Search results for: regional data

Authors: Zhu Zhizheng, Huang Yong, Li Tong

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In the context of land and space development and resource environmental protection. Due to its special geographical location, mountain-plain transition zones are limited by many factors such as topography, mountain forest protection, etc., and their ecology is also more sensitive, with the characteristics of disaster susceptibility and resource gradient. Taking Dujiangyan City, Chengdu as an example, this paper establishes resilience evaluation indicators on the basis of ecological suitability evaluation through the analysis of current situation data and relevant policies: water conservation evaluation, soil and water conservation evaluation, biodiversity evaluation, soil erosion sensitivity evaluation, etc. Based on GIS spatial analysis, the ecological suitability and resilience evaluation results of Dujiangyan city were obtained by disjunction operation. The ecological resilience level of Dujiangyan city was divided into three categories: high, medium and low, with an area ratio of 50.81%, 16.4% and 32.79%, respectively. This paper can provide ideas for solving the contradiction between man and land in the mountain-plain transition zones, and also provide a certain basis for the construction of regional ecological protection and the delineation of three zones and three lines.

Keywords: urban and rural planning, ecological resilience, dujiangyan city, mountain-plain transition zones

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Authors: Nabil Saad, David Morgan, Manish Gupta

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Visibility has become a key component of air quality and is regulated in many areas by environmental laws such as the EPA Clean Air Act and Regional Haze Rule. Typically, visibility is calculated by estimating the optical absorption and scattering of both gases and aerosols. A major component of the aerosols’ climatic effect is due to their scattering and absorption of solar radiation, which are governed by their optical and physical properties. However, the accurate assessment of this effect on global warming, climate change, and air quality is made difficult due to uncertainties in the calculation of single scattering albedo (SSA). Experimental complications arise in the determination of the single scattering albedo of an aerosol particle since it requires the simultaneous measurement of both scattering and extinction. In fact, aerosol optical absorption, in particular, is a difficult measurement to perform, and it’s often associated with large uncertainties when using filter methods or difference methods. In this presentation, we demonstrate the use of a new open-path Optical Extinction Analyzer (OEA) in conjunction with a nephelometer and two particle sizers, emphasizing the benefits that co-employment of the OEA offers to derive the complex refractive index of aerosols and their single scattering albedo parameter. Various use cases, data reproducibility, and instrument calibration will also be presented to highlight the value proposition of this novel Open-Path OEA.

Keywords: aerosols, extinction, visibility, albedo

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Authors: James Hilton Williams

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Recent tsunami events, including the 2011 Tohoku Tsunami, Japan, and the 2015 Illapel Tsunami, Chile, have highlighted the potential for tsunami impacts on the built environment. International research in the tsunami impacts domain has been largely focused toward impacts on buildings and casualty estimations, while only limited attention has been placed on the impacts on infrastructure which is critical for the recovery of impacted communities. New Zealand, with 75% of the population within 10 km of the coast, has a large amount of coastal infrastructure exposed to local, regional and distant tsunami sources. To effectively manage tsunami risk for New Zealand critical infrastructure, including energy, transportation, and communications, the vulnerability of infrastructure networks and components must first be determined. This research develops infrastructure asset vulnerability, functionality and repair- cost functions based on international post-event tsunami impact assessment data from technologically similar countries, including Japan and Chile, and adapts these to New Zealand. These functions are then utilized within a New Zealand based impact framework, allowing for cost benefit analyses, effective tsunami risk management strategies and mitigation options for exposed critical infrastructure to be determined, which can also be applied internationally.

Keywords: impact assessment, infrastructure, tsunami impacts, vulnerability functions

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Authors: Ezeh Chukwunonso Peter Excel, Akruti Vg

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Aim/Background: To show that even after undergoing 1-5 courses of chemotherapy for Gestational Trophoblastic Disease (GTD) reproductive health of women is intact and they conceive successfully after it. Method: Retrospective cohort analysis using data from the Lugansk regional maternity hospital database of years 1993-2013, which shows n=18 females had GTD and underwent 1-5 courses of chemotherapy. Results and Discussion: Frequency of GTD was rare. All 18 patients (pts) belong to age group of 17-39 years, covering wide range of reproductive age. Out of 18 pts, 15 had hydatidiform mole (HM) while other 3 had choriocarcinoma (CC). In anamnesis, among CC pts, 1 had early pre-eclampsia at 24 weeks and 1 had 4th week of late postpartum (PP) bleeding, while all HM pts had genital inflammatory diseases, 1 pt of HM during follow-up had High hCG and 3 times curettage in 5 months. 18 women became pregnant for 25 times after chemotherapy. Chemotherapy was given under indication of either high level of HCG, luteal cyst >6cm or path-morphological results of curettage. CC 3 pts had (2 spontaneous abortions (SA), 2 term cesarean section (CS), 1 preterm CS). HM 15 pts had (3 artificial abortion, 2 SA, 7CS (5 term and 2 preterm), 8 vaginal deliveries (7 term and 1 preterm)). Conclusion: During our research we got 22.2% preterm deliveries and 55.6% CS which is higher than the normal cases, but still all the 18 women were able to have kids successfully after chemotherapy. So we can conclude that chemotherapy for GTD was successful in keeping the reproductive health of women intact.

Keywords: reproductive health, chemotherapy, gestational trophoblastic disease, women

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Authors: Djamila Benhaddouche, Abdelkader Benyettou

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In this paper, we used data mining to extract biomedical knowledge. In general, complex biomedical data collected in studies of populations are treated by statistical methods, although they are robust, they are not sufficient in themselves to harness the potential wealth of data. For that you used in step two learning algorithms: the Decision Trees and Support Vector Machine (SVM). These supervised classification methods are used to make the diagnosis of thyroid disease. In this context, we propose to promote the study and use of symbolic data mining techniques.

Keywords: biomedical data, learning, classifier, algorithms decision tree, knowledge extraction

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Authors: Tatiana G. Smirnova, Stan G. Benjamin

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Rapid Update Cycle (RUC) land surface model (LSM) was a land-surface component in several generations of operational weather prediction models at the National Center for Environment Prediction (NCEP) at the National Oceanic and Atmospheric Administration (NOAA). It was designed for short-range weather predictions with an emphasis on severe weather and originally was intentionally simple to avoid uncertainties from poorly known parameters. Nevertheless, the RUC LSM, when coupled with the hourly-assimilating atmospheric model, can produce a realistic evolution of time-varying soil moisture and temperature, as well as the evolution of snow cover on the ground surface. This result is possible only if the soil/vegetation/snow component of the coupled weather prediction model has sufficient skill to avoid long-term drift. RUC LSM was first implemented in the operational NCEP Rapid Update Cycle (RUC) weather model in 1998 and later in the Weather Research Forecasting Model (WRF)-based Rapid Refresh (RAP) and High-resolution Rapid Refresh (HRRR). Being available to the international WRF community, it was implemented in operational weather models in Austria, New Zealand, and Switzerland. Based on the feedback from the US weather service offices and the international WRF community and also based on our own validation, RUC LSM has matured over the years. Also, a sea-ice module was added to RUC LSM for surface predictions over the Arctic sea-ice. Other modifications include refinements to the snow model and a more accurate specification of albedo, roughness length, and other surface properties. At present, RUC LSM is being tested in the regional application of the Unified Forecast System (UFS). The next generation UFS-based regional Rapid Refresh FV3 Standalone (RRFS) model will replace operational RAP and HRRR at NCEP. Over time, RUC LSM participated in several international model intercomparison projects to verify its skill using observed atmospheric forcing. The ESM-SnowMIP was the last of these experiments focused on the verification of snow models for open and forested regions. The simulations were performed for ten sites located in different climatic zones of the world forced with observed atmospheric conditions. While most of the 26 participating models have more sophisticated snow parameterizations than in RUC, RUC LSM got a high ranking in simulations of both snow water equivalent and surface temperature. However, ESM-SnowMIP experiment also revealed some issues in the RUC snow model, which will be addressed in this paper. One of them is the treatment of grid cells partially covered with snow. RUC snow module computes energy and moisture budgets of snow-covered and snow-free areas separately by aggregating the solutions at the end of each time step. Such treatment elevates the importance of computing in the model snow cover fraction. Improvements to the original simplistic threshold-based approach have been implemented and tested both offline and in the coupled weather model. The detailed description of changes to the snow cover fraction and other modifications to RUC soil and snow parameterizations will be described in this paper.

Keywords: land-surface models, weather prediction, hydrology, boundary-layer processes

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Authors: Usama Ahmed

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Data mining is the process of analyze data which are used to predict helpful information. It is the field of research which solve various type of problem. In data mining, classification is an important technique to classify different kind of data. Diabetes is most common disease. This paper implements different classification technique using Waikato Environment for Knowledge Analysis (WEKA) on diabetes dataset and find which algorithm is suitable for working. The best classification algorithm based on diabetic data is Naïve Bayes. The accuracy of Naïve Bayes is 76.31% and take 0.06 seconds to build the model.

Keywords: data mining, classification, diabetes, WEKA

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Authors: Asifa Amara, Prachi Singh, Kanishka, Debargho Pathak, Akshat Kumar, Jayakumar Eravelly

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Today's generation is totally dependent on technology that uses data as its fuel. The present study is all about innovations and developments in data science and gives an idea about how efficiently to use the data provided. This study will help to understand the core concepts of data science. The concept of artificial intelligence was introduced by Alan Turing in which the main principle was to create an artificial system that can run independently of human-given programs and can function with the help of analyzing data to understand the requirements of the users. Data science comprises business understanding, analyzing data, ethical concerns, understanding programming languages, various fields and sources of data, skills, etc. The usage of data science has evolved over the years. In this review article, we have covered a part of data science, i.e., machine learning. Machine learning uses data science for its work. Machines learn through their experience, which helps them to do any work more efficiently. This article includes a comparative study image between human understanding and machine understanding, advantages, applications, and real-time examples of machine learning. Data science is an important game changer in the life of human beings. Since the advent of data science, we have found its benefits and how it leads to a better understanding of people, and how it cherishes individual needs. It has improved business strategies, services provided by them, forecasting, the ability to attend sustainable developments, etc. This study also focuses on a better understanding of data science which will help us to create a better world.

Keywords: data science, machine learning, data analytics, artificial intelligence

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Authors: Maryam Khalili, Fateme Ghanei

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As one of the most significant phenomena of industrialized societies, tourism plays a key role in encouraging regional developments and enhancing higher standards of living for local communities in particular. Traveling is a formative experience endowed with lessons on various aspects of life. It allows us learning how to enhance the social position as well as the social relationships. However, people forget the need to travel and gain first-hand experiences as they have to cope with the ever-increasing rate of stress created by the disorders and routines of the urban dwelling style. In this paper, various spaces of such experiences were explored through a virtual tour with two underlying aims: 1) encouraging, informing, and educating the community in terms of tourism development, and 2) introducing a temporary release from the routines. This study enjoyed a practical-qualitative research methodology, and the required data were collected through observation and using a multiple-response questionnaire. The participants (19-48 years old) included 41 citizens of both genders (63.4% male and 36.6% female) from two regions in Tehran, selected by cluster-probability sampling. The results led to development of a spatial design for a virtual tour experience in Tehran where different areas are explored to both raise people’s awareness and educate them on their cultural heritage.

Keywords: ecotourism, education, gamification, social interaction, urban design, virtual tour

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Authors: Arundhati Devi Maibam, K. Ingocha Singh

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Cervical cancer is preventable if detected early. Determination of risk factors is essential to plan screening programmes to prevent the disease. To study the demographic risk factors of cervical cancer among Manipuri women, information on age, marital status, educational level, monthly family income and socioeconomic status were collected through a pre-tested interview schedule. In this study, 64 incident cases registered at the RT Dept, RIMS (Regional Institute of Medical Sciences), Imphal, Manipur, India during 2008-09 participated. Data were entered in Microsoft Excel and the results were expressed in percentages. Among the 64 patients with cervical cancer, 56 (88.9%) were in the age group of 40+ years. The majority of the patients were from rural areas (68.75%) and 31.25% were from urban areas. The majority of the patients were Hindus (73%), 55(85.9%) were of low educational level, 43(67.2%) were married, and 36 (56.25%) belonged to Class IV socioeconomic status. In conclusion, if detected early, cervical cancer is preventable and curable. The potential risk factors need to be identified and women in the risk group need to be motivated for screening. Affordable screening programmes and health care resources will help in lessening the burden of the disease.

Keywords: cervical cancer, Manipuri women, RIIMS, socio-demographic risk factors

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Authors: Jiraporn Weenuttranon

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The ASEAN Economic Community (AEC) shall be the goal of regional economic integration among ASEAN countries. The goal of establishing AEC is to transform the region into a single market and production base with a highly competitive advantage to make it a stable and prosperous region. However, with the wild range of economic conditions in each country, the implementation of its objectives under the limited resources available in the past showed the weakness of the region. For this reason, the group of countries in the region should allocate its rich potential of the region by collaborating effectively.

Keywords: impact, AEC, influence, direction, politics, Thailand

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Authors: Jang-Hwan Jo

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The supply management of ecosystem services of local forests is an essential issue as it is linked to the ecological welfare of local residents. This study aims to estimate the supply, trade-offs, and synergies of local forest regulating ecosystem services using a land cover classification map (LCCM) and a forest types map (FTM). Rigorous literature reviews and Expert Delphi analysis were conducted using the detailed variables of 1:5,000 LCCM and FTM. Land-use scoring method and Getis-Ord Gi* Analysis were utilized on detailed variables to propose a method for estimating supply, trade-offs, and synergies of the local forest regulating ecosystem services. The analysis revealed that the rank order (1st to 5th) of supply of regulating ecosystem services was Erosion prevention, Air quality regulation, Heat island mitigation, Water quality regulation, and Carbon storage. When analyzing the correlation between defined services of the entire city, almost all services showed a synergistic effect. However, when analyzing locally, trade-off effects (Heat island mitigation – Air quality regulation, Water quality regulation – Air quality regulation) appeared in the eastern and northwestern forest areas. This suggests the need to consider not only the synergy and trade-offs of the entire forest between specific ecosystem services but also the synergy and trade-offs of local areas in managing the regulating ecosystem services of local forests. The study result can provide primary data for the stakeholders to determine the initial conditions of the planning stage when discussing the establishment of policies related to the adjustment of the supply of regulating ecosystem services of the forests with limited access. Moreover, the study result can also help refine the estimation of the supply of the regulating ecosystem services with the availability of other forms of data.

Keywords: ecosystem service, getis ord gi* analysis, land use scoring method, regional forest, regulating service, synergies, trade-offs

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Authors: Maria Areias, Diogo Simões, Ana Figueiredo, Anishur Rahman, Filipa Figueiredo, João Nunes

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It is expected that close to 7 billion people will live in urban areas by 2050. In order to improve the sustainability of the territories and its transition towards circular economy, it’s necessary to understand its metabolism and promote and guide the entrepreneurship answer. The study of a macroeconomic metabolism involves the quantification of the inputs, outputs and storage of energy, water, materials and wastes for an urban region. This quantification and analysis representing one opportunity for the promotion of green entrepreneurship. There are several methods to assess the environmental impacts of an urban territory, such as human and environmental risk assessment (HERA), life cycle assessment (LCA), ecological footprint assessment (EF), material flow analysis (MFA), physical input-output table (PIOT), ecological network analysis (ENA), multicriteria decision analysis (MCDA) among others. However, no consensus exists about which of those assessment methods are best to analyze the sustainability of these complex systems. Taking into account the weaknesses and needs identified, the CiiM - Circular Innovation Inter-Municipality project aims to define an uniform and globally accepted methodology through the integration of various methodologies and dynamic approaches to increase the efficiency of macroeconomic metabolisms and promoting entrepreneurship in a circular economy. The pilot territory considered in CiiM project has a total area of 969,428 ha, comprising a total of 897,256 inhabitants (about 41% of the population of the Center Region). The main economic activities in the pilot territory, which contribute to a gross domestic product of 14.4 billion euros, are: social support activities for the elderly; construction of buildings; road transport of goods, retailing in supermarkets and hypermarkets; mass production of other garments; inpatient health facilities; and the manufacture of other components and accessories for motor vehicles. The region's business network is mostly constituted of micro and small companies (similar to the Central Region of Portugal), with a total of 53,708 companies identified in the CIM Region of Coimbra (39 large companies), 28,146 in the CIM Viseu Dão Lafões (22 large companies) and 24,953 in CIM Beiras and Serra da Estrela (13 large companies). For the construction of the database was taking into account data available at the National Institute of Statistics (INE), General Directorate of Energy and Geology (DGEG), Eurostat, Pordata, Strategy and Planning Office (GEP), Portuguese Environment Agency (APA), Commission for Coordination and Regional Development (CCDR) and Inter-municipal Community (CIM), as well as dedicated databases. In addition to the collection of statistical data, it was necessary to identify and characterize the different stakeholder groups in the pilot territory that are relevant to the different metabolism components under analysis. The CIIM project also adds the potential of a Geographic Information System (GIS) so that it is be possible to obtain geospatial results of the territorial metabolisms (rural and urban) of the pilot region. This platform will be a powerful visualization tool of flows of products/services that occur within the region and will support the stakeholders, improving their circular performance and identifying new business ideas and symbiotic partnerships.

Keywords: circular economy tools, life cycle assessment macroeconomic metabolism, multicriteria decision analysis, decision support tools, circular entrepreneurship, industrial and regional symbiosis

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Authors: Saifurahman Fayiz

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Afghanistan and India have close technical, political, economic, and diplomatic bilateral ties. The ties is not limited between the governments of the two countries, but their relationship are among the peoples. India is the best regional trustworthy partner and biggest donor for the development of Afghanistan. The objectives of this study to assess India’s foreign policy towards Afghanistan since 9\11. The research method conducted based on qualitative research method with descriptive. The research findings propose that; India should deal with and build up its strategy relations with neighbor countries.

Keywords: strategy, policy, India, Afghanistan

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Authors: Divya Pathak, James Sloane

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Surgical treatment of midface fractures should ideally occur within two weeks of injury, after which bony healing and consolidation make the repair more difficult for the operating surgeon. The oral and maxillofacial unit at the Royal Surrey Hospital is the tertiary referral center for maxillofacial trauma from five regional hospitals. This is a complete audit cycle of midface trauma referrals managed over a one year period. The standard set was that clinical assessment of the midface fracture would take place in a consultant led outpatient clinic within 7 days, and when indicated, surgical fixation would occur within 10 days of referral. Retrospective data was collected over one year (01/11/2018 - 31/12/2019). Three key changes were implemented: an IT referral mailbox, standardization of an on-call trauma table, and creation of a trauma theatre list. Re-audit was carried out over six months completing the cycle. 283 midface fracture referrals were received, of which 22 patients needed surgical fixation. The average time from referral to outpatient follow-up improved from 14.5 days to 8.3 days, and time from referral to surgery improved from 21.5 days to 11.6 days. Changes implemented in this audit significantly improved patient prioritization to appropriate outpatient clinics and shortened time to surgical intervention.

Keywords: maxillofacial trauma, midface trauma, oral and maxillofacial surgery, surgery fixation

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Authors: Shailendra Kumar, Lokesh Kashyap, Puneet Khanna, Nishant Patel, Rakesh Kumar, Arshad Ayub, Kelika Prakash, Yudhyavir Singh, Krithikabrindha V.

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Introduction: Spinal anesthesia is considered a standard anesthesia technique for caesarean delivery. The incidence of spinal hypotension during caesarean delivery is 70 -80%. Spinal hypotension may cause cerebral hypoperfusion in the mother, but physiologically cerebral autoregulatory mechanisms accordingly prevent cerebral hypoxia. Cerebral blood flow remains constant in the 50-150 mmHg of Cerebral Perfusion Pressure (CPP) range. Near-infrared spectroscopy (NIRS) is a non-invasive technology that is used to detect Cerebral Desaturation Events (CDEs) immediately compared to other conventional intraoperative monitoring techniques. Objective: The primary aim of the study is to correlate the change in cerebral oxygen saturation using NIRS with respect to a fall in mean blood pressure after spinal anaesthesia and to find out the effects of spinal hypotension on neonatal APGAR score, neonatal acid-base variations, and presence of Postoperative Delirium (POD). Methodology: NIRS sensors were attached to the forehead of all the patients, and their baseline readings of cerebral oxygenation on the right and left frontal regions and mean blood pressure were noted. Subarachnoid block was given with hyperbaric 0.5% bupivacaine plus fentanyl, the dose being determined by the individual anaesthesiologist. Co-loading of IV crystalloid solutions was given to the patient. Blood pressure reading and cerebral saturation were recorded every 1 minute till 30min. Hypotension was a fall in MAP less than 20% of the baseline values. Patients going for hypotension were treated with an IV Bolus of phenylephrine/ephedrine. Umbilical cord blood samples were taken for blood gas analysis, and neonatal APGAR was noted by a neonatologist. Study design: A prospective observational study conducted in a population of Thirty ASA 2 and 3 parturients scheduled for lower segment caesarean section (LSCS). Results: Mean fall in regional cerebral saturation is 28.48 ± 14.7% with respect to the mean fall in blood pressure 38.92 ± 8.44 mm Hg. The correlation coefficient between fall in saturation and fall in mean blood pressure is 0.057, and p-value {0.7} after subarachnoid block. A fall in regional cerebral saturation occurred 2±1 min before a fall in mean blood pressure. Twenty-nine out of thirty patients required vasopressors during hypotension. The first dose of vasopressor requirement is needed at 6.02±2 min after the block. The mean APGAR score was 7.86 and 9.74 at 1 and 5 min of birth, respectively, and the mean umbilical arterial pH of 7.3±0.1. According to DRS-98 (Delirium Rating Scale), the mean delirium rating score on postoperative day 1 and day 2 were 0.1 and 0.7, respectively. Discussion: There was a fall in regional cerebral oxygen saturation, which started before with respect to a significant fall in mean blood pressure readings but was statistically not significant. Maximal fall in blood pressure requiring vasopressors occurs within 10 min of SAB. Neonatal APGAR scores and acid-base variations were in the normal range with maternal hypotension, and there was no incidence of postoperative delirium in patients with post-spinal hypotension.

Keywords: cerebral oxygenation, LSCS, NIRS, spinal hypotension

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Authors: Azadeh Bashiri

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Introduction: Lack of proper diagnosis and inadequate treatment of asthma leads to physical and financial complications. This study aimed to use data mining techniques and creating a neural network intelligent system for diagnosis of asthma. Methods: The study population is the patients who had visited one of the Lung Clinics in Tehran. Data were analyzed using the SPSS statistical tool and the chi-square Pearson's coefficient was the basis of decision making for data ranking. The considered neural network is trained using back propagation learning technique. Results: According to the analysis performed by means of SPSS to select the top factors, 13 effective factors were selected, in different performances, data was mixed in various forms, so the different models were made for training the data and testing networks and in all different modes, the network was able to predict correctly 100% of all cases. Conclusion: Using data mining methods before the design structure of system, aimed to reduce the data dimension and the optimum choice of the data, will lead to a more accurate system. Therefore, considering the data mining approaches due to the nature of medical data is necessary.

Keywords: asthma, data mining, Artificial Neural Network, intelligent system

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Authors: A. Camões, M. Ferreira Dias, M. Amorim

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In recent years, the social economy is increasingly seen as a viable means to address social problems. Social enterprises, as well as public projects and initiatives targeted to meet social purposes, offer organizational models that assume heterogeneity, flexibility and adaptability to the ‘real world and real problems’. Despite the growing popularity of social initiatives, decision makers still face a paucity in what concerns the available models and tools to adequately assess its sustainability, and its impacts, notably the nature of its contribution to economic growth. This study was carried out at the local level, by analyzing the social impact initiatives and projects promoted by the Municipality of Albergaria-a-Velha (Câmara Municipal de Albergaria-a-Velha -CMA), a municipality of 25,000 inhabitants in the central region of Portugal. This work focuses on the challenges related to the qualifications and employability of citizens, which stands out as one of the key concerns in the Portuguese economy, particularly expressive in the context of small-scale cities and inland territories. The study offers a characterization of the Municipality, its socio-economic structure and challenges, followed by an exploratory analysis of multiple sourced data, collected from the CMA's documental sources as well as from privileged informants. The purpose is to conduct detailed analysis of the CMA's social projects, aimed at characterizing its potential impact for the model of qualifications and employability of the citizens of the Municipality. The study encompasses a discussion of the socio-economic profile of the municipality, notably its asymmetries, the analysis of the social projects and initiatives, as well as of data derived from inquiry actors involved in the implementation of the social projects and its beneficiaries. Finally, the results obtained with the Better Life Index will be included. This study makes it possible to ascertain if what is implicit in the literature goes to the encounter of what one experiences in reality.

Keywords: measurement, municipalities, social economy, social impact

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Authors: Christopher Muhawe, Masooda Bashir

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With increased Internet Communication Technology(ICT), the virtual world has become the new normal. At the same time, there is an unprecedented collection of massive amounts of data by both private and public entities. Unfortunately, this increase in data collection has been in tandem with an increase in data misuse and data breach. Regrettably, the majority of data breach and data misuse claims have been unsuccessful in the United States courts for the failure of proof of direct injury to physical or economic interests. The requirement to express data privacy harms from an economic or physical stance negates the fact that not all data harms are physical or economic in nature. The challenge is compounded by the fact that data breach harms and risks do not attach immediately. This research will use a descriptive and normative approach to show that not all data harms can be expressed in economic or physical terms. Expressing privacy harms purely from an economic or physical harm perspective negates the fact that data insecurity may result into harms which run counter the functions of privacy in our lives. The promotion of liberty, selfhood, autonomy, promotion of human social relations and the furtherance of the existence of a free society. There is no economic value that can be placed on these functions of privacy. The proposed approach addresses data harms from a psychological and social perspective.

Keywords: data breach and misuse, economic harms, privacy harms, psychological harms

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Authors: Shpetim Rezniqi

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Over the years has increased, and increasingly has become necessary to make audit of financial statements. An auditor to perform an audit, should plan its audit in order to provide a high-quality audit and to be performed in an economic, efficient, effective and timely. This phase of the audit is also important stages of reach to the final goal of an audit to be professional and based in Kosovo and International Standards on Auditing. Always considering Kosovo as a new state and once out of war, where everything in its entrepreneurship started from the lowest stage of economic development and aim at development and regional and European integration, planning and performing audit becomes even more important.

Keywords: control, accounting, planning, analysis

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Authors: Seongryong Kang, Woonjin Kim, Sungjoo Lee

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Under the environment of fierce competition and globalized economy, international technology collaboration has gained increasing attention as a way to improve innovation efficiency. While international technology transfer helps a firm to acquire necessary technology in a short period of time, it also has a risk; embedding external technology from overseas partners may cause a transaction cost due to the regional, cultural and language barriers, which tend to offset the benefits of such transfer. Though a number of previous studies have focused on the effects of technology in-transfer on firm performance, few have conducted in the context of international technology transfer. To fill this gap, this study aims to investigate the impact of international technology in-transfer on firm performance – both innovation and financial performance, with a particular emphasis on the diversity and intensity of such transfer. To do this, we adopted technology balance payment (TBP) data of Korean firms from 2010 to 2011, where an intermediate regression analysis was used to identify the intermediate effects of absorptive capacity. The analysis results indicate that i) the diversity and intensity of international technology transfer influence innovation performance by improving R&D capability positively; and ii) the diversity has a positive impact but the intensity has a negative impact on financial performance through the intermediation of R&D intensity. The research findings are expected to provide meaningful implications for establishing global technology strategy and developing policy programs to facilitate technology transfer.

Keywords: diversity, intensity, international technology acquisition, performance, technology transfer

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Authors: Chandra Prayaga, Aaron Wade, Lakshmi Prayaga, Gopi Shankar Mallu

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This paper presents the use of machine learning algorithms to predict the success of students in an introductory physics course. Data having 140 rows pertaining to the performance of two batches of students was used. The lack of sufficient data to train robust machine learning models was compensated for by generating synthetic data similar to the real data. CTGAN and CTGAN with Gaussian Copula (Gaussian) were used to generate synthetic data, with the real data as input. To check the similarity between the real data and each synthetic dataset, pair plots were made. The synthetic data was used to train machine learning models using the PyCaret package. For the CTGAN data, the Ada Boost Classifier (ADA) was found to be the ML model with the best fit, whereas the CTGAN with Gaussian Copula yielded Logistic Regression (LR) as the best model. Both models were then tested for accuracy with the real data. ROC-AUC analysis was performed for all the ten classes of the target variable (Grades A, A-, B+, B, B-, C+, C, C-, D, F). The ADA model with CTGAN data showed a mean AUC score of 0.4377, but the LR model with the Gaussian data showed a mean AUC score of 0.6149. ROC-AUC plots were obtained for each Grade value separately. The LR model with Gaussian data showed consistently better AUC scores compared to the ADA model with CTGAN data, except in two cases of the Grade value, C- and A-.

Keywords: machine learning, student success, physics course, grades, synthetic data, CTGAN, gaussian copula CTGAN

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Authors: Jongsoo Jurng

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The drive to expand renewable energies is often in direct conflict with sustainable development goals. Thus, it is important that energy policies account for potential trade-offs. We assess the interlinkages between energy, food, water, and land, for two case studies, Suwon and Seoul. We apply a range of assessment methods and study their usefulness as tools to identify trade-offs and to compare the sustainability performance. We calculate cross-sectoral footprints, self-sufficiency ratios and perform a simplified Energy-Water-Food nexus analysis. We use the latter for assessing scenarios to increase energy and food self-sufficiency in Suwon, while we use ecosystem service (ESS) accounting for Seoul. For Suwon, we find that constraints on the energy, food and water sectors urgently call for integrated approaches to energy policy; for Seoul, the further expansion of renewables comes at the expense of cultural and supporting ESS, which could outweigh gains from increased energy exports. We recommend a general upgrade to indicators and visualization methods that look beyond averages and a fostering of infrastructure for data on sustainable development based on harmonized international protocols. We warn against rankings of countries or regions based on benchmarks that are neither theory-driven nor location-specific.

Keywords: ESS, renewable energy, energy-water-food nexus, assessment

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Authors: Joachim Monkelbaan, Marcia Hale

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Now that global frameworks for sustainability governance (e.g. the Sustainable Development Goals, Paris Climate Agreement and Sendai Framework for Disaster Risk Reduction) are in place, the question is how these aspirations that represent major transitions can be put into practice. Water ‘infrasystems’ can play an especially significant role in strengthening regional sustainability. Infrasystems include both hard and soft infrastructure, such as pipes and technology for delivering water, as well as the institutions and governance models that direct its delivery. As such, an integrated infrasystems view is crucial for Integrative Water Management (IWM). Due to frequently contested ownership of and responsibility for water resources, these infrasystems can also play an important role in facilitating conflict and catalysing community empowerment, especially through participatory approaches to governance. In this paper, we analyze the water infrasystem of the Los Angeles region through the lens of global frameworks for sustainability governance. By complementing a solid overview of governance theories with empirical data from interviews with water actors in the LA metropolitan region (including NGOs, water managers, scientists and elected officials), this paper elucidates ways for this infrasystem to be better aligned with global sustainability frameworks. In addition, it opens up the opportunity to scrutinize the appropriateness of global frameworks when it comes to fostering sustainability action at the local level.

Keywords: governance, transitions, global frameworks, infrasystems

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Authors: Michelle Jennett, Jana Dengler, Maytal Perlman

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Background: Cervical spinal cord injury (SCI) is a devastating event that results in upper limb paralysis, loss of independence, and disability. People living with cervical SCI have identified improvement of upper limb function as a top priority. Nerve and tendon transfer surgery has successfully restored upper limb function in cervical SCI but is not universally used or available to all eligible individuals. This exploratory mixed-methods study used an implementation science approach to better understand these factors that influence access to upper limb reconstruction in the Canadian context and design an intervention to increase access to care. Methods: Data from the Canadian Institute for Health Information’s Discharge Abstracts Database (CIHI-DAD) and the National Ambulatory Care Reporting System (NACRS) were used to determine the annual rate of nerve transfer and tendon transfer surgeries performed in cervical SCI in Canada over the last 15 years. Semi-structured interviews informed by the consolidated framework for implementation research (CFIR) were used to explore Ontario healthcare provider knowledge and practices around upper limb reconstruction. An inductive, iterative constant comparative process involving descriptive and interpretive analyses was used to identify themes that emerged from the data. Results: Healthcare providers (n = 10 upper extremity surgeons, n = 10 SCI physiatrists, n = 12 physical and occupational therapists working with individuals with SCI) were interviewed about their knowledge and perceptions of upper limb reconstruction and their current practices and discussions around upper limb reconstruction. Data analysis is currently underway and will be presented. Regional variation in rates of upper limb reconstruction and trends over time are also currently being analyzed. Conclusions: Utilization of nerve and tendon transfer surgery to improve upper limb reconstruction in Canada remains low. There are a complex array of interrelated individual-, provider- and system-level barriers that prevent individuals with cervical SCI from accessing upper limb reconstruction. In order to offer equitable access to care, a multi-modal approach addressing current barriers is required.

Keywords: cervical spinal cord injury, nerve and tendon transfer surgery, spinal cord injury, upper extremity reconstruction

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Authors: Tong-Hsien Chow

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Background: Plantar pressure measurement is an effective method for assessing plantar loading and can be applied to evaluating movement performance of the foot. The purpose of this study is to explore the sprint athletes’ plantar loading characteristics and pain profiles in static standing. Methods: Experiments were undertaken on 80 first-division college sprint athletes and 85 healthy non-sprinters. ‘JC Mat’, the optical plantar pressure measurement was applied to examining the differences between both groups in the arch index (AI), three regional and six distinct sub-regional plantar pressure distributions (PPD), and footprint characteristics. Pain assessment and self-reported health status in sprint athletes were examined for evaluating their common pain areas. Results: Findings from the control group, the males’ AI fell into the normal range. Yet, the females’ AI was classified as the high-arch type. AI values of the sprint group were found to be significantly lower than the control group. PPD were higher at the medial metatarsal bone of both feet and the lateral heel of the right foot in the sprint group, the males in particular, whereas lower at the medial and lateral longitudinal arches of both feet. Footprint characteristics tended to support the results of the AI and PPD, and this reflected the corresponding pressure profiles. For the sprint athletes, the lateral knee joint and biceps femoris were the most common musculoskeletal pains. Conclusions: The sprint athletes’ AI were generally classified as high arches, and that their PPD were categorized between the features of runners and high-arched runners. These findings also correspond to the profiles of patellofemoral pain syndrome (PFPS)-related plantar pressure. The pain profiles appeared to correspond to the symptoms of high-arched runners and PFPS. The findings reflected upon the possible link between high arches and PFPS. The correlation between high-arched runners and PFPS development is worth further studies.

Keywords: sprint athletes, arch index, plantar pressure distributions, high arches, patellofemoral pain syndrome

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Authors: Chuping Lo

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This paper presents a simple model demonstrating that ceteris paribus countries with lower barriers to accessing global data tend to earn higher incomes than other countries. Therefore, large countries that inherently have greater data resources tend to have higher incomes than smaller countries, such that the former may be more hesitant than the latter to liberalize cross-border data flows to maintain this advantage. Furthermore, countries with higher artificial intelligence (AI) intensity in production technologies tend to benefit more from economies of scale in data aggregation, leading to higher income and more trade as they are better able to utilize global data.

Keywords: digital intensity, digital divide, international trade, scale of economics

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Authors: G. R. Navaneesh, E. Nagarajan, C. H. Rajam Raju

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Nowadays the multimedia data are used to store some secure information. All previous methods allocate a space in image for data embedding purpose after encryption. In this paper, we propose a novel method by reserving space in image with a boundary surrounded before encryption with a traditional RDH algorithm, which makes it easy for the data hider to reversibly embed data in the encrypted images. The proposed method can achieve real time performance, that is, data extraction and image recovery are free of any error. A secure transmission process is also discussed in this paper, which improves the efficiency by ten times compared to other processes as discussed.

Keywords: secure communication, reserving room before encryption, least significant bits, image encryption, reversible data hiding

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Authors: Fuad M. Alkoot

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DNA data have been used in forensics for decades. However, current research looks at using the DNA as a biometric identity verification modality. The goal is to improve the speed of identification. We aim at using gene data that was initially used for autism detection to find if and how accurate is this data for identification applications. Mainly our goal is to find if our data preprocessing technique yields data useful as a biometric identification tool. We experiment with using the nearest neighbor classifier to identify subjects. Results show that optimal classification rate is achieved when the test set is corrupted by normally distributed noise with zero mean and standard deviation of 1. The classification rate is close to optimal at higher noise standard deviation reaching 3. This shows that the data can be used for identity verification with high accuracy using a simple classifier such as the k-nearest neighbor (k-NN). 

Keywords: biometrics, genetic data, identity verification, k nearest neighbor

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Authors: Kibret Berhanu Getinet

Abstract:

Off-farm income diversification by farm rural households has gained the attention of researchers and policymakers due to the fact that agriculture failed to meet the needs of people in developing countries like Ethiopia. The objective of this study was to investigate income diversification strategies into off-farm activities among rural households in Hawassa Zuria Woreda, Sidama National Regional State, Ethiopia. The study used primary and secondary data sources for the primary data collection questionnaire employed as a data collection instrument. A multistage sampling technique was used to collect data from a total of 197 sample households from four kebeles of the study area. Descriptive statistics, as well as econometrics methods of data analysis, were employed. The descriptive statistics result indicates that the majority of sample rural households (68.53 %) have engaged in off-farm income diversification activities while the remaining 31.47% of households did not participate in the diversification in the study area. The choice of participants among the strategies indicates that 6.60% of respondents participated in off-farm wage employment, 30.46% participated in off-farm self-employment, and about 31.47% of them participated in both off-farm wage employment. The study revealed that the share of off-farm income in total annual earnings of households was about 48.457%, and thus, the off-farm diversification significantly contributes to the rural household income. Moreover, binary and multinomial logistic regression models were employed to identify factors that affect the participation and the choices of the off-farm income diversification strategies, respectively. The binary logit model result indicated that agro-ecological zone, education status of the households, available technical skills of the household, household saving, total livestock owned by the households, access to electricity, road access and being married of household head were significant and positively affected the chance of diversification in off-farm activities while the on-farm income of households is negatively affected the chance of diversification. Similarly, the multinomial logistic regression model estimate revealed that agroecological zone, on-farm income, available technical skills, household savings, and access to electricity are positively related and significantly influenced the household’s choice of employment into off-farm wage employment. The off-farm self-employment diversification choice is significantly influenced by on-farm income, available technical skills, household savings, total livestock owned, and access to electricity. Moreover, the result showed that the factors that affect the choice of farm households to engage in both off-farm wage and self-employment are ecological zone, education status, on-farm income, available technical skills, household own saving, market access, total livestock owned, access to electricity and road access. Thus, due attention should be given to addressing the demographic, socio-economic, and institutional constraints to strengthen off-farm income diversification strategies to improve the income of rural households.

Keywords: off-farm, incoem, diversification, logit model

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