyzed using independent sample T-tests. The qualitative data were analyzed using thematic analysis. The quantitative data showed that students in the experimental group, who were taught using the engineering design process, had significantly higher post-test scores on physics problem-solving than students in the control group, who were taught using the conventional method. The qualitative data showed that students in the experimental group were more motivated and engaged in the learning process than students in the control group. Students in the experimental group also reported that they found the engineering design process to be a more effective way of learning physics. The findings of this study suggest that the engineering design process can be an effective way of enhancing student learning outcomes in physics courses. The engineering design process engages students in the learning process and helps them to develop problem-solving skills.

Keywords: engineering design process, problem-solving, learning outcome of physics, students’ physics competencies, deep learning

Procedia PDF Downloads 70

Authors: K. S. Poutanen, P. Dussort, A. Erkner, S. Fiszman, K. Karnik, M. Kristensen, C. F. M. Marsaux, S. Miquel-Kergoat, S. Pentikäinen, P. Putz, R. E. Steinert, J. Slavin, D. J. Mela

Abstract:

Dietary fiber (DF) intake has been associated with lower body weight or less weight gain. These effects are generally attributed to putative effects of DF on appetite. Many intervention studies have tested the effect of DFs on appetite-related measures, with inconsistent results. However, DF includes a wide category of different compounds with diverse chemical and physical characteristics, and correspondingly diverse effects in human digestion. Thus, inconsistent results between DF consumption and appetite are not surprising. The specific contribution of different compounds with varying physico-chemical properties to appetite control and the mediating mechanisms are not well characterized. This systematic review aimed to assess the influence of specific DF characteristics, including viscosity, gel forming capacity, fermentability, and molecular weight, on appetite-related outcomes in healthy humans. Medline and FSTA databases were searched for controlled human intervention trials, testing the effects of well-characterized DFs on subjective satiety/appetite or energy intake outcomes. Studies were included only if they reported: 1) fiber name and origin, and 2) data on viscosity, gelling properties, fermentability, or molecular weight of the DF materials tested. The search generated 3001 unique records, 322 of which were selected for further consideration from title and abstract screening. Of these, 149 were excluded due to insufficient fiber characterization and 124 for other reasons (not original article, not randomized controlled trial, or no appetite related outcome), leaving 49 papers meeting all the inclusion criteria, most of which reported results from acute testing (<1 day). The eligible 49 papers described 90 comparisons of DFs in foods, beverages or supplements. DF-containing material of interest was efficacious for at least one appetite-related outcome in 51/90 comparisons. Gel-forming DF sources were most consistently efficacious but there were no clear associations between viscosity, MW or fermentability and appetite-related outcomes. A considerable number of papers had to be excluded from the review due to shortcomings in fiber characterization. To build understanding about the impact of DF on satiety/appetite specifically there should be clear hypotheses about the mechanisms behind the proposed beneficial effect of DF material on appetite, and sufficient data about the DF properties relevant for the hypothesized mechanisms to justify clinical testing. The hypothesized mechanisms should also guide the decision about relevant duration of exposure in studies, i.e. are the effects expected to occur during acute time frame (related to stomach emptying, digestion rate, etc.) or develop from sustained exposure (gut fermentation mediated mechanisms). More consistent measurement methods and reporting of fiber specifications and characterization are needed to establish reliable structure-function relationships for DF and health outcomes.

Keywords: appetite, dietary fiber, physico-chemical properties, satiety

Procedia PDF Downloads 239

Authors: B. R. Shen, J. R. Wang, J. H. Yang, S. W. Chen, C. Shih, Y. Chiang, Y. F. Chang, Y. H. Huang

Abstract:

In this research, TRACE code with the interface code-SNAP was used to simulate and analyze the SBO (station blackout) accident which occurred in Maanshan PWR (pressurized water reactor) nuclear power plant (NPP). There are four main steps in this research. First, the SBO accident data of Maanshan NPP were collected. Second, the TRACE/SNAP model of Maanshan NPP was established by using these data. Third, this TRACE/SNAP model was used to perform the simulation and analysis of SBO accident. Finally, the simulation and analysis of SBO with mitigation equipments was performed. The analysis results of TRACE are consistent with the data of Maanshan NPP. The mitigation equipments of Maanshan can maintain the safety of Maanshan in the SBO according to the TRACE predictions.

Keywords: pressurized water reactor (PWR), TRACE, station blackout (SBO), Maanshan

Procedia PDF Downloads 197

Authors: Katharina Crepaz

Abstract:

Both minority rights and disability rights are relatively new fields for policy-making in a European context, and both are affected by the EU’s diversity mainstreaming approach, as well as by the non-discrimination legislation drafted at the European level. These processes correspond to the classic understanding of Europeanization, namely a “top-down” stream of influence from the European to the national and subnational levels. However, both minority and disability rights movements also show instances of “bottom-up” Europeanization, e.g. transnational advocacy networks and efforts to reach joint goals at the EU-level. This paper aims to provide a comparative perspective on Europeanization in both fields, pointing out similar dynamics and patterns, but also explaining in which sectors outcomes may be different and which domestic and other scope conditions may be responsible for these differences.

Keywords: europeanization, disability rights, minority rights, comparative perspective

Procedia PDF Downloads 419

Authors: Yuliya Leonidovna Kiva-Khamzina

Abstract:

The legal nature of the contract for educational services causes a lot of controversies. In particular, it raises the question about industry sector relationships, which require making a contract for educational services. The article describes the different types of contracts classifications for services provision from the perspective of civil law, deals with the specifics of the contract on rendering educational services; the author makes the conclusion that the contract for the provision of educational services is a complex institution that includes elements of the civil and administrative law. The following methods were used to conduct the study: dialectical method of cognition, the historical method, systemic analysis, classification.

Keywords: administrative aspect, civil aspect, educational service, industry, legal nature, services provision

Procedia PDF Downloads 326

Authors: Jojo Y. C. Mo

Abstract:

Memories are good. They remind us of people, places and experiences that we cherish. But memories cannot be changed and there may well be memories that we do not want to remember. This is particularly true in relation to information which causes us embarrassment and humiliation or simply because it is private – we all want to erase or delete such information. This desire to delete is recently recognised by the Court of Justice of the European Union in the 2014 case of Google Spain SL, Google Inc. v Agencia Española de Protección de Datos, Mario Costeja González in which the court ordered Google to remove links to some information about the complainant which he wished to be removed. This so-called ‘right to be forgotten’ received serious attention and significantly, the European Council and the European Parliament enacted the General Data Protection Regulation (GDPR) to provide a more structured and normative framework for implementation of right to be forgotten across the EU. This development in data protection laws will, undoubtedly, have significant impact on companies and co-operations not just within the EU but outside as well. Hong Kong, being one of the world’s leading financial and commercial center as well as one of the first jurisdictions in Asia to implement a comprehensive piece of data protection legislation, is therefore a jurisdiction that is worth looking into. This article/project aims to investigate the following: a) whether there is a right to be forgotten under the existing Hong Kong data protection legislation b) if not, whether such a provision is necessary and why. This article utilises a comparative methodology based on a study of primary and secondary resources, including scholarly articles, government and law commission reports and working papers and relevant international treaties, constitutional documents, case law and legislation. The author will primarily engage literature and case-law review as well as comparative and doctrinal analyses. The completion of this article will provide privacy researchers with more concrete principles and data to conduct further research on privacy and data protection in Hong Kong and internationally and will provide a basis for policy makers in assessing the rationale and need for a right to be forgotten in Hong Kong.

Keywords: privacy, right to be forgotten, data protection, Hong Kong

Procedia PDF Downloads 195

Authors: Harvey Sanchez-Restrepo, Jorge Louca

Abstract:

Equity and education are major focus of government policies around the world due to its relevance for addressing the sustainable development goals launched by Unesco. In this research, we developed a primary analysis of a data set of more than one hundred educational and non-educational factors associated with learning, coming from a census-based large-scale assessment carried on in Ecuador for 1.038.328 students, their families, teachers, and school directors, throughout 2014-2018. Each participating student was assessed by a standardized computer-based test. Learning outcomes were calibrated through item response theory with two-parameters logistic model for getting raw scores that were re-scaled and synthetized by a learning index (LI). Our objective was to develop a network for modelling educational deprivation and analyze the structure of inequality gaps, as well as their relationship with socioeconomic status, school financing, and student's ethnicity. Results from the model show that 348 270 students did not develop the minimum skills (prevalence rate=0.215) and that Afro-Ecuadorian, Montuvios and Indigenous students exhibited the highest prevalence with 0.312, 0.278 and 0.226, respectively. Regarding the socioeconomic status of students (SES), modularity class shows clearly that the system is out of equilibrium: the first decile (the poorest) exhibits a prevalence rate of 0.386 while rate for decile ten (the richest) is 0.080, showing an intense negative relationship between learning and SES given by R= –0.58 (p < 0.001). Another interesting and unexpected result is the average-weighted degree (426.9) for both private and public schools attending Afro-Ecuadorian students, groups that got the highest PageRank (0.426) and pointing out that they suffer the highest educational deprivation due to discrimination, even belonging to the richest decile. The model also found the factors which explain deprivation through the highest PageRank and the greatest degree of connectivity for the first decile, they are: financial bonus for attending school, computer access, internet access, number of children, living with at least one parent, books access, read books, phone access, time for homework, teachers arriving late, paid work, positive expectations about schooling, and mother education. These results provide very accurate and clear knowledge about the variables affecting poorest students and the inequalities that it produces, from which it might be defined needs profiles, as well as actions on the factors in which it is possible to influence. Finally, these results confirm that network analysis is fundamental for educational policy, especially linking reliable microdata with social macro-parameters because it allows us to infer how gaps in educational achievements are driven by students’ context at the time of assigning resources.

Keywords: complex network, educational deprivation, evidence-based policy, large-scale assessments, policy informatics

Procedia PDF Downloads 128

Authors: Hyeongju Jeon, Yonghyun Kim, Yongil Kim

Abstract:

Synthetic Aperture Radar (SAR) is an effective tool for damage assessment induced by disasters due to its all-weather and night/day acquisition capability. In this paper, the 2017 Colombia landslide was observed using full-polarimetric ALOS/PALSAR-2 data. Polarimetric decompositions, including the Freeman-Durden decomposition and the Cloude decomposition, are utilized to analyze the scattering mechanisms changes before and after-landslide. These analyses are used to detect the damaged areas induced by the landslide. Experimental results validate the efficiency of the full polarimetric SAR data since the damaged areas can be well discriminated. Thus, we can conclude the proposed method using full polarimetric data has great potential for damage assessment of landslides.

Keywords: Synthetic Aperture Radar (SAR), polarimetric decomposition, damage assessment, landslide

Procedia PDF Downloads 399

Authors: Sofia Stoica

Abstract:

In this paper, we use historical data to predict the stock price of a tech company. To this end, we use a dataset consisting of the stock prices in the past five years of ten major tech companies – Adobe, Amazon, Apple, Facebook, Google, Microsoft, Netflix, Oracle, Salesforce, and Tesla. We experimented with a variety of models– a linear regressor model, K nearest Neighbors (KNN), a sequential neural network – and algorithms - Multiplicative Weight Update, and AdaBoost. We found that the sequential neural network performed the best, with a testing error of 0.18%. Interestingly, the linear model performed the second best with a testing error of 0.73%. These results show that using historical data is enough to obtain high accuracies, and a simple algorithm like linear regression has a performance similar to more sophisticated models while taking less time and resources to implement.

Keywords: finance, machine learning, opening price, stock market

Procedia PDF Downloads 203

Authors: Jihen Bennaceur, Wissem Zouaghi, Ali Mabrouk

Abstract:

The major aim of cyber threat intelligence (CTI) is to provide sophisticated knowledge about cybersecurity threats to ensure internal and external safeguards against modern cyberattacks. Inaccurate, incomplete, outdated, and invaluable threat intelligence is the main problem. Therefore, data analysis based on AI algorithms is one of the emergent solutions to overcome the threat of information-sharing issues. In this paper, we propose a supervised machine learning-based algorithm to improve threat information sharing by providing a sophisticated classification of cyber threats and data. Extensive simulations investigate the accuracy, precision, recall, f1-score, and support overall to validate the designed algorithm and to compare it with several supervised machine learning algorithms.

Keywords: threat information sharing, supervised learning, data classification, performance evaluation

Procedia PDF Downloads 155

Authors: Tunjo Perič, Marin Fatović

Abstract:

In this paper a new methodology for vendor selection and supply quotas determination (VSSQD) is proposed. The problem of VSSQD is solved by the model that combines revised weighting method for determining the objective function coefficients, and a multiple objective linear programming (MOLP) method based on the cooperative game theory for VSSQD. The criteria used for VSSQD are: (1) purchase costs and (2) product quality supplied by individual vendors. The proposed methodology is tested on the example of flour purchase for a bakery with two decision makers.

Keywords: cooperative game theory, multiple objective linear programming, revised weighting method, vendor selection

Procedia PDF Downloads 362

Authors: Avadh Bihari

Abstract:

Corporate social responsibility (CSR) has become a global parameter to define corporates' ethical and responsible behaviour. It was a voluntary practice in India till 2013, driven by various guidelines, which has become a mandate since 2014 under the Companies Act, 2013. This has compelled the corporates to redesign their CSR strategies by bringing in structures, planning, accountability, and transparency in their processes with a mandate to 'comply or explain'. Based on the author's M.Phil. dissertation, this paper presents the changes in organisational practices and institutional mechanisms of third-sector organisations (TSOs) with the theoretical frameworks of institutionalism and co-optation. It became an interesting case as India is the only country to have a law on CSR, which is not only mandating the reporting but the spending too. The space of CSR in India is changing rapidly and affecting multiple institutions, in the context of the changing roles of the state, market, and TSOs. Several factors such as stringent regulation on foreign funding, mandatory CSR pushing corporates to look out for NGOs, and dependency of Indian NGOs on CSR funds have come to the fore almost simultaneously, which made it an important area of study. Further, the paper aims at addressing the gap in the literature on the effects of mandated CSR on the functioning of TSOs through the empirical and theoretical findings of this study. The author had adopted an interpretivist position in this study to explore changes in organisational practices from the participants' experiences. Data were collected through in-depth interviews with five corporate officials, eleven officials from six TSOs, and two academicians, located at Mumbai and Delhi, India. The findings of this study show the legislation has institutionalised CSR, and TSOs get co-opted in the process of implementing mandated CSR. Seventy percent of the corporates implement their CSR projects through TSOs in India; this has affected the organisational practices of TSOs to a large extent. They are compelled to recruit expert workforce, create new departments for monitoring & evaluation, communications, and adopt management practices of project implementation from corporates. These are attempts to institutionalise the TSOs so that they can produce calculated results as demanded by corporates. In this process, TSOs get co-opted in a struggle to secure funds and lose their autonomy. The normative, coercive, and mimetic isomorphisms of institutionalism come into play as corporates are mandated to take up CSR, thereby influencing the organisational practices of TSOs. These results suggest that corporates and TSOs require an understanding of each other's work culture to develop mutual respect and work towards the goal of sustainable development of the communities. Further, TSOs need to retain their autonomy and understanding of ground realities without which they become an extension of the corporate-funder. For a successful CSR project, engagement beyond funding is required from corporate, through their involvement and not interference. CSR-led community development can be structured by management practices to an extent, but cannot overshadow the knowledge and experience of TSOs.

Keywords: corporate social responsibility, institutionalism, organisational practices, third-sector organisations

Procedia PDF Downloads 119

Authors: Shilpa Khobragade, Carlos Da Silva Granja, Niklas Sandström, Igor Efimov, Victor P. Ostanin, Wouter van der Wijngaart, David Klenerman, Sourav K. Ghosh

Abstract:

Rapid, label-free and direct detection of pathogenic bacteria is critical for the prevention of disease outbreaks. This paper for the first time attempts to probe the nonlinear acoustic response of quartz crystal resonator (QCR) functionalized with specific DNA aptamers for direct detection and quantification of viable E. coli KCTC 2571 bacteria. DNA aptamers were immobilized through biotin and streptavidin conjugation, onto the gold surface of QCR to capture the target bacteria and the detection was accomplished by shift in amplitude of the peak 3f signal (3 times the drive frequency) upon binding, when driven near fundamental resonance frequency. The developed nonlinear acoustic aptasensor system demonstrated better reliability than conventional resonance frequency shift and energy dissipation monitoring that were recorded simultaneously. This sensing system could directly detect 10⁽⁵⁾ cells/mL target bacteria within 30 min or less and had high specificity towards E. coli KCTC 2571 bacteria as compared to the same concentration of S.typhi bacteria. Aptasensor response was observed for the bacterial suspensions ranging from 10⁽⁵⁾-10⁽⁸⁾ cells/mL. Conclusively, this nonlinear acoustic aptasensor is simple to use, gives real-time output, cost-effective and has the potential for rapid, specific, label-free direction detection of bacteria.

Keywords: acoustic, aptasensor, detection, nonlinear

Procedia PDF Downloads 571

Authors: Rita Chattopadhyay, Vivek Anand Thoutam

Abstract:

Speech is the most acceptable means of communication where we can quickly exchange our feelings and thoughts. Quite often, people can communicate orally but cannot interact or work with computers or devices. It’s easy and quick to give speech commands than typing commands to computers. In the same way, it’s easy listening to audio played from a device than extract output from computers or devices. Especially with Robotics being an emerging market with applications in warehouses, the hospitality industry, consumer electronics, assistive technology, etc., speech-based human-machine interaction is emerging as a lucrative feature for robot manufacturers. Considering this factor, the objective of this paper is to design the “Audio-Visual Co-Data Processing Pipeline.” This pipeline is an integrated version of Automatic speech recognition, a Natural language model for text understanding, object detection, and text-to-speech modules. There are many Deep Learning models for each type of the modules mentioned above, but OpenVINO Model Zoo models are used because the OpenVINO toolkit covers both computer vision and non-computer vision workloads across Intel hardware and maximizes performance, and accelerates application development. A speech command is given as input that has information about target objects to be detected and start and end times to extract the required interval from the video. Speech is converted to text using the Automatic speech recognition QuartzNet model. The summary is extracted from text using a natural language model Generative Pre-Trained Transformer-3 (GPT-3). Based on the summary, essential frames from the video are extracted, and the You Only Look Once (YOLO) object detection model detects You Only Look Once (YOLO) objects on these extracted frames. Frame numbers that have target objects (specified objects in the speech command) are saved as text. Finally, this text (frame numbers) is converted to speech using text to speech model and will be played from the device. This project is developed for 80 You Only Look Once (YOLO) labels, and the user can extract frames based on only one or two target labels. This pipeline can be extended for more than two target labels easily by making appropriate changes in the object detection module. This project is developed for four different speech command formats by including sample examples in the prompt used by Generative Pre-Trained Transformer-3 (GPT-3) model. Based on user preference, one can come up with a new speech command format by including some examples of the respective format in the prompt used by the Generative Pre-Trained Transformer-3 (GPT-3) model. This pipeline can be used in many projects like human-machine interface, human-robot interaction, and surveillance through speech commands. All object detection projects can be upgraded using this pipeline so that one can give speech commands and output is played from the device.

Keywords: OpenVINO, automatic speech recognition, natural language processing, object detection, text to speech

Procedia PDF Downloads 83

Authors: Thiago Spilborghs Bueno Meyer, Plinio Thomaz Aquino Junior

Abstract:

Through speech, which privileges the functional and interactive nature of the text, it is possible to ascertain the spatiotemporal circumstances, the conditions of production and reception of the discourse, the explicit purposes such as informing, explaining, convincing, etc. These conditions allow bringing the interaction between humans closer to the human-robot interaction, making it natural and sensitive to information. However, it is not enough to understand what is said; it is necessary to recognize emotions for the desired interaction. The validity of the use of neural networks for feature selection and emotion recognition was verified. For this purpose, it is proposed the use of neural networks and comparison of models, such as recurrent neural networks and deep neural networks, in order to carry out the classification of emotions through speech signals to verify the quality of recognition. It is expected to enable the implementation of robots in a domestic environment, such as the HERA robot from the RoboFEI@Home team, which focuses on autonomous service robots for the domestic environment. Tests were performed using only the Mel-Frequency Cepstral Coefficients, as well as tests with several characteristics of Delta-MFCC, spectral contrast, and the Mel spectrogram. To carry out the training, validation and testing of the neural networks, the eNTERFACE’05 database was used, which has 42 speakers from 14 different nationalities speaking the English language. The data from the chosen database are videos that, for use in neural networks, were converted into audios. It was found as a result, a classification of 51,969% of correct answers when using the deep neural network, when the use of the recurrent neural network was verified, with the classification with accuracy equal to 44.09%. The results are more accurate when only the Mel-Frequency Cepstral Coefficients are used for the classification, using the classifier with the deep neural network, and in only one case, it is possible to observe a greater accuracy by the recurrent neural network, which occurs in the use of various features and setting 73 for batch size and 100 training epochs.

Keywords: emotion recognition, speech, deep learning, human-robot interaction, neural networks

Procedia PDF Downloads 175