Recent Submissions

  • Comparing the impact of internet of things and cloud computing on organisational behavior: a survey

    García-Tadeo, Diego A.; Reddy Peram, Dattatreya; Suresh Kumar, K.; Vives, Luis; Sharma, Trishu; Manoharan, Geetha (Elsevier Ltd, 2022-01-01)
    Cloud computing is about delivery of different computing services involving databases, analytics, software, networking with the use of internet to enhance innovation, incorporate flexibility in resources and broaden profitability. However, Internet of Things (IoT) is an essential system for interrelating computer devices, digital machines, people and others which are offered with unique identifiers where data can be transferred with human involvement and wireless network. 42% of organisations in UK use cloud computing. The problem with cloud computing revolves around security and privacy issues as data is stored by a third party from inside or outside of the organisation leading to broken authentication, compromising of credentials and others. The use of IoT is vulnerable as it provides connectivity to devices, machines and people therefore, it needs to contain more storage that is made from cloud facilities. Survey has been conducted where primary quantitative method has been considered to obtain data from 101 managers of the organisation that has adopted cloud computing and IoT. However, 8 close-ended questions have been asked to 101 managers. Positivism philosophy has been used to make quantifiable observations along with descriptive design and others. The results and discussion will analyse responses of the respondents after conducting statistical analysis. However, research has been revolving around making a comparison between using cloud computing and IoT along with analysing organisational behaviour.
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  • Intelligent gravitational search random forest algorithm for fake news detection

    Natarajan, Rathika; Mehbodniya, Abolfazl; Rane, Kantilal Pitambar; Jindal, Sonika; Hasan, Mohammed Faez; Vives, Luis; Bhatt, Abhishek (World Scientific, 2022-01-01)
    Online social media has made the process of disseminating news so quick that people have shifted their way of accessing news from traditional journalism and press to online social media sources. The rapid rotation of news on social media makes it challenging to evaluate its reliability. Fake news not only erodes public trust but also subverts their opinions. An intelligent automated system is required to detect fake news as there is a tenuous difference between fake and real news. This paper proposes an intelligent gravitational search random forest (IGSRF) algorithm to be employed to detect fake news. The IGSRF algorithm amalgamates the Intelligent Gravitational Search Algorithm (IGSA) and the Random Forest (RF) algorithm. The IGSA is an improved intelligent variant of the classical gravitational search algorithm (GSA) that adds information about the best and worst gravitational mass agents in order to retain the exploitation ability of agents at later iterations and thus avoid the trapping of the classical GSA in local optimum. In the proposed IGSRF algorithm, all the intelligent mass agents determine the solution by generating decision trees (DT) with a random subset of attributes following the hypothesis of random forest. The mass agents generate the collection of solutions from solution space using random proportional rules. The comprehensive prediction to decide the class of news (fake or real) is determined by all the agents following the attributes of random forest. The performance of the proposed algorithm is determined for the FakeNewsNet dataset, which has sub-categories of BuzzFeed and PolitiFact news categories. To analyze the effectiveness of the proposed algorithm, the results are also evaluated with decision tree and random forest algorithms. The proposed IGSRF algorithm has attained superlative results compared to the DT, RF and state-of-the-art techniques.
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  • Data Visualization Techniques for Monitoring Real-Time Information of Cold Chain

    Rivas Tucto, Jerson; Castillo Talexio, Nora; Shiguihara Juárez, Pedro (Springer Science and Business Media Deutschland GmbH, 2021-01-01)
    Real-time monitoring of temperature is a critical factor in ensuring the integrity of food during the cold chain. In this work, we compare techniques related to real-time data visualization to contribute to more efficient monitoring of the cold chain. Three real-time data display attributes were evaluated, and we constructed a dataset based on the Frisbee database (CDD). In this paper, we proposed graphics containing different line and area techniques to be evaluated for a specialist. The proposed graphs contained the line and area techniques that, when performing the experiment, obtained a higher success rate compared to the auto-charting technique. However, it was evidenced that elements such as color facilitate the detection of anomalies and trends in temperature change due to its high percentage of effectiveness in the results.
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  • Telepresence Technological Model Applied to Primary Education

    Yovera Chavez, David; Villena Romero, Gonzalo; Barrientos Villalta, Alfredo; Cuadros Galvez, Miguel (Institute of Electrical and Electronics Engineers Inc., 2020-09-01)
    This research paper proposes a low-cost telepresence technological model focused on primary education. Its aim is to give students a new resource/communication channel for classes, which would be used when they cannot attend school due to health problems that do not affect their learning process. This solution seeks students to not be passive listeners during a session, but that they interact with their classmates and teachers during class. To validate the model, a telepresence platform based on WebRTC was developed. It was tested in three schools in different geographical areas belonging to socioeconomic sector C, collecting data from the students who tested the tool, as well as from classmates, teachers, and parents.
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  • Prediction of financial product acquisition for Peruvian savings and credit associations

    Vargas, Emmanuel Roque; Cadillo Montesinos, Ricardo; Mauricio, David (Institute of Electrical and Electronics Engineers Inc., 2020-09-30)
    Savings and credit cooperatives in Peru are of great importance for their participation in the economy, reaching in 2019, deposits and deposits and assets of more than 2,890,191,000. However, they do not invest in predictive technologies to identify customers with a higher probability of purchasing a financial product, making marketing campaigns unproductive. In this work, a model based on machine learning is proposed to identify the clients who are most likely to acquire a financial product for Peruvian savings and credit cooperatives. The model was implemented using IBM SPSS Modeler for predictive analysis and tests were performed on 40,000 records on 10,000 clients, obtaining 91.25% accuracy on data not used in training.
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  • Blockchain-based Website Solution for Controlling the Authorized Sale of Drugs in Peru

    Garcia, Herbert Melendez; Cortez, Manuel Maza; Amaya, Edgar Diaz (Institute of Electrical and Electronics Engineers Inc., 2020-10-21)
    Drug counterfeiting or adulteration is a worldwide concern due to the serious consequences they generate, especially in the health and economic sectors. This concern is greater in Peru, as it is among the top five countries with drug counterfeiting incidents in the Americas, according to a study carried out in 2018 by the Pan American Health Organization. In this paper, we present our project, which aims at implementing a technological solution that provides reliable information on the origin and authenticity of these products in Peru to the drug consumer user, preserving the security and integrity of the exposed information using Blockchain technology. Likewise, it allows showing detailed drug characteristics, such as: composition, pharmaceutical form, active ingredients, among other relevant information. The technological solution, proposed by our project, aims at publishing the commercial origin of drugs from their sale in laboratories and distributors to the sale to the public in pharmacies. In the development of this paper, a bibliographic review of research on the use of blockchain technology is presented, as well as its benefits in the health sector, the architecture used by the system and the conceptual commercialization chain that supports it, and the qualitative and quantitative validation for the drug query service is shown.
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  • Extended Model for the Early Skin Cancer Detection Using Image Processing

    Poma, Jonathan Miguel Campos; Dominguez, Emily Yanira De La Cruz; Armas-Aguirre, Jimmy; Gonzalez, Leonor Gutierrez (IEEE Computer Society, 2020-06-01)
    In this research paper, we proposed an extended model for the early detection of skin cancer... The purpose is reduce the waiting time to obtaining a diagnosis, in addition, the function of the dermatoscope has been digitized by using a Smartphone and magnifying lenses as an accessory the mobile device. The proposed model has five phases: 1. The patient is attended by a general practitioner or nurse previously trained in any health center which has WiFi or mobile network connectivity to record their data and capture the skin lesion that will be analyzed. 2) The image will be in the cloud storage, which at the same time feeds an exclusive access website of dermatologists.3) Images are analyzed in real time using an image recognition service provided by IBM, which is integrated into a cloud-hosted web platform and an-Android application. 4)The result of the image processing is visualized by the dermatologist who makes a remote diagnosis.5) This diagnosis is received by the general practitioner or nurse, responsible for transmitting the diagnosis and treatment to the patient. This model was validated in a group of 60 patients, where 28 suffer from skin cancer in the early stage, 12 in the late stage and 20 are healthy patients, in a network of clinics in Lima, Peru. The obtained result was 97.5% of assertiveness on the analyzed skin lesions and 95% in healthy patients.
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  • Technological solution for the identification and reduction of stress level using wearables

    Raymondi, Luis Guillermo Antezana; Guzman, Fabricio Eduardo Aguirre; Armas-Aguirre, Jimmy; Agonzalez, Paola (IEEE Computer Society, 2020-06-01)
    In this article, a technological solution is proposed to identify and reduce the level of mental stress of a person through a wearable device. The proposal identifies a physiological variable: Heart rate, through the integration between a wearable and a mobile application through text recognition using the back camera of a smartphone. As part of the process, the technological solution shows a list of guidelines depending on the level of stress obtained in a given time. Once completed, it can be measured again in order to confirm the evolution of your stress level. This proposal allows the patient to keep his stress level under control in an effective and accessible way in real time. The proposal consists of four phases: 1. Collection of parameters through the wearable; 2. Data reception by the mobile application; 3. Data storage in a cloud environment and 4. Data collection and processing; this last phase is divided into 4 sub-phases: 4.1. Stress level analysis, 4.2. Recommendations to decrease the level obtained, 4.3. Comparison between measurements and 4.4. Measurement history per day. The proposal was validated in a workplace with people from 20 to 35 years old located in Lima, Peru. Preliminary results showed that 80% of patients managed to reduce their stress level with the proposed solution.
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  • Information security risk management model for mitigating the impact on SMEs in Peru

    Garay, Daniel Felipe Carnero; Marcos Antonio, Carbajal Ramos; Armas-Aguirre, Jimmy; Molina, Juan Manuel Madrid (IEEE Computer Society, 2020-06-01)
    This paper proposes an information security risk management model that allows mitigating the threats to which SMEs in Peru are exposed. According to studies by Ernst Young, 90% of companies in Peru are not prepared to detect security breaches, and 51% have already been attacked. In addition, according to Deloitte, only 10% of companies maintain risk management indicators. The model consists of 3 phases: 1. Inventory the information assets of the company, to conduct the risk analysis of each one; 2. Evaluate treatment that should be given to each risk, 3. Once the controls are implemented, design indicators to help monitor the implemented safeguards. The article focuses on the creation of a model that integrates a standard of risk management across the company with a standard of IS indicators to validate compliance, adding as a contribution the results of implementation in a specific environment. The proposed model was validated in a pharmaceutical SME in Lima, Peru. The results showed a 71% decrease in risk, after applying 15 monitoring and training controls, lowering the status from a critical level to an acceptable level between 1.5 and 2.3, according to the given assessment.
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  • Technological Architecture with Low Cost Sensors to Improve Physical Therapy Monitoring

    Zambrano, Ericsson Ocas; Munoz, Kemeli Reyes; Armas-Aguirre, Jimmy; Gonzalez, Paola A. (IEEE Computer Society, 2020-06-01)
    In this article, we propose a wireless monitoring solution for gait parameters using low-cost sensors in the physical rehabilitation of patients with gait disorders. This solution consists of infrared speed sensors (IRSS), force-sensing Resistor (FSR) and microcontrollers placed in a walker. These sensors collect the pressure distribution on the walker's handle and the speed of the steps during therapy session. The proposal allows to improve the traditional physiotherapy session times through a mobile application to perform the monitoring controlled by a health specialist in real time. The proposed solution consists of 4 stages: 1. Obtaining gear parameters, 2. Data transmission, 3. Information Storage and 4. Data collection and processing. Solution was tested with 10 patients from a physical rehabilitation center in Lima, Peru. Preliminary results revealed a significant reduction in the rehabilitation session from 25 to 5.2 minutes.
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  • Matrix of guidelines to improve the understandability of non-expert users in process mining projects

    Teran, Bryhan Chise; Bravo, Jimmy Manuel Hurtado; Armas-Aguirre, Jimmy; Mayorga, Santiago Aguirre (IEEE Computer Society, 2020-06-01)
    Process Mining is a discipline that recognizes three types of analysis: Discovery, monitoring, and process improvement. Organizations are focusing on redesigning and automating their major processes, according to a report published in 2018 [1]. In this way, a challenge n process mining is to show the results of the process analysis in a way that is understandable to non-expert users. Therefore, this research paper introduces a matrix of guidelines to guide process mining specialists/tool developers to improve the results of the analysis in process mining projects. This matrix is composed of 2 study fields that throughout the literature have been merging their virtues. First, process mining under 2 of its 3 types of projects: (1) based on objectives and (2) based on questions. The last type is based on data (exploratory analysis). Second, visualization of data with its techniques to represent data graphically. This research proposes a matrix of guidelines that integrates the discipline of process mining and the set of data visualization techniques based on the purpose of each graph (technique), the question / objective to be achieved and the importance that colors take in the analysis results in the process mining projects.
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  • Reduction of complications generated by Type 2 Diabetes Mellitus using a remote health care solution in Peru

    Marcos, Dora Vanesa Diaz; Romero, Jhezsenia Huaman; Aguirre, Jimmy Armas; Gonzalez, Paola A. (IEEE Computer Society, 2020-06-01)
    In this article, we propose a technological architecture that supports the remote medical care service for elderly people suffering from Type 2 Diabetes Mellitus in Peru. The problem is based on the limitations that elderly people have with compliance with medical controls, which leads to increased complications of the disease and the patient's quality of life. The design of the technological architecture is based on 6 layers: 1) devices, 2) software, 3) channels, 4) data storage, 5) data processing and 6) information visualization. Through the solution, patients are able to autonomously manage their disease through periodic glucose control and the execution of an updated treatment in real time. In the same way, the specialist doctor periodically analyzes the glucose level and it is notified in real time about the out-of-range indicators, which allows him to make treatment decisions as the anomaly occurs. The focus of the solution is to reduce the complications generated by the disease through efficient glucose control and periodic medical advice. The solution was validated in a nursing home with adults over 60 and an endocrinologist from a medical office in Lima, Peru. For the study, we measured the constancy of the glucose record, the average response time of the doctor in case of emergencies or indicators out of range, the percentage of reduction of complications and the level of satisfaction of the Telehomecare solution in older adults. The results show that patients interact more frequently as they adapt the solution as part of their daily routine. On the other hand, the response time was approximately 4.13 minutes from the anomaly record. The percentage of complication reduction was 14% and the level of satisfaction of the solution was reflected in the dimensions of the response time and understanding of the user's need.
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  • Design of a hexapod robot using artificial intelligence for the routes of the peruvian andes

    Abarca, Arnold; Quispe, Grimaldo; Zapata-Ramirez, Gianpierre; Raymundo-Ibanez, Carlos; Rivera, Luis (Institute of Electrical and Electronics Engineers Inc., 2019-11-01)
    This paper presents an alternative solution to improve the locomotion system of a hexapod robot by artificial intelligence. Through an optimal design to achieve static stability, dynamic stability and optimize energy consumption through an autonomous system that is able to perform trajectories without any inconvenience. For the robot to move without flaws has certain restrictions in design (weight, size, materials, etc.) The hexapod has a high degree of movement and this allows many trajectories handle at the time of travel. Using sensors under certain working conditions we will obtain the necessary data and signals to satisfactorily comply with the hexapod robot design.
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  • Cloud-based open-source enterprise content management model at a SME operating in the manufacturing sector

    Montesinos-Rosales, Andrea; Salas-Villacorta, Sebastian; Mauricio-Sanchez, David; Raymundo-Ibañez, Carlos (Association for Computing Machinery, Inc, 2019-11-12)
    Every year, small- and medium-sized enterprises (SMEs) expand their participation in the Peruvian market, while facing high internal disorganization issues that stifle their growth. This problem is rooted on the fact that the contents generated by these companies are not usually adequately recorded, managed, and exploited, and thus negatively affecting the organization and their competitiveness levels. Now, although most of this issue may be solved through enterprise content management (ECM) solutions, they are not affordable for most SMEs because of their high prices. Within this context, this study proposes the implementation of a cloud-based open-source ECM model at a manufacturing SME in Peru. Through this model, the company was able to access the benefits of an ECM to restructure the way they manage content, gaining 67% more efficiency, establishing a collaboration channel between employees, suppliers, and customers, and reporting a 93% model adaptation rate among staff members.
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  • Business information architecture for successful project implementation based on sentiment analysis in the tourist sector

    Zapata, Gianpierre; Murga, Javier; Raymundo, Carlos; Dominguez, Francisco; Moguerza, Javier M.; Alvarez, Jose Maria (Springer New York LLC, 2019-12-01)
    In the today’s market, there is a wide range of failed IT projects in specialized small and medium-sized companies because of poor control in the gap between the business and its vision. In other words, acquired goods are not being sold, a scenario which is very common in tourism retail companies. These companies buy a number of travel packages from big companies and due to lack of demand for these packages, they expire, becoming an expense, rather than an investment. To solve this problem, we propose to detect the problems that limit a company by re-engineering the processes, enabling the implementation of a business architecture based on sentimental analysis, allowing small and medium-sized tourism enterprises (SMEs) to make better decisions and analyze the information that most possess, without knowing how to exploit it. In addition, a case study was applied using a real company, comparing data before and after using the proposed model in order to validate feasibility of the applied model.
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  • Lean Manufacturing Model Adapted for Waste Reduction in Peruvian Condiment Production Agri-Businesses

    Mesones-Guillén, Axel; Palacios-Jesús, Lizeth; Carvallo-Munar, Edgardo; Salas-Castro, Rosa; Cardenas-Rengifo, Luis (2021-01-01)
    The Peruvian export supply is primarily based on the segment of dressings and condiments. This paper seeks to adapt lean manufacturing tools using Poka-Yoke techniques and process standardization, which may align with existing processes to prevent production errors. This combination of tools is expected to reduce the percentage of waste generated throughout the condiment production process. Subsequent to an initial evaluation of the current method combined with the application of both the tools, 11.4% waste reduction was ultimately reported.
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  • Wearable Technology for Presumptive Diagnosis of High Blood Pressure Based on Risk Factors

    Prada, Eithel Josue Meza; Agullar, Helgar Miguel Angel Herrera; Armas-Aguirre, Jimmy; Gonzalez, Paola A. (2021-01-01)
    In this paper, we propose a technological solution integrated to a wearable device that allows measuring some physiological variables such as body mass index (BMI), steps walked in a determined day, burned calories, blood pressure and other risk factors associated with the Framingham´s score. The objective of this article is to identify the evolutionary pattern of the Framingham’s score each day in order to determine a presumptive diagnosis of high blood pressure. The technological solution was validated in the social insurance of a public hospital in Lima, Perú. The preliminary results obtained in a diagnostic test show a sensitivity level of 83.33%, a level of precision better than a traditional Framingham´s score for presumptive diagnosis of high blood pressure. Our proposal contributes to the patient’s awareness about the bad routine habits related to lifestyle and promotes the empowerment of data in order to make some changes that influence on the reduction of cardiovascular disease risk.
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  • Evaluation Method of Variables and Indicators for Surgery Block Process Using Process Mining and Data Visualization

    Rojas-Candio, Piero; Villantoy-Pasapera, Arturo; Armas-Aguirre, Jimmy; Aguirre-Mayorga, Santiago (2021-01-01)
    In this paper, we proposed a method that allows us to formulate and evaluate process mining indicators through questions related to the process traceability, and to bring about a clear understanding of the process variables through data visualization techniques. This proposal identifies bottlenecks and violations of policies that arise due to the difficulty of carrying out measurements and analysis for the improvement of process quality assurance and process transformation. The proposal validation was carried out in a health clinic in Lima (Peru) with data obtained from an information system that supports the surgery block process. Finally, the results contribute to the optimization of decision-making by the medical staff involved in the surgery block process.
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  • Reference Model to Identify the Maturity Level of Cyber Threat Intelligence on the Dark Web

    Santos, Ricardo Meléndez; Gallardo, Anthony Aguilar; Aguirre, Jimmy Armas (2021-01-01)
    In this article, we propose a reference model to identify the maturity level of the cyber intelligence threat process. This proposal considers the dark web as an important source of cyber threats causing a latent risk that organizations do not consider in their cybersecurity strategies. The proposed model aims to increase the maturity level of the process through a set of proposed controls according to the information found on the dark web. The model consists of three phases: (1) Identification of information assets using cyber threat intelligence tools. (2) Diagnosis of the exposure of information assets. (3) Proposal of controls according to the proposed categories and criteria. The validation of the proposal was carried out in an insurance institution in Lima, Peru, with data obtained by the institution. The measurement was made with artifacts that allowed to obtain an initial value of the current panorama of the company. Preliminary results showed 196 emails and passwords exposed on the dark web of which one corresponded to the technology manager of the company under evaluation. With this identification, it was diagnosed that the institution was at a “Normal” maturity level, and from the implementation of the proposed controls, the “Advanced” level was reached.
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  • A Technological Solution to Identify the Level of Risk to Be Diagnosed with Type 2 Diabetes Mellitus Using Wearables

    Nuñovero, Daniela; Rodríguez, Ernesto; Armas, Jimmy; Gonzalez, Paola (2021-01-01)
    This paper proposes a technological solution using a predictive analysis model to identify and reduce the level of risk for type 2 diabetes mellitus (T2DM) through a wearable device. Our proposal is based on previous models that use the auto-classification algorithm together with the addition of new risk factors, which provide a greater contribution to the results of the presumptive diagnosis of the user who wants to check his level of risk. The purpose is the primary prevention of type 2 diabetes mellitus by a non-invasive method composed of the phases: (1) Capture and storage of risk factors; (2) Predictive analysis model; (3) Presumptive results and recommendations; and (4) Preventive treatment. The main contribution is in the development of the proposed application.
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