Search results for: data security

Authors: Golayeh Yousefi, Mehdi Homaee, Ali Akbar Norouzi

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Ongoing monitoring of soil contamination by heavy metals is critical for ecosystem stability and environmental protection, and food security. The conventional methods of determining these soil contaminants are time-consuming and costly. Spectroscopy in the visible near-infrared (VNIR) - short wave infrared (SWIR) region is a rapid, non-destructive, noninvasive, and cost-effective method for assessment of soil heavy metals concentration by studying the spectral properties of soil constituents. The aim of this study is to derive spectral bands and important ranges that are sensitive to heavy metals and can be used to estimate the concentration of these soil contaminants. In other words, the change in the spectral properties of spectrally active constituents of soil can lead to the accurate identification and estimation of the concentration of these compounds in soil. For this purpose, 325 soil samples were collected, and their spectral reflectance curves were evaluated at a range of 350-2500 nm. After spectral preprocessing operations, the partial least-squares regression (PLSR) model was fitted on spectral data to predict the concentration of Cu and Ni. Based on the results, the spectral range of Cu- sensitive spectra were 480, 580-610, 1370, 1425, 1850, 1920, 2145, and 2200 nm, and Ni-sensitive ranges were 543, 655, 761, 1003, 1271, 1415, 1903, 2199 nm. Finally, the results of this study indicated that the spectral data contains a lot of information that can be applied to identify the soil properties, such as the concentration of heavy metals, with more detail.

Keywords: heavy metals, spectroscopy, spectral bands, PLS regression

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Authors: Geng-Gui Wang, Chia-Hao Chang, Jee-Cheng Wu

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A shoreline is a line where a body of water and the shore meet. It provides economic and social security to coastal habitations. However, shorelines face multiple threats due to both natural processes and man-made effects because of disasters, rapid urbanization, industrialization, and sand deposition and erosion, etc. In this study, we analyzed multi-temporal satellite images of the Yilan coast, Taiwan from 1978 to 2016, using the United States Geological Survey (USGS) Digital Shoreline Analysis System (DSAS), weather information (as rainfall records and typhoon routes), and man-made construction project data to explore the causes of shoreline changes. The results showed that the shoreline at Yilan coast is greatly influenced by typhoons and anthropogenic interventions.

Keywords: shoreline change, multi-temporal satellite, digital shoreline analysis system, DSAS, Yi-Lan coast

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Authors: Amitha Puranik, V. S. Binu, Seena Biju

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Missing data is a common problem in spatial analysis especially at the aggregate level. Missing can either occur in covariate or in response variable or in both in a given location. Many missing data techniques are available to estimate the missing data values but not all of these methods can be applied on spatial data since the data are autocorrelated. Hence there is a need to develop a method that estimates the missing values in both response variable and covariates in spatial data by taking account of the spatial autocorrelation. The present study aims to develop a model to estimate the missing data points at the aggregate level in spatial data by accounting for (a) Spatial autocorrelation of the response variable (b) Spatial autocorrelation of covariates and (c) Correlation between covariates and the response variable. Estimating the missing values of spatial data requires a model that explicitly account for the spatial autocorrelation. The proposed model not only accounts for spatial autocorrelation but also utilizes the correlation that exists between covariates, within covariates and between a response variable and covariates. The precise estimation of the missing data points in spatial data will result in an increased precision of the estimated effects of independent variables on the response variable in spatial regression analysis.

Keywords: spatial regression, missing data estimation, spatial autocorrelation, simulation analysis

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Authors: Mohammed Sale Abubakar, Kabir Omar, Mohammed Umar Abba

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The effects of climate change continue to ravage globe upsetting or even overturning the entire communities in its wake. It is therefore on the front burner of most global issues affecting the world today. Hardly any field of endeavor has escaped the manifestation of its effects. The effects of climate change on agricultural productivity calls for intense study because of the nexus between agriculture, global food security and provision of employment for the teaming population in sub-saharan Africa. This paper examines current challenges of climate change on agricultural productivity in this region. This challenge indicated that both long and short-term change in climate bring unpleasant repercussion on agricultural productivity as they manifest in the vulnerability of industrial work force. The paper also focused on the impact of agriculture and bio-environmental engineering as a separate entity that will help to fight these major challenges facing humanity currently associated with negative effects of climate change such as scarcity of water, declining agricultural yields, desert encroachment, and damage of coastal structures. Finally, a suggestion was put forward as an effort that should be directed towards mitigating the negative effects of climate change on our environment.

Keywords: climate change mitigation, desert encroachment, environment, global food security, greenhouse gases (GHGs)

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Authors: Sarra Senhadji, Imene Benzeguimi, Zohra Yagoub

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Big Data represents the recent technology of manipulating voluminous and unstructured data sets over multiple sources. Therefore, NOSQL appears to handle the problem of unstructured data. Association rules mining is one of the popular techniques of data mining to extract hidden relationship from transactional databases. The algorithm for finding association dependencies is well-solved with Map Reduce. The goal of our work is to reduce the time of generating of frequent itemsets by using Map Reduce and NOSQL database oriented document. A comparative study is given to evaluate the performances of our algorithm with the classical algorithm Apriori.

Keywords: Apriori, Association rules mining, Big Data, Data Mining, Hadoop, MapReduce, MongoDB, NoSQL

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Authors: Dan Kanmegne

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Africa will become the most populated continent by the end of the century, with around 4 billion inhabitants. Food security and climate changes will become continental issues since agricultural practices depend on climate but also contribute to global emissions and land degradation. Agroforestry has been identified as a cost-efficient and reliable strategy to address these two issues. It is defined as the integrated management of trees and crops/animals in the same land unit. Agroforestry provides benefits in terms of goods (fruits, medicine, wood, etc.) and services (windbreaks, fertility, etc.), and is acknowledged to have a great potential for carbon sequestration; therefore it can be integrated into reduction mechanisms of carbon emissions. Particularly in sub-Saharan Africa, the constraint stands in the lack of information about both areas under agroforestry and the characterization (composition, structure, and management) of each agroforestry system at the country level. This study describes and quantifies “what is where?”, earliest to the quantification of carbon stock in different systems. Remote sensing (RS) is the most efficient approach to map such a dynamic technology as agroforestry since it gives relatively adequate and consistent information over a large area at nearly no cost. RS data fulfill the good practice guidelines of the Intergovernmental Panel On Climate Change (IPCC) that is to be used in carbon estimation. Satellite data are getting more and more accessible, and the archives are growing exponentially. To retrieve useful information to support decision-making out of this large amount of data, satellite data needs to be organized so to ensure fast processing, quick accessibility, and ease of use. A new solution is a data cube, which can be understood as a multi-dimensional stack (space, time, data type) of spatially aligned pixels and used for efficient access and analysis. A data cube for Burkina Faso has been set up from the cooperation project between the international service provider WASCAL and Germany, which provides an accessible exploitation architecture of multi-temporal satellite data. The aim of this study is to map and characterize agroforestry systems using the Burkina Faso earth observation data cube. The approach in its initial stage is based on an unsupervised image classification of a normalized difference vegetation index (NDVI) time series from 2010 to 2018, to stratify the country based on the vegetation. Fifteen strata were identified, and four samples per location were randomly assigned to define the sampling units. For safety reasons, the northern part will not be part of the fieldwork. A total of 52 locations will be visited by the end of the dry season in February-March 2020. The field campaigns will consist of identifying and describing different agroforestry systems and qualitative interviews. A multi-temporal supervised image classification will be done with a random forest algorithm, and the field data will be used for both training the algorithm and accuracy assessment. The expected outputs are (i) map(s) of agroforestry dynamics, (ii) characteristics of different systems (main species, management, area, etc.); (iii) assessment report of Burkina Faso data cube.

Keywords: agroforestry systems, Burkina Faso, earth observation data cube, multi-temporal image classification

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Authors: Melaku Tsehay

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The Consortium of Christian Relief and Development Associations (CCRDA), and the CORE Group Polio Partners (CGPP) Secretariat have been working with Global Alliance for Vac-cines and Immunization (GAVI) to improve the immunization data quality in Afar and Somali Regional States. The main aim of this study was to compare the quality of immunization data before and after the above interventions in health facilities in the pastoralist communities in Ethiopia. To this end, a comparative-cross-sectional study was conducted on 51 health facilities. The baseline data was collected in May 2019, while the end line data in August 2021. The WHO data quality self-assessment tool (DQS) was used to collect data. A significant improvment was seen in the accuracy of the pentavalent vaccine (PT)1 (p = 0.012) data at the health posts (HP), while PT3 (p = 0.010), and Measles (p = 0.020) at the health centers (HC). Besides, a highly sig-nificant improvment was observed in the accuracy of tetanus toxoid (TT)2 data at HP (p < 0.001). The level of over- or under-reporting was found to be < 8%, at the HP, and < 10% at the HC for PT3. The data completeness was also increased from 72.09% to 88.89% at the HC. Nearly 74% of the health facilities timely reported their respective immunization data, which is much better than the baseline (7.1%) (p < 0.001). These findings may provide some hints for the policies and pro-grams targetting on improving immunization data qaulity in the pastoralist communities.

Keywords: data quality, immunization, verification factor, pastoralist region

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Authors: Maria A. Castillo H., Andres R. Leandro, Jose F. Bienvenido B.

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In 2015, Guatemala officially adopted the Sustainable Development Goals (SDG) according to the 2030 Agenda agreed by the United Nations Organization. In 2016, these objectives and goals were reviewed, and the National Priorities were established within the K'atún 2032 National Development Plan. In 2019 and 2021, progress was evaluated with 120 defined indicators, and the need to improve quality and availability of statistical data necessary for the analysis of sustainability indicators was detected, so the values to be reached in 2024 and 2032 were adjusted. The need for greater agricultural technology is one of the priorities established within SDG 2 "Zero Hunger". Within this area, protected agricultural production provides greater productivity throughout the year, reduces the use of chemical products to control pests and diseases, reduces the negative impact of climate and improves product quality. During the crisis caused by Covid-19, there was an increase in exports of fruits and vegetables produced in greenhouses from Guatemala. However, this information has not been considered in the 2021 revision of the Plan. The objective of this study is to evaluate the information available on Greenhouse Agricultural Production and its integration into the Sustainability Indicators for Guatemala. This study was carried out in four phases: 1. Analysis of the Goals established for SDG 2 and the indicators included in the K'atún Plan. 2. Analysis of Environmental, Social and Economic Indicator Models. 3. Definition of territorial levels in 2 geographic scales: Departments and Municipalities. 4. Diagnosis of the available data on technological agricultural production with emphasis on Greenhouses at the 2 geographical scales. A summary of the results is presented for each phase and finally some recommendations for future research are added. The main contribution of this work is to improve the available data that allow the incorporation of some agricultural technology indicators in the established goals, to evaluate their impact on Food Security and Nutrition, Employment and Investment, Poverty, the use of Water and Natural Resources, and to provide a methodology applicable to other production models and other geographical areas.

Keywords: greenhouses, protected agriculture, sustainable indicators, Guatemala, sustainability, SDG

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Authors: Maria Paula Santos, Ana Lucas

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Organizations support their operations and decision making on the data they have at their disposal, so the quality of these data is remarkably important and Data Quality (DQ) is currently a relevant issue, the literature being unanimous in pointing out that poor DQ can result in large costs for organizations. The literature review identified and described 24 Critical Success Factors (CSF) for Data Quality Management (DQM) that were presented to a panel of experts, who ordered them according to their degree of importance, using the Delphi method with the Q-sort technique, based on an online questionnaire. The study shows that the five most important CSF for DQM are: definition of appropriate policies and standards, control of inputs, definition of a strategic plan for DQ, organizational culture focused on quality of the data and obtaining top management commitment and support.

Keywords: critical success factors, data quality, data quality management, Delphi, Q-Sort

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Authors: Kimton Opiyo, Elliot M. Berry, Patil Karamchand, Barnabas K. Natamba

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Background: Postpartum depression (PPD) is a major psychiatric disorder that affects women soon after birth and in some cases, is a continuation of antenatal depression. Food insecurity (FI) and social support (SS) are known to be associated with major depressive disorder, and vice versa. This study was conducted to examine the interrelationships among FI, SS, and PPD among postpartum women in Gulu, a post-conflict region in Uganda. Methods: Cross-sectional data from postpartum women on depression symptoms, FI and SS were, respectively, obtained using the Center for Epidemiologic Studies-Depression (CES-D) scale, Individually Focused FI Access scale (IFIAS) and Duke-UNC functional social support scale. Standard regression methods were used to assess associations among FI, SS, and PPD. Results: A total of 239 women were studied, and 40% were found to have any PPD, i.e., with depressive symptom scores of ≥ 17. The mean ± standard deviation (SD) for FI score and SS scores were 6.47 ± 5.02 and 19.11 ± 4.23 respectively. In adjusted analyses, PPD symptoms were found to be positively associated with FI (unstandardized beta and standardized beta of 0.703 and 0.432 respectively, standard errors =0.093 and p-value < 0.0001) and negatively associated with SS (unstandardized beta and standardized beta of -0.263 and -0.135 respectively, standard errors = 0.111 and p-value = 0.019). Conclusions: Many women in this post-conflict region reported experiencing PPD. In addition, this data suggest that food security and psychosocial support interventions may help mitigate women’s experience of PPD or its severity.

Keywords: postpartum depression, food insecurity, social support, post-conflict region

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Authors: Bandar Alahmadi, Lethia Jackson

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Machine Learning model is used today in many real-life applications. The safety and security of such model is important, so the results of the model are as accurate as possible. One challenge of machine learning model security is the adversarial examples attack. Adversarial examples are designed by the attacker to cause the machine learning model to misclassify the input. We propose a method to generate adversarial examples to attack image classifiers. We are modifying the successfully classified images, so a classifier misclassifies them after the modification. In our method, we do not update the whole image, but instead we detect the important region, modify it, place it back to the original image, and then run it through a classifier. The algorithm modifies the detected region using two methods. First, it will add abstract image matrix on back of the detected image matrix. Then, it will perform a rotation attack to rotate the detected region around its axes, and embed the trace of image in image background. Finally, the attacked region is placed in its original position, from where it was removed, and a smoothing filter is applied to smooth the background with foreground. We test our method in cascade classifier, and the algorithm is efficient, the classifier confident has dropped to almost zero. We also try it in CNN (Convolutional neural network) with higher setting and the algorithm was successfully worked.

Keywords: adversarial examples, attack, computer vision, image processing

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Authors: Mohammed Ibrahim Girei

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Adamawa state is one the major producers of both crop and animals in Nigeria. Agricultural production serves as the major means livelihood of the people in the state. However, the agricultural activities of the farmers in the state are at subsistence level. However integration of these small scale farmers in local, national and international market is paramount importance. The paper was designed to categorize farmers based on market participation among the cattle farmers in Adamawa state, Nigeria. The multistage sampling procedure was employed. To achieve this procedure, structured questionnaires were used to collect data from 400 respondents. The data were analyzed using the descriptive statistics. The result revealed that the majority of market participants were net sellers (78.51 %) (Sales greater than purchase), net buyers were (purchase greater than sales) 12.95 % and only 9% were autarkic (sales equal purchase). The study recommends that Government should provide more effective security services in cattle farming communities, which is very important as the market participants in the study area were net sellers (producers), it will help in addressing the problem of cattle rustling and promote more investment in cattle industry. There is a need to establish a standard cattle market, veterinary services and grazing reserves in the area so that to facilitate the cattle production and marketing system in the area and to meet up with the challenging of livestock development as a result of rapid human population growth in developing countries like Nigeria.

Keywords: categories, cattle, farmers, market, participation

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Authors: Kenneth Azaigba

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The history of post-colonial African States has been dubbed a history of endemic warfare in existing literature. Indeed, Africa political environment is characterized by a multiplicity of threats to peace and security. Africa's leading drivers of conflict include abundant (especially mineral) resources, personal rule and attendant political authoritarianism, manipulation of identity politics across ethnicity, marginalization of communities, as well as electoral mal-practices resulting in contested legitimacy and resultant violence. However, the character of armed conflicts in Africa is changing. This paper attempts to reconstruct the trajectory of armed conflicts in Africa and explain the changing pattern of armed conflict. The paper contends that large scale political violence in Africa is on the decline rendering the endemic thesis an inappropriate paradigm in explaining political conflicts in Africa. The paper also posits that though small scale conflicts are springing up and exhibiting trans-border dimensions, these patterns of armed conflicts are not peculiar to Africa but emerging waves of global conflicts. The paper explains that the shift in the scale of warfare in Africa is a function of a multiplicity of post-cold war global contradictions. Inclusive governance, social justice and economic security are articulated as workable panaceas for mitigating warfare in Africa.

Keywords: Africa, conflicts, pattern, war

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Authors: Myagmarsuren Soronzonjav, N. Togtokhbayar, L. Davaahuu, B. Minjigdorj, Seong Gu Hwang

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The number of natural or organic product consumers is increased in recent years and this healthy demand pushes to increase usage of healthy meat. At the same time, consumers pay more attention on the healthy fat, especially on unsaturated fatty acids. These long chain carbohydrates reduce heart diseases, improve memory and eye sight and activate the immune system. One of the important issues to be solved for our Mongolia’s food security is to provide healthy, fresh, widely available and cheap meat for the population. Thus, an importance of the Selenge breed meat production is increasing in order to supply the quality meat food security since the Selenge breed cattle are rapidly multiplied, beneficial in term of income, the same quality as Mongolian breed, and well digested for human body. We researched the lipid, unsaturated and saturated fatty acid contents of meat of Selenge breed younger cattle by their muscle types. Result of our research reveals that 11 saturated fatty acids are detected. For the content of palmitic acid among saturated fatty acids, 23.61% was in the sirloin meat, 24.01% was in the round and chuck meat, and 24.83% was in the short loin meat.

Keywords: chromatogram, gas chromatography, organic resolving, saturated and unsaturated fatty acids

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Authors: Asma’a Mahfoud, Abu Bakar Md. Sultan, Abdul Azim Abd, Norhayati Mohd Ali, Novia Admodisastro

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Obfuscation is a practice to make something difficult and complicated. Programming code is ordinarily obfuscated to protect the intellectual property (IP) and prevent the attacker from reverse engineering (RE) a copyrighted software program. Obfuscation may involve encrypting some or all the code, transforming out potentially revealing data, renaming useful classes and variables (identifiers) names to meaningless labels, or adding unused or meaningless code to an application binary. Obfuscation techniques were not performing effectively recently as the reversing tools are able to break the obfuscated code. We propose in this paper a hybrid obfuscation technique that contains three approaches of renaming. Experimentation was conducted to test the effectiveness of the proposed technique. The experimentation has presented a promising result, where the reversing tools were not able to read the code.

Keywords: intellectual property, obfuscation, software security, reverse engineering

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Authors: Maria Brás

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The main purpose of the presentation is to identify the impacts and appropriate measures to prevent potential attacks, or minimize the risk of an attack in tourist destination. Terrorism has been growing in the shadow of unpredictability, however, is possible to minimize the danger of a terrorist attack by doing the: (1) recognition; (2); evaluation; (3) avoidance; (4) threat reduction. The vulnerability of tourism industry to terrorism is an undeniable fact, and terrorists know it. They use this advantage attacking tourists for very specific reasons, such as the: (1) international coverage by the media, “if it bleeds it leads” ; (2) chances of getting different nationalities at the same place and time; (3) possibility of destroyed the economy of a destination, or destinations (“terrorism contamination effect”), through the reduction of tourist demand; (4) psychological, and social disruption based on fear of negative consequences. Security incidents, such as terrorism, include different preventive measures that can be conducted in partnership with: tourism industry (hotels, airports, tourist attractions, among others); central government; public and/or private sector; local community; and media. The recovery strategies must be based on the dissemination of positive information to the media; in creating new marketing strategies that emphasize the social and cultural values of the destination; encourage domestic tourism; get government, or state, financial support.

Keywords: terrorism, tourism, safety, security, impacts, prevention, recovery

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Authors: Rashi Jain

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The Wireless Body Area Networks (WBANs) is an emerging interdisciplinary area where small sensors are placed on/within the human body. These sensors monitor the physiological activities and vital statistics of the body. The data from these sensors is aggregated and communicated to a remote doctor for immediate attention or to a database for records. On 6 Feb 2012, the IEEE 802.15.6 task group approved the standard for Body Area Network (BAN) technologies. The standard proposes the physical and MAC layer for the WBANs. The work provides an introduction to WBANs and overview of the physical and MAC layers of the standard. The physical layer specifications have been covered. A comparison of different protocols used at MAC layer is drawn. An introduction to the network layer and security aspects of the WBANs is made. The WBANs suffer certain limitations such as regulation of frequency bands, minimizing the effect of transmission and reception of electromagnetic signals on the human body, maintaining the energy efficiency among others. This has slowed down their implementation.

Keywords: vehicular networks, sensors, MicroController 8085, LTE

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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: 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: Muhammad Umar

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Safety and Assets management is considering a backbone of every department. GIS in the Railway become very important to Manage Assets and Security through Digital Maps and Web based GIS Maps. It provides a complete frame of work to the organization for the management of assets. Pakistan Railway is the most common and safest mode of traveling in Pakistan. Due to ever-increasing demand of transporting huge amount of information generated from various sources and this information must be accurate. This creates problems for Passengers and Administration that causes finical and time loss. GIS Solve this problem by Digital Maps & Database. It provides you a real time Spatial and Statistical analysis that helps you to communicate and exchange the information in a sophisticated way to the users. GIS Based Web system provides a facility to different end user to make query at a time as per requirements. This GIS System provides an advancement in an organization for a complete Monitoring, Safety and Decision System for tracks, Stations and Junctions that further use for the Analysis of different areas i.e. analysis of tracks, junctions and Stations in case of reconstruction, Rescue for rail accidents and Natural disasters .This Research work helps to reduce the financial loss and reduce human mistakes helps you provide a complete security and Management system of assets.

Keywords: Geographical Information System (GIS) for assets management, geo spatial database, railway assets management, Pakistan

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Authors: Nazli Hardy

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Multidisciplinary application of computer science, interactive database-driven web application, the Internet of Things (IoT) represents a digital ecosystem that has pervasive technological, social, and economic, impact on the human population. It is a long-term technology, and its development is built around the connection of everyday objects, to the Internet. It is estimated that by 2020, with billions of people connected to the Internet, the number of connected devices will exceed 50 billion, and thus IoT represents a paradigm shift in in our current interconnected ecosystem, a communication shift that will unavoidably affect people, businesses, consumers, clients, employees. By nature, in order to provide a cohesive and integrated service, connected devices need to collect, aggregate, store, mine, process personal and personalized data on individuals and corporations in a variety of contexts and environments. A significant factor in this paradigm shift is the necessity for secure and appropriate transmission, processing and storage of the data. Thus, while benefits of the applications appear to be boundless, these same opportunities are bounded by concerns such as trust, privacy, security, loss of control, and related issues. This poster and presentation look at a multi-factor authentication (MFA) mechanisms that need to change from the login-password tuple to an Identity and Access Management (IAM) model, to the more cohesive to Identity Relationship Management (IRM) standard. It also compares and contrasts messaging protocols that are appropriate for the IoT ecosystem.

Keywords: Internet of Things (IoT), authentication, protocols, survey

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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: Chander Shekhar Kohli

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In the field of international relations, countries have been experiencing distinct nature of conflicts. But, in the case of Association of Southeast Asian Nations (ASEAN) for a long time, the members have witnessed conflicts, small and large. These conflicts, as a result, have given catastrophic outcomes, such as killings and destroying properties. For the resolution of such conflicts, nonetheless, efforts likewise have been made, simultaneously, in terms of establishing peace and security. In this background, the ASEAN presents a significant example as before it had faced several wars, like Vietnam War, Cambodia conflicts, and so on. This research paper, therefore, strives to examine the ASEAN as a case with the help of both primary and secondary sources. It likewise will be dealt with how changing norms and identity building facilitate the ASEAN countries to deal with their conflicts both internal and external. This paper also will discuss how internal developments within countries affect conflict resolution process as each member of ASEAN is guided by its national interest. It is then argued that conflict resolution in the ASEAN is moving from its existing power-based solution to norms and identity-based solution as member countries have become more dependent on other countries. The research, therefore, is concluded by saying that the conflicts could only be resolved through building norms and common identities, which of course are recognized crucial mechanisms among the ASEAN countries with some exceptions.

Keywords: ASEAN, conflict resolution, norms and identities, peace and security

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Authors: Sevelina Ndlovu

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Financial Technology (fintech) advancement is recognised as one of the most transformational innovations in the financial industry. Fintech has given rise to internet-only digital banking, a novel financial technology advancement, and innovation that allows banking services through internet applications with no need for physical branches. This technology is becoming a new banking normal among consumers for its ubiquitous and real-time access advantages. There is evident switching and migration from traditional banking towards these fintech facilities, which could possibly pose a systemic risk if not properly understood and monitored. Fintech advancement has also brought about the emergence and escalation of financial technology consumption themes such as trust, security, perceived risk, and sustainability within the banking industry, themes scarcely covered in existing theoretic literature. To that end, the objective of this research is to investigate factors that determine fintech adoption and propose an integrated adoption model. This study aims to establish what the significant drivers of adoption are and develop a conceptual model that integrates technological, behavioral, and environmental constructs by extending the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2). It proposes integrating constructs that influence financial consumption themes such as trust, perceived risk, security, financial incentives, micro-investing opportunities, and environmental consciousness to determine the impact of these factors on the adoption and intention to use digital banking apps. The main advantage of this conceptual model is the consolidation of a greater number of predictor variables that can provide a fuller explanation of the consumer's adoption of digital banking Apps. Moderating variables of age, gender, and income are incorporated. To the best of author’s knowledge, this study is the first that extends the UTAUT2 model with this combination of constructs to investigate user’s intention to adopt internet-only digital banking apps in the UK context. By investigating factors that are not included in the existing theories but are highly pertinent to the adoption of internet-only banking services, this research adds to existing knowledge and extends the generalisability of the UTAUT2 in a financial services adoption context. This is something that fills a gap in knowledge, as highlighted to needing further research on UTAUT2 after reviewing the theory in 2016 from its original version of 2003. To achieve the objectives of this study, this research assumes a quantitative research approach to empirically test the hypotheses derived from existing literature and pilot studies to give statistical support to generalise the research findings for further possible applications in theory and practice. This research is explanatory or casual in nature and uses cross-section primary data collected through a survey method. Convenient and purposive sampling using structured self-administered online questionnaires is used for data collection. The proposed model is tested using Structural Equation Modelling (SEM), and the analysis of primary data collected through an online survey is processed using Smart PLS software with a sample size of 386 digital bank users. The results are expected to establish if there are significant relationships between the dependent and independent variables and establish what the most influencing factors are.

Keywords: banking applications, digital banking, financial technology, technology adoption, UTAUT2

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Authors: Girma Y. Iyassu Menelik

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The international community has gone through indescribable atrocities resulting from acts of war. These atrocities turned Europe and Africa into a wilderness of bloodshed and crime. In the period 1960- 1970s Africa witnessed unprecedented and well-documented assaults on life and property. This necessitated the adoption, signing and ratification of the International Criminal Court, establishment of the International Court of Justice which is a great achievement for the protection and fulfilling of human rights in the context of international political instability. The ICC came as an important opportunity to advance justice for serious crimes committed in violation of international law. Thus the Rome statute has become a formidable contribution to peace and security. There are concerns that the ICC is targeting African states. However, the ICC cannot preside over cases that are not parties to the Rome statute unless the UN Security council refers the situation or the relevant state asks the court to become involved. The instable international political situation thus deals with criminal prosecutions where amnesty is not permissible or is strongly repudiated. The court has become important justice instruments for states that are unable or unwilling to fulfill their obligation to address legacies of massive human rights violations. The ICJ as a court has a twofold role; to settle legal disputes submitted to it by states, and to give advisory opinions on legal questions referred to it by duly authorized United Nations organs and specialized agencies. All members of the UN are ipso facto parties to the statute of the ICJ. The court gives advisory opinion on any legal question. These courts are the most appropriate fora to pronounce on international crimes and are in a better position to know and apply international law. Cases that have been brought to the courts include Rwanda’s genocide, Liberia’s Charles Taylor etc. The receptiveness and cooperation of the local populations are important to the courts and if the ICC and ICJ can provide appropriate protections for the physical and economic safety of victims then peace and human rights observance can be attained. This paper will look into the effectiveness and impediments of these courts in handling criminal and injustices in international politics as while as what needs to be done to strengthen the capacity of these courts.

Keywords: ICC, international politics, justice, UN security council, violence, protection, fulfilling

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Authors: Hagar Elsayed

Abstract:

This case study examines the framing of the diverse populations of Arab, Muslim and South Asian immigrants and their descendants in local communities by both federal and local law enforcement agencies. It explores how urban spaces and policing are constructed as necessary components of national security in the context of the war on terror by focusing on practices employed in local spaces such as Dearborn, Michigan and training methods adopted on a national level. The proliferation of American Arabs as ‘terrorist’ works to legitimize not only increasing state surveillance, but also military strategies which infringe on ‘inside’ spaces. Sustaining these progressively militarized civil policing operations, which demand intense mobilization of state power, requires that whole neighborhoods and districts are reimagined to portray these geographies in a certain light. This case study is central in understanding how Arab, South Asian, and Muslim civilians’ transformation into a “national security” issue have created militarized police enforcement agencies that employ military tactics to map the terrain of Otherness. This study looks at how race factors into key recent incidents, and asks whether this militarization builds from past forms of racist policing, and whether these specific incidents are reflective of larger patterns or whether they are just isolated incidents.

Keywords: American-Muslims, Arabs, militarization, policing

Procedia PDF Downloads 136

Authors: Adriana Postal, Silvio C. Sampaio, Marcio A. Villas Boas, Josué P. Castro

Abstract:

This study deals with the estimation of reference evapotranspiration (ET₀) in an agricultural context, focusing on efficient irrigation management to meet the growing interest in the sustainable management of water resources. Given the importance of water in agriculture and its scarcity in many regions, efficient use of this resource is essential to ensure food security and environmental sustainability. The methodology used involved the application of artificial intelligence techniques, specifically Multilayer Perceptron (MLP) Artificial Neural Networks (ANNs), to predict ET₀ in the state of Paraná, Brazil. The models were trained and validated with meteorological data from the Brazilian National Institute of Meteorology (INMET), together with data obtained from a producer's weather station in the western region of Paraná. Two optimizers (SGD and Adam) and different meteorological variables, such as temperature, humidity, solar radiation, and wind speed, were explored as inputs to the models. Nineteen configurations with different input variables were tested; amidst them, configuration 9, with 8 input variables, was identified as the most efficient of all. Configuration 10, with 4 input variables, was considered the most effective, considering the smallest number of variables. The main conclusions of this study show that MLP ANNs are capable of accurately estimating ET₀, providing a valuable tool for irrigation management in agriculture. Both configurations (9 and 10) showed promising performance in predicting ET₀. The validation of the models with cultivator data underlined the practical relevance of these tools and confirmed their generalization ability for different field conditions. The results of the statistical metrics, including Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Coefficient of Determination (R²), showed excellent agreement between the model predictions and the observed data, with MAE as low as 0.01 mm/day and 0.03 mm/day, respectively. In addition, the models achieved an R² between 0.99 and 1, indicating a satisfactory fit to the real data. This agreement was also confirmed by the Kolmogorov-Smirnov test, which evaluates the agreement of the predictions with the statistical behavior of the real data and yields values between 0.02 and 0.04 for the producer data. In addition, the results of this study suggest that the developed technique can be applied to other locations by using specific data from these sites to further improve ET₀ predictions and thus contribute to sustainable irrigation management in different agricultural regions. The study has some limitations, such as the use of a single ANN architecture and two optimizers, the validation with data from only one producer, and the possible underestimation of the influence of seasonality and local climate variability. An irrigation management application using the most efficient models from this study is already under development. Future research can explore different ANN architectures and optimization techniques, validate models with data from multiple producers and regions, and investigate the model's response to different seasonal and climatic conditions.

Keywords: agricultural technology, neural networks in agriculture, water efficiency, water use optimization

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Authors: Sam Ng, Lewis Leighton, Sam Atkinson, Carson Yan, Landan Hu, Leslie Cheung, Brian Yap, Kent Lung, Ketat Sarakune

Abstract:

This paper introduces a method for verifying cryptocurrency reserves that balances the need for both transparency and data confidentiality. Our methodology employs cryptographic techniques, including Merkle Trees, Bulletproof, and zkSnark, to verify that total assets equal or exceed total liabilities, represented by customer funds. Importantly, this verification is achieved without disclosing sensitive information such as the total asset value, customer count, or cold wallet addresses. We delve into the construction and implementation of this methodology. While the system is robust and scalable, we also identify areas for potential enhancements to improve its efficiency and versatility. As the digital asset landscape continues to evolve, our approach provides a solid foundation for ensuring continued trust and security in digital asset platforms.

Keywords: cryptocurrency, crypto-currency, proof-of-reserve, por, zero-knowledge, ZKP

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Authors: Azadeh Bashiri

Abstract:

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

Procedia PDF Downloads 273

Authors: Ladaporn Pithuk

Abstract:

The purposes of the study were to ascertain the customer requirement, to identify the factors related to online business in Thailand. The sample of this study consisted of 400 customers who are purchasing product and service on E-commerce. To get primary sources, a questionnaire consisting of 31 questions was designed and adapted from previous studies. The data from the questionnaires were collected and analyzed in descriptive forms and (ONE-WAY ANOVA) was conducted. The majority of the respondents showed customer requirement by stating “moderately agree” for questions asking them about customization, connection, content, commerce, context, communication and community, however, they also displayed negative attitudes by identifying “moderately disagree” for security concerns and after-sales services. These important issues need to be improved immediately since it can encourage customers to buy goods and services through the Internet or discourage them, and businesses should offer more channels of payment methods for customers for instance, e-payment.

Keywords: customer requirement, customization, connection, online business

Procedia PDF Downloads 201