Search results for: data security architecture

Authors: Usman Adekunle Ojedokun, Adeyinka Abideen Aderinto

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Migration remains an important course of action often resort-to by human and some other classes of animal for survival in the face of life-threatening conditions. However, the activity of certain group of immigrants, who are exploiting the socio-economic and environmental challenges in their home countries to conduct street begging across different countries in Africa, is fast becoming a major cause for concern. This paper examined the migratory trajectory of transnational street beggars in South Western, Nigeria. Strain and Migration Network Theories were adopted for the study. The methods of data collection were survey questionnaire, in-depth interview, and key informant interview. Convenience and purposive sampling techniques were employed for the selection of 395 transnational street beggars and 4 key informants were purposively chosen. Findings revealed that transnational street beggars immigrated into Nigeria all year round and all of them came by road. Also, while some of them entered the country officially, others gained entry illegally. The majority (29.3%) arrived through Sokoto, a border State to some neighbouring countries. This study calls for more security measures at the Nigerian borders as a way of controlling the influx of this category of beggars into the country.

Keywords: transnational street beggars, street begging, migration, Nigeria

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Authors: Harold P. Villota, Alejandro Osorio B.

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The energy meteorology is an area for study energy complementarity and the use of renewable sources in interconnected systems. Due to diversify the energy matrix in Colombia with wind sources, is necessary to know the data bases about this one. However, the time series given by 260 automatic weather stations have empty, and no apply data, so the purpose is to fill the time series selecting two years to characterize, impute and use like base to complete the data between 2005 and 2020.

Keywords: complementarity, wind speed, renewable, colombia, characteri, characterization, imputation

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Authors: Hend Albassam, Nouf Alrumaih

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Nowadays we are in the age of technologies and communication and there is no doubt that technologies such as the Internet can offer many advantages for many business fields, and the health field is no execution. In fact, using the Internet provide us with a new path to improve the quality of health care throughout the world. The e-healthcare offers many advantages such as: efficiency by reducing the cost and avoiding duplicate diagnostics, empowerment of patients by enabling them to access their medical records, enhancing the quality of healthcare and enabling information exchange and communication between healthcare organizations. There are many problems that result from using papers as a way of communication, for example, paper-based prescriptions. Usually, the doctor writes a prescription and gives it to the patient who in turn carries it to the pharmacy. After that, the pharmacist takes the prescription to fill it and give it to the patient. Sometimes the pharmacist might find difficulty in reading the doctor’s handwriting; the patient could change and counterfeit the prescription. These existing problems and many others heighten the need to improve the quality of the healthcare. This project is set out to develop a distributed e-healthcare system that offers some features of e-health and addresses some of the above-mentioned problems. The developed system provides an electronic health record (EHR) and enables communication between separate health care organizations such as the clinic, pharmacy and laboratory. To develop this system, the Service Oriented Architecture (SOA) is adopted as a design approach, which helps to design several independent modules that communicate by using web services. The layering design pattern is used in designing each module as it provides reusability that allows the business logic layer to be reused by different higher layers such as the web service or the website in our system. The experimental analysis has shown that the project has successfully achieved its aims toward solving the problems related to the paper-based healthcare systems and it enables different health organization to communicate effectively. It implements four independent modules including healthcare provider, pharmacy, laboratory and medication information provider. Each module provides different functionalities and is used by a different type of user. These modules interoperate with each other using a set of web services.

Keywords: e-health, services oriented architecture (SOA), web services, interoperability

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Authors: Hyun-Woo Cho

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Unexpected events may occur with serious impacts on industrial process. This work utilizes a data representation technique to model and to analyze process data pattern for the purpose of diagnosis. In this work, the use of triangular representation of process data is evaluated using simulation process. Furthermore, the effect of using different pre-treatment techniques based on such as linear or nonlinear reduced spaces was compared. This work extracted the fault pattern in the reduced space, not in the original data space. The results have shown that the non-linear technique based diagnosis method produced more reliable results and outperforms linear method.

Keywords: process monitoring, data analysis, pattern modeling, fault, nonlinear techniques

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Authors: Mohamed Al Araby, Amany Salman, Mostafa Amin, Mohamed Madbully, Dalia Keraa, Mariam Ali, Marah Abdelfatah, Mariam Ahmed, Ahmed Hassab

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In recent years, the architecture, engineering, and construction (A.E.C.) industry have been exposed to important innovations, most notably the global integration of digital design and fabrication (D.D.F.) processes in the industry’s workflow. Despite this evolution in that sector, Africa was excluded from the examination of this development. The reason behind this exclusion is the preconceived view of it as a developing region that still employs traditional methods of construction. The primary objective of this review is to investigate the trend of digital construction (D.C.) in the African environment and the difficulties in its regular utilization of it. This objective can be attained by recognizing the notion of distributed computing in Africa and evaluating the impact of the projects deploying this technology on both the immediate and broader contexts. The paper’s methodology begins with the collection of data from 224 initiatives throughout Africa. Then, 50 of these projects were selected based on the criteria of the project's recency, typology variety, and location diversity. After that, a literature-based comparative analysis was undertaken. This study’s findings reveal a pattern of motivation for applying digital fabrication processes. Moreover, it is essential to evaluate the socio-economic effects of these projects on the population living near the analyzed subject. The last step in this study is identifying the influence on the neighboring nations.

Keywords: Africa, digital construction, digital design, fabrication

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Authors: Ishna Indika Jusi, Rifana Meika

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Terrorism financing method in Indonesia is developing at an alarming rate, to the point, it is now becoming more complex than before. Terrorists traditionally use conventional methods like robberies, charities, and courier services to fund their activities; today terrorists are able to utilize modern methods in financing their activities due to the rapid development in financial technology nowadays; one example is by hacking an illegal Fintech Company. Therefore, this research is conducted in order to explain and analyze the consideration behind the usage of an illegal fintech company to finance terrorism activities and how to prevent it. The analysis in this research is done by using the theory that is coined by Michael Freeman about the reasoning of terrorists when choosing their financing method. The method used in this research is a case study, and the case that is used for this research is the terrorism financing hacking of speedline.com in 2011 by Rizki Gunawan. Research data are acquired from interviews with the perpetrators, experts from INTRAC (PPATK), Special Detachment 88, reports, and journals that are relevant to the research. As a result, this study found that the priority aspects in terms of terrorist financing are security, quantity, and simplicity while obtaining funds.

Keywords: Fintech, illegal, Indonesia, technology, terrorism financing

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Authors: Mostafa Gamal, Hoda K. Mohamed, Islam El-Maddah, Ali Hamdi

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In recent years, many digital documents on the web have been created due to the rapid growth of ’social applications’ communities or ’Data-intensive applications’. The evolution of online-based multimedia data poses new challenges in storing and querying large amounts of data for online recommender systems. Graph data models have been shown to be more efficient than relational data models for processing complex data. This paper will explain the key differences between graph and relational databases, their strengths and weaknesses, and why using graph databases is the best technology for building a realtime recommendation system. Also, The paper will discuss several similarity metrics algorithms that can be used to compute a similarity score of pairs of nodes based on their neighbourhoods or their properties. Finally, the paper will discover how NLP strategies offer the premise to improve the accuracy and coverage of realtime recommendations by extracting the information from the stored unstructured knowledge, which makes up the bulk of the world’s data to enrich the graph database with this information. As the size and number of data items are increasing rapidly, the proposed system should meet current and future needs.

Keywords: graph databases, NLP, recommendation systems, similarity metrics

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Authors: Osakwe Jude Odiakaosa

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Today’s digital society is characterized by e-education or e-learning, e-commerce, and so on. All these have been propelled by digital revolution. Digital technology such as computer technology, Global Positioning System (GPS) and Geographic Information System (GIS) has been having a tremendous impact on the field of technology. This development has positively affected the scope, methods, speed of data acquisition, data management and the rate of delivery of the results (map and other map products) of data processing. This paper tries to address the impact of revolution brought by digital technology.

Keywords: digital revolution, internet, technology, data management

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Authors: Kerolis Samoul Zaghloul Noaman

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area law is the brand new access in the basket of worldwide law in the latter half of the 20 th Century. inside the last hundred and fifty years, courts and pupils advanced a consensus that, the custom is an vital supply of global law. Article 38(1) (b) of the statute of the international court of Justice identified global custom as a supply of global law. country practices and usages have a more role to play in formulating commonplace international regulation. This paper examines those country practices which may be certified to emerge as global standard law. due to the fact that, 1979 (after Moon Treaty) no hard law had been developed within the vicinity of space exploration. It attempts to link among country practices and custom in area exploration and development of standard global regulation in area activities. The paper makes use of doctrinal approach of felony research for inspecting the current questions of worldwide regulation. The paper explores exceptional worldwide prison files which include general meeting Resolutions, Treaty standards, working papers of UN, cases relating to commonplace global law and writing of jurists regarding area law and standard international law. it's far argued that, ideas such as common background of mankind, non-navy region, sovereign equality, nuclear weapon unfastened area and protection of outer area environment, etc. evolved nation practices a number of the worldwide community which can be certified to turn out to be international customary regulation.

Keywords: social networks privacy issues, social networks security issues, social networks privacy precautions measures, social networks security precautions measures

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Authors: Hamid Yazdani, Fatemeh Abbasi

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Understanding the natural potentials, as the basis for the prevailing context of human activities, environmental planning, and land-use form shows. In this regard, regional characteristics and spatial distribution of the dominant elements in shaping human behavior and environment play a role Knndhayy. As far as today's studies of human Byvklymay basis for urban planning, settlement, architecture, Tourism and so on. In this study, comfort or lack of comfort in Shiraz in Horn of models and indices based on eco-Baker, Trjvng, were examined and the best time to do-using 39 years of data (TCI) stress, and the effective temperature Environmental activities and tourism in the city was established. The results showed that the worth parameters used, the ability to detect Terms of comfort and discomfort are Shiraz, despite minor differences, relatively homogenous aspects of the city provide a comfortable climate. Studies showed that having diversity in the worth of Shiraz during the year, the situation is heating up much coolness; during winter and summer Find out eco comfort zone and during the transition from cold to warm in spring and autumn (April) and warm to cold (November) climate Iran is close to human comfort. Totally, unique human comfort conditions in spring, the best season for environmental activities Tourism in Shiraz.

Keywords: BIO comfort Klymayy, Trjvng, baker, effective temperature, stress and (TCI)

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Authors: Abdullah Al Mamun, Talal Alkharobi

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As data size is growing up, people are became more familiar to store big amount of secret information into cloud storage. Companies are always required to need transfer massive business files from one end to another. We are going to lose privacy if we transmit it as it is and continuing same scenario repeatedly without securing the communication mechanism means proper encryption. Although asymmetric key encryption solves the main problem of symmetric key encryption but it can only encrypt limited size of data which is inapplicable for large data encryption. In this paper we propose a probable approach of pretty good privacy for encrypt big data using both symmetric and asymmetric keys. Our goal is to achieve encrypt huge collection information and transmit it through a secure communication channel for committing the business and personal privacy. To justify our method an experimental dataset from three different platform is provided. We would like to show that our approach is working for massive size of various data efficiently and reliably.

Keywords: big data, cloud computing, cryptography, hadoop, public key

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Authors: Snezana Savoska, Blagoj Ristevski, Violeta Manevska, Zlatko Savoski, Ilija Jolevski

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Big data is widely accepted by the pharmaceutical companies as a result of business demands create through legal pressure. Pharmaceutical companies have many legal demands as well as standards’ demands and have to adapt their procedures to the legislation. To manage with these demands, they have to standardize the usage of the current information technology and use the latest software tools. This paper highlights some important aspects of experience with big data projects implementation in a pharmaceutical Macedonian company. These projects made improvements of their business processes by the help of new software tools selected to comply with legal and business demands. They use IT as a strategic tool to obtain competitive advantage on the market and to reengineer the processes towards new Internet economy and quality demands. The company is required to manage vast amounts of structured as well as unstructured data. For these reasons, they implement projects for emerging and appropriate software tools which have to deal with big data concepts accepted in the company.

Keywords: big data, unstructured data, SAP ERP, documentum

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Authors: Adriano Araujo Carvalho, Arturo Alatrista Corrales

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This paper intends to show how electrical energy consumption and production data analysis were used to find opportunities to save energy at Taboada wastewater treatment plant in Callao, Peru. In order to access the data, it was used independent data networks for both electrical and process instruments, which were taken to analyze under an ISO 50001 energy audit, which considered, thus, Energy Performance Indexes for each process and a step-by-step guide presented in this text. Due to the use of aforementioned methodology and data mining techniques applied on information gathered through electronic multimeters (conveniently placed on substation switchboards connected to a cloud network), it was possible to identify thoroughly the performance of each process and thus, evidence saving opportunities which were previously hidden before. The data analysis brought both costs and energy reduction, allowing the plant to save significant resources and to be certified under ISO 50001.

Keywords: energy and production data analysis, energy management, ISO 50001, wastewater treatment plant energy analysis

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Authors: Misty Attwood, Helgi Schioth

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Transmembrane proteins are important components in many essential cell processes such as signal transduction, cell-cell signalling, transport of solutes, structural adhesion activities, and protein trafficking. Due to their involvement in diverse critical activities, transmembrane proteins are implicated in different disease pathways and hence are the focus of intense interest in understanding functional activities, their pathogenesis in disease, and their potential as pharmaceutical targets. Further, as the structure and function of proteins are correlated, investigating a group of proteins with the same tertiary structure, i.e., the same number of transmembrane regions, may give understanding about their functional roles and potential as therapeutic targets. In this in silico bioinformatics analysis, we identify and comprehensively characterize the previously unstudied group of proteins with five transmembrane-spanning regions (5TM). We classify nearly 60 5TM proteins in which 31 are members of ten families that contain two or more family members and all members are predicted to contain the 5TM architecture. Furthermore, nine singlet proteins that contain the 5TM architecture without paralogues detected in humans were also identifying, indicating the evolution of single unique proteins with the 5TM structure. Interestingly, more than half of these proteins function in localization activities through movement or tethering of cell components and more than one-third are involved in transport activities, particularly in the mitochondria. Surprisingly, no receptor activity was identified within this family in sharp contrast with other TM families. Three major 5TM families were identified and include the Tweety family, which are pore-forming subunits of the swelling-dependent volume regulated anion channel in astrocytes; the sidoreflexin family that acts as mitochondrial amino acid transporters; and the Yip1 domain family engaged in vesicle budding and intra-Golgi transport. About 30% of the proteins have enhanced expression in the brain, liver, or testis. Importantly, 60% of these proteins are identified as cancer prognostic markers, where they are associated with clinical outcomes of various tumour types, indicating further investigation into the function and expression of these proteins is important. This study provides the first comprehensive analysis of proteins with 5TM regions and provides details of the unique characteristics and application in pharmaceutical development.

Keywords: 5TM, cancer prognostic marker, drug targets, transmembrane protein

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Authors: Krishan Kumar, Mohit Mittal, Pramod Kumar

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Wireless sensor network is one of the most promising communication networks for monitoring remote environmental areas. In this network, all the sensor nodes are communicated with each other via radio signals. The sensor nodes have capability of sensing, data storage and processing. The sensor nodes collect the information through neighboring nodes to particular node. The data collection and processing is done by data aggregation techniques. For the data aggregation in sensor network, clustering technique is implemented in the sensor network by implementing self-organizing feature map (SOFM) neural network. Some of the sensor nodes are selected as cluster head nodes. The information aggregated to cluster head nodes from non-cluster head nodes and then this information is transferred to base station (or sink nodes). The aim of this paper is to manage the huge amount of data with the help of SOM neural network. Clustered data is selected to transfer to base station instead of whole information aggregated at cluster head nodes. This reduces the battery consumption over the huge data management. The network lifetime is enhanced at a greater extent.

Keywords: artificial neural network, data clustering, self organization feature map, wireless sensor network

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Authors: Suzan Wedyan

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Data mining is one of the main phases in the Knowledge Discovery Database (KDD) which is responsible of finding hidden and useful knowledge from databases. There are many different tasks for data mining including regression, pattern recognition, clustering, classification, and association rule. In recent years a promising data mining approach called associative classification (AC) has been proposed, AC integrates classification and association rule discovery to build classification models (classifiers). This paper surveys and critically compares several AC algorithms with reference of the different procedures are used in each algorithm, such as rule learning, rule sorting, rule pruning, classifier building, and class allocation for test cases.

Keywords: associative classification, classification, data mining, learning, rule ranking, rule pruning, prediction

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Authors: Rahma Souli-Jbali, Minyar Sassi Hidri, Rahma Ben Ayed

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Grid of computing nodes has emerged as a representative means of connecting distributed computers or resources scattered all over the world for the purpose of computing and distributed storage. Since fault tolerance becomes complex due to the availability of resources in decentralized grid environment, it can be used in connection with replication in data grids. The objective of our work is to present fault tolerance in data grids with data replication-driven model based on clustering. The performance of the protocol is evaluated with Omnet++ simulator. The computational results show the efficiency of our protocol in terms of recovery time and the number of process in rollbacks.

Keywords: data grids, fault tolerance, clustering, chandy-lamport

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Authors: George Vernon Byrd, Bhim Bahadur Ghaley, Eri Hayashi

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In urban farming, research and innovation are taking place at an unprecedented pace, and soilless growing technologies are emerging at different rates motivated by different objectives in various parts of the world. Local food production is ultimately a main objective everywhere, but adoption rates and expressions vary with socio-economic drivers. Herein, the status of hydroponics and aquaponics is summarized for four countries with diverse socio-economic settings: Europe (Denmark), Asia (Japan and Nepal) and North America (US). In Denmark, with a strong environmental ethic, soilless growing is increasing in urban agriculture because it is considered environmentally friendly. In Japan, soil-based farming is being replaced with commercial plant factories using advanced technology such as complete environmental control and computer monitoring. In Nepal, where rapid loss of agriculture land is occurring near cities, dozens of hydroponics and aquaponics systems have been built in the past decade, particularly in “non-traditional” sites such as roof tops to supplement family food. In the US, where there is also strong interest in locally grown fresh food, backyard and commercial systems have proliferated. Nevertheless, soilless growing is still in the research and development and early adopter stages, and the broad contribution of hydroponics and aquaponics to food security is yet to be fully determined. Nevertheless, current adoption of these technologies in diverse environments in different socio-economic settings highlights the potential contribution to food security with social and environmental benefits which contribute to several Sustainable Development Goals.

Keywords: aquaponics, hydroponics, soilless agriculture, urban agriculture

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Authors: Majdah Alnefaie

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The ‘netnographic study’ and data mining have been used to monitor the public interaction on Social Media Sites (SMSs) to understand what the motivational factors influence the Saudi intentions regarding allowing women driving in Saudi Arabia in 2018. The netnographic study monitored the publics’ textual and visual communications in Twitter, Snapchat, and YouTube. SMSs users’ communications method is also known as electronic word of mouth (eWOM). Netnography methodology is still in its initial stages as it depends on manual extraction, reading and classification of SMSs users text. On the other hand, data mining is come from the computer and physical sciences background, therefore it is much harder to extract meaning from unstructured qualitative data. In addition, the new development in data mining software does not support the Arabic text, especially local slang in Saudi Arabia. Therefore, collaborations between social and computer scientists such as ‘netnographic study’ and data mining will enhance the efficiency of this study methodology leading to comprehensive research outcome. The eWOM communications between individuals on SMSs can promote a sense that sharing their preferences and experiences regarding politics and social government regulations is a part of their daily life, highlighting the importance of using SMSs as assistance in promoting participation in political and social. Therefore, public interactions on SMSs are important tools to comprehend people’s intentions regarding the new government regulations in the country. This study aims to answer this question, "What factors influence the Saudi Arabians' intentions of Saudi female's car-driving in 2018". The study utilized qualitative method known as netnographic study. The study used R studio to collect and analyses 27000 Saudi users’ comments from 25th May until 25th June 2018. The study has developed data collection model that support importing and analysing the Arabic text in the local slang. The data collection model in this study has been clustered based on different type of social networks, gender and the study main factors. The social network analysis was employed to collect comments from SMSs owned by governments’ originations, celebrities, vloggers, social activist and news SMSs accounts. The comments were collected from both males and females SMSs users. The sentiment analysis shows that the total number of positive comments Saudi females car driving was higher than negative comments. The data have provided the most important factors influenced the Saudi Arabians’ intention of Saudi females car driving including, culture and environment, freedom of choice, equal opportunities, security and safety. The most interesting finding indicted that women driving would play a role in increasing the individual freedom of choice. Saudi female will be able to drive cars to fulfill her daily life and family needs without being stressed due to the lack of transportation. The study outcome will help Saudi government to improve woman quality of life by increasing the ability to find more jobs and studies, increasing income through decreasing the spending on transport means such as taxi and having more freedom of choice in woman daily life needs. The study enhances the importance of using use marketing research to measure the public opinions on the new government regulations in the country. The study has explained the limitations and suggestions for future research.

Keywords: netnographic study, data mining, social media, Saudi Arabia, female driving

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Authors: Muhammet Dursun Kaya, Hasan Asil

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One of the most important factors of research and development is the deep insight into the evolutions of scientific development. The state-of-the-art tools and instruments can considerably assist the researchers, and many of the world organizations have become aware of the advantages of data mining for the acquisition of the knowledge required for the unstructured data. This paper was an attempt to review the articles on the information technology published in the past five years with the aid of data mining. A clustering approach was used to study these articles, and the research results revealed that three topics, namely health, innovation, and information systems, have captured the special attention of the researchers.

Keywords: information technology, data mining, scientific development, clustering

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Authors: M. Sai Veerendra

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Today, money laundering (ML) poses a serious threat not only to financial institutions but also to the nation. This criminal activity is becoming more and more sophisticated and seems to have moved from the cliché of drug trafficking to financing terrorism and surely not forgetting personal gain. Most of the financial institutions internationally have been implementing anti-money laundering solutions (AML) to fight investment fraud activities. However, traditional investigative techniques consume numerous man-hours. Recently, data mining approaches have been developed and are considered as well-suited techniques for detecting ML activities. Within the scope of a collaboration project on developing a new data mining solution for AML Units in an international investment bank in Ireland, we survey recent data mining approaches for AML. In this paper, we present not only these approaches but also give an overview on the important factors in building data mining solutions for AML activities.

Keywords: data mining, clustering, money laundering, anti-money laundering solutions

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Authors: Juan Carlos Briones Macias

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Currently, the Huancavilca City Park in Guayaquil is an abandoned public space that is discovering a growing problem of insecurity, where various problems have been perceived, such as the lack of green areas, deteriorating furniture, insufficient lighting, the use of inadequate cladding materials and very sunny areas due to the lack of planning in the design of green areas. The objective of this scientific article is to redesign Huancavilca Park through public space design strategies for more attractive and comfortable areas, becoming a point of interaction in a safe and accessible way. A mixed methodology (qualitative and quantitative) was applied, obtaining information based on surveys, interviews, field observations, and systematizing the data in the traditional weighting of the structuring aspects of the park. The results were obtained from the methodological design scheme of iterative analysis of public spaces by Jan Güell. It is concluded that the use of urban strategies in the structuring elements of the park, such as vegetation, furniture, generating new activities, and security interventions, will specifically solve all the problems of the Huancavilca Park tested in a Pareto 80/20 Diagram.

Keywords: public space, green areas, vegetation, street furniture, urban analysis

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Authors: Noureddine Mohtaram, Jeremy Patrix, Jerome Verny

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As an enormous number of online services have been developed into web applications, security problems based on web applications are becoming more serious now. Most intrusion detection systems rely on each request to find the cyber-attack rather than on user behavior, and these systems can only protect web applications against known vulnerabilities rather than certain zero-day attacks. In order to detect new attacks, we analyze the HTTP protocols of web servers to divide them into two categories: normal attacks and malicious attacks. On the other hand, the quality of the results obtained by deep learning (DL) in various areas of big data has given an important motivation to apply it to cybersecurity. Deep learning for attack detection in cybersecurity has the potential to be a robust tool from small transformations to new attacks due to its capability to extract more high-level features. This research aims to take a new approach, deep learning to cybersecurity, to classify these two categories to eliminate attacks and protect web servers of the defense sector which encounters different web traffic compared to other sectors (such as e-commerce, web app, etc.). The result shows that by using a machine learning method, a higher accuracy rate, and a lower false alarm detection rate can be achieved.

Keywords: anomaly detection, HTTP protocol, logs, cyber attack, deep learning

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Authors: Marina Vicario, Amadeo Argüelles, Pilar Gómez, Carlos Hernández

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In this paper, the Computer Research Network of the National Polytechnic Institute of Mexico proposes a paradigmatic model for the inference of cognitive patterns in digital learning systems. This model leads to metadata architecture useful for analysis and prediction in online learning systems; especially on MOOc's architectures. The model is in the design phase and expects to be tested through an institutional of courses project which is going to develop for the MOOc.

Keywords: cognitive footprints, learning analytics, predictive learning, digital learning, educational computing, educational informatics

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Authors: Evangeline Mbah, Margret Okeke, Agbo Joseph

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Agriculture was primarily a rural activity in Nigeria, but due to increasing demand for food and jobs for many urban dwellers, it became necessary for urban households to embark on farming as a means of improving household food security and additional income for economic empowerment. Urban agriculture serves as a veritable tool for poverty reduction among people living in urban areas mostly low-income earners and unemployed. The survey was conducted to identify key challenges encountered by households in Makurdi metropolis of Benue state, Nigeria who are engaged in urban agriculture. A well-structured questionnaire was used to collect data from a sample of respondents used for the study. Data were analyzed using frequency, percentage, mean score and standard deviation. Results show that a greater percentage (46.0%) of the respondents engaged in cultivation of leafy vegetable, 22.0% cultivated cassava, 21.0% planted sweet potato, 18.0% cultivated tomato while 56.0% reared poultry, 23.0% kept goat, among others. Sources of agricultural information indicated by the respondents were family members/relations (85.0%), friends/neighbours (73.0%), radio (68.0%), extension agents (57.0%), etc. Major challenges encountered by the respondents in urban agriculture include inadequate size of farmland (M= 2.72), lack of access to credit facilities (M= 2.63), lack of funds (M= 2.50), high cost of labour (M= 2.49), insecurity of lands (M= 2.46), theft of crops at maturity (M= 2.38), lack of farm inputs such as improved varieties of seeds, fertilizer and exotic breeds of livestock (M= 2.23), destruction of crops by stray farm animals (M= 1.96), among others. The study recommends that there is a need for adequate provision of farm inputs by the government at all levels at a subsidized rate in order to reduce the cost of production and enhance optimum productivity.

Keywords: urban, agriculture, household, challenges, Makurdi, Nigeria

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Authors: Hrudaya Kamasani

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The cultural prevalence of vigilante justice is sustained through the social sanction for foregoing a judicial trial to determine guilt. Precisely due to its roots in social sanction, it has repercussions as more than just being symptomatic of cultural values that condone violence. In the long term, the practice of vigilante justice as a response to incidents of sexual violence, while veiled in civic discontent over the standards of women’s security in society, can adversely affect the discourse on sexual violence. To illustrate the impact that acts of vigilante justice can have in prematurely ending a budding discourse on sexual violence, the paper reviews three cases of heinous crimes committed against women in India that gained popular attention in the discursive spaces. The 2012 Nirbhaya rape and murder case in Delhi demonstrates how the criminal justice system can spur a social movement and can result in legislative changes and a discourse that challenged a wide range of socio-cultural issues of women’s security and treatment. The paper compares it with two incidents of sexual violence in India that ended with the suspects being killed in the name of vigilante justice that had wide social sanction. The two cases are the 2019 extrajudicial killing of Priyanka Reddy rape and murder case suspects in Hyderabad and the 2015 mob lynching of an accused in a rape case in Dimapur. The paper explains why the absence of judicial trials in sexual violence cases results in ending any likelihood of the instances inspiring civic engagement with the discourse on sexual violence.

Keywords: sexual violence, vigilante justice, extrajudicial killing, cultural values of violence, Nirbhaya rape case, mob violence

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Authors: Jin Xu

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5G network developers need to satisfy the necessary requirements of additional capacity from massive users and spectrally efficient wireless technologies. Therefore, the significant amount of underutilized spectrum in network is motivating operators to combine long-term evolution (LTE) with intelligent spectrum management technology. This new LTE intelligent spectrum management in unlicensed band (LTE-U) has the physical layer topology to access spectrum, specifically the 5-GHz band. We proposed a new intelligent cloud RAN for 5G.

Keywords: cloud radio access network, wireless network, cloud computing, multi-agent

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Authors: Reshan Perera, Sarith Munasinghe, Himali Lakshika, Yasith Perera, Hasitha Walakadawattage, Udayanga Hemapala

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This research presents a reconfigurable architecture for residential microgrid systems utilizing Z-Source Inverter (ZSI) to optimize solar photovoltaic (SPV) system utilization and enhance grid resilience. The proposed system addresses challenges associated with high solar power penetration through various modes, including current control, voltage-frequency control, and reactive power control. It ensures uninterrupted power supply during grid faults, providing flexibility and reliability for grid-connected SPV customers. Challenges and opportunities in reactive power control for microgrids are explored, with simulation results and case studies validating proposed strategies. From a control and power perspective, the ZSI-based inverter enhances safety, reduces failures, and improves power quality compared to traditional inverters. Operating seamlessly in grid-connected and islanded modes guarantees continuous power supply during grid disturbances. Moreover, the research addresses power quality issues in long distribution feeders during off-peak and night-peak hours or fault conditions. Using the Distributed Static Synchronous Compensator (DSTATCOM) for voltage stability, the control objective is nighttime voltage regulation at the Point of Common Coupling (PCC). In this mode, disconnection of PV panels, batteries, and the battery controller allows the ZSI to operate in voltage-regulating mode, with critical loads remaining connected. The study introduces a structured controller for Reactive Power Controlling mode, contributing to a comprehensive and adaptable solution for residential microgrid systems. Mathematical modeling and simulations confirm successful maximum power extraction, controlled voltage, and smooth voltage-frequency regulation.

Keywords: reconfigurable architecture, solar photovoltaic, microgrids, z-source inverter, STATCOM, power quality, battery storage system

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Authors: Kisik Song, Kyuwoong Kim, Sungjoo Lee

Abstract:

Many global firms and corporations derive new technology and opportunity by identifying vacant technology from patent analysis. However, previous studies failed to focus on technologies that promised continuous growth in industrial fields. Most studies that derive new technology opportunities do not test practical effectiveness. Since previous studies depended on expert judgment, it became costly and time-consuming to evaluate new technologies based on patent analysis. Therefore, research suggests a quantitative and systematic approach to technology evaluation indicators by using patent data to and from customer communities. The first step involves collecting two types of data. The data is used to construct evaluation indicators and apply these indicators to the evaluation of new technologies. This type of data mining allows a new method of technology evaluation and better predictor of how new technologies are adopted.

Keywords: data mining, evaluating new technology, technology opportunity, patent analysis

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Authors: Parsa Mahdavi, M. Amin Hariri-Ardebili

Abstract:

The development of accurate machine learning and deep learning models traditionally demands hands-on expertise and a solid background to fine-tune hyperparameters. With the continuous expansion of datasets in various scientific and engineering domains, researchers increasingly turn to machine learning methods to unveil hidden insights that may elude classic regression techniques. This surge in adoption raises concerns about the adequacy of the resultant meta-models and, consequently, the interpretation of the findings. In response to these challenges, automated machine learning (AutoML) emerges as a promising solution, aiming to construct machine learning models with minimal intervention or guidance from human experts. AutoML encompasses crucial stages such as data preparation, feature engineering, hyperparameter optimization, and neural architecture search. This paper provides a comprehensive overview of the principles underpinning AutoML, surveying several widely-used AutoML platforms. Additionally, the paper offers a glimpse into the application of AutoML on various engineering datasets. By comparing these results with those obtained through classical machine learning methods, the paper quantifies the uncertainties inherent in the application of a single ML model versus the holistic approach provided by AutoML. These examples showcase the efficacy of AutoML in extracting meaningful patterns and insights, emphasizing its potential to revolutionize the way we approach and analyze complex datasets.

Keywords: automated machine learning, uncertainty, engineering dataset, regression

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