Ebook: Advances in Digital Technologies

International Conference on Applications of Digital Information and Web Technologies was the 8th event of the series organized since 2008 with the aim at building infrastructure necessary for large-scale development of Web technologies that make easy access to digital information in its every form regardless of the user's need. Over these years, the ICADIWT conference has created its own research community of participants from very many countries who attend the event every time with intention to demonstrate and discuss the essential details of their research findings.

The ICADIWT conference series is organized by the Indian Digital Information Research Foundation, a publisher of academic journals in computer and information science. The 8th ICADIWT conference was held between the 29th and 31st March at the Autonomous University of Ciudad Juarez, Chihuahua, Mexico. This year Professor Vladik Kreinovichand Professor Luc Longpre, bothfrom Computer Science Department, University of Texas at El Paso, Texas, USA honored the conference with their keynote speeches. Dr. Ricardo Rodriguez Jorge from the Autonomous University of Ciudad Juarez, Chihuahua, Mexico gave the third keynote speech.

The scope of the ICADIWT 2017 conference covers the following research areas: Internet Communication, Internet Technologies, Web Applications, Internet Software, Data Access and Transmission, Digital Communication Software, Digital Networks, Web Communication Interfaces, Adaptive Systems, Internet of Things, Internet of Everything, Augmented Reality, Databases and applications, Web Systems Engineering Design, Intelligent Agent systems, Semantic Web Studies, Adaptive Web applications and personalization, Actuators and sensors, Robotics and Machine Vision, Vibration and noise control, Smart structures, Motion Control MEMS, Control, Automation, Human-Machine Interfaces, Real-time simulation, Digital Technologies for Aerospace, Digital Technologies for Mechanical design.

This year, 20 papers were accepted for presentation out of 55 submissions reviewed by at least two Review Committee members each, making the overall acceptance rate at 36%. The authors come from Mexico, US, Poland, Nigeria and some other countries.

We would like to express our sincere gratitude to all our Program Committee members as well as the Board of Reviewers for their hard work to ensure a high standard of the ICADIWT 2017 conference papers.

ICADIWT 2017 Editors:

Jolanta Mizera-Pietraszko

Ricardo Rodriguez Jorge

Diego Moisés Almazo Pérez

Pit Pichappan

Most data processing techniques traditionally used in scientific and engineering practice are statistical. These techniques are based on the assumption that we know the probability distributions of measurement errors etc.

In practice, often, we do not know the distributions, we only know the bound Δ on the measurement accuracy – hence, after the get the measurement result , the only information that we have about the actual (unknown) value x of the measured quantity is that x belongs to the interval . Techniques for data processing under such interval uncertainty are called interval computations; these techniques have been developed since 1950s.

In many practical problems, we have a combination of different types of uncertainty, where we know the probability distribution for some quantities, intervals for other quantities, and expert information for yet other quantities. The purpose of this paper is to describe the theoretical background for interval and combined techniques and to briefly describe the existing practical applications.

Computer security and privacy concerns have become a priority for our nation. A traditional approach is to develop strong and intelligent virus and intrusion detection programs. Although this approach is important, we believe this approach will never really put these concerns to rest. A more promising approach for running security and privacy sensitive programs is to be able to run them with guaranteed confidentiality and integrity in spite of a computing environment containing malware. We start with the difficulty of defining privacy and a review of some existing definitions. We continue with different approaches to run programs securely in an insecure environment. This includes white listing and process isolation techniques.

In this paper, artificial neural networks applications in the prediction field are described. The aim is to analyze the potentialities of conventional neural networks, such as feedforward neural networks, recurrent neural networks; and also, the potentialities of nonconventional neural networks composed typically by higher-order neural units. Finally, experimental analysis of long-term prediction of non-stationary time series (Mackey-Glass) is presented as well. The resulting prediction made by the proposed neural models feedforward multilayer perceptron and quadratic neural unit show high prediction accuracy for non-stationary time series.

This paper presents a relatively new approach to show how a web usability classical paradigm can be benefit from quantitative data of a non-classical approach. In a pilot stage, we used experimental eye tracking data acquired from 11 participants faced to a three simple tasks on a web page.

Results show advantages by using eye tracking data to identify and verify some usability problems of a web page. Along the paper, some hints are presented for people interested in measure web usability by using such approach. However, a deeper study should be carried out in order to generalize our results toward the construction of a methodology to be followed by a web developer or interested people in such field of research.

The importance of XML (eXtensible Markup Language) can't be understated; their usefulness may range from data sharing to data transport in software systems. Schema languages describe the structure of an XML document and the common schemas languages are Document Definition Type (DTD), W3C XML Schema and RelaxNG. Applications depend heavily on XML documents to be free of error and this makes it imperative to determine the quality of such schema document. Schema metrics is used to achieve this, and several of them have been proposed in recent years. In this paper we present the existing schema metrics and to make comparative studies on all schema metrics, figuring out the features, advantages and limitations of each metrics.

Facial expressions provide non-verbal information about people's emotional and mental states without the need for verbal communication, so the extraction and automatic tracking of facial components are the main tasks that artificial vision systems must solve in the realm of Human behavior, detection of facial expressions, man-machine interfaces, among other areas. In this work are proposed to use Kinect and the facetracking library to create a system that automatically locates the face and perform an interpretation of its elements to detect the motivation in an activity. The evaluation of the tests of this system obtained for cases where the system determined that the subjects were paying attention was 89.79%. For the cases where the system evaluated that the test subjects did not pay attention was 90.72%.

During recent years, decentralized storage services have emerged as a promising solution to support the IT industry. The decentralized aspect means that there are no central servers. Many of these services are based on cloud computing. Cloud computing is a novel paradigm that has altered our perception of computing infrastructures, software delivery and development models, and has been quickly adopted worldwide. In this way, several IT resources, such as heavy computing, massive storage, and high-capacity networks are offered as services, and these can be accessed from anywhere at any time. However, most popular cloud systems are based on a centralized approach, which introduces several limitations such as storage dependence, privacy, scalability, localization and connectivity. Collaborative infrastructures as peer-to-peer (P2P) networks have emerged as promising solutions for the management and storage of all data. This paper reviews different types of infrastructures as possible solutions to support distributed storage services.

Network coding is a promising technique in the field of Information Theory that has shown improved performance of communication networks. These benefits have been mainly oriented to energy savings or increase throughput. This paper evaluates the impact of network coding in buffer usage during the process of video transmission. In this evaluation, the video packets are encoded in the source while network coding is implemented in the intermediate nodes before forwarding the encoded packets to the end nodes. The received packets are decoded in the end nodes in order to recover the original video signal. The video sequences are compressed under the H.264/MPEG-4 AVC standard, and the experiments are simulated in network simulator (NS-2). The results show that network coding provides savings in the use of buffers in video transmission, which allows decreasing the delay, increasing throughput, and improving the video quality.

With the emergence of cloud computing, it has become easy to store large volumes of data in the cloud to enhance Human Resource Management (HRM), based on the elasticity and scalability that cloud computing offers. This paper proposes the OnibereOdunayoSecurity-4 (OOS-4) security model for Human Resource Information System (HRIS) deployed on a cloud platform. The OOS-4 framework is a holistic and integrated model that is expected to allow for better interrelatedness of the various components of a HRM organization with adequate consideration for security. Furthermore, utilizing the Platform as a Service (PaaS) cloud computing architecture, the model was implemented using the Google App Engine. The result is a scalable application in which the data in storage is encrypted and visible on the Google Cloud Platform data store. The application is secured by proving encryption for data in storage on the Google Cloud Platform. The application will enhance HRM.

About 5.9 million children under the age of 5 died in 2015, Preterm birth, delivery complications and infections source a great number of neonatal deaths. the Sustainable Development goals (SDGs) 3.2 is to end preventable deaths of newborns and children under 5 years of age, with a target to reduce neonatal mortality to at least 12 per 1,000 live births and under-5 mortality to at least as low as 25 per 1,000 live births in all countries. However quality and accessible healthcare service is essential to achieve this goal whereas most undeveloped and developing countries still have poor access to quality healthcare. with the emergences on mobile computing and telemedicine, this work provide diagnostics alternative for childhood infectious diseases using Naïve Bayesian classier which has been proven to be efficient in handling uncertainty as regards learning of incomplete data. In this research, sample data was collected from hospitals to model a pediatric system using Naïve Bayes classifier, which produce a 70% accuracy level suitable for a decision support system. The model was also integrated into a SMS platform to enable ease of usage.

In the current context (year: 2017) there are many medical advances applied to women pregnancy state, however the lack of information at the female young sector and the shortage of mobile tools which provide a satisfactory control of the health of the fetus, they lead to prenatal care problems or to the born ofa baby. This is a proposal generated to be applied at the North Region of the state of Guanajuato, Mexico a zone affected by chronic-degenerative health problems is developed by a team of teachers to control better pregnancy, preventing suffering for the mother and the gestating.

“The Internet of things consist of a system of devices or appliances that are connected to each other, and work together, through networks.” We expect that large corporations that provide their electronic services on a network that can not support adequate solutions will investigate and design new protocols that can control the adopted media. In retrospect, the origin of the vulnerability is analyzed by considering the RFID (Radio Frequency Identification) Middleware, protocols, and architecture of the IoT. Protection in the computer code is considered as a case study.

In the aerodynamic design process students of the University of Juarez City perform studies of Aerodynamics, Stability and Control to approach an optimal performance in flight. Data in this research show methodologies and tools applied to accomplish the final design.

The subject of the paper is to show an optimal aircraft's structure analysis made by students of UACJ using diverse software's such as MATLAB, SolidWorks, Ansys to model and calculate shear force, bending moment, moment of inertia, and all structure loads. The analysis includes wing's structure, fuselage's structure divided by three section, nose, central fuselage and tail, as well as tail assembly. Data in this research show methodologies and tools applied to accomplish the final design.

A Reynolds-Averaged Navier-Stokes (RANS) method has been employed in conjunction with an overlapping moving grid approach to provide accurate resolution of a five-blade propeller flows under both the design and off-design conditions. It is well known that some off-design propeller flow phenomena are dominated by viscous effects and cannot be accurately predicted by the potential flow methods. To properly account for viscous effects, it is necessary to employ accurate and robust numerical methods which can provide detailed resolution of the propeller boundary layer, turbulent wake, leading edge separation, and unsteady ring vortices induced by propeller operations under off-design conditions. In this study, time-domain simulations are performed for the National Advisory Committee for Aeronautics Airfoil 6512 propeller.

A pharmacy is viewed as a physical store contained either in a hospital or as a small venture primarily saddled with the responsibility of dispensing medication to various individuals. While various individuals choose voluntarily to bypass the need for professional medical advice in the area of drug prescription by engaging in self-medication, either as a result of lack of funds or ignorance of what should be done, quality pharmaceutical services could mean the difference between life and death. Problems such as handwriting misinterpretation, cost incurred from frequent calls from pharmacists to physicians, data inconsistency and long waiting lines exist in traditional, manual pharmacy management methods. The goal of this paper therefore is to review the traditional approach to pharmacy management and prescription handling with the view of developing an electronic version. The solution was implemented using the Java programming language due to its platform independence and object-oriented nature. The proposed system addresses the aforementioned problems.

Android is becoming a platform for mobile health-care devices and apps. However, there are many challenges in developing soft real-time, health-care apps for non-dedicated mobile devices like smartphones and tablets. In this paper, we share our experiences in developing the HifoCap app, a mobile app for receiving electroencephalogram (EEG) wave samples from a wearable device, visualizing the received EEG samples, and transmitting them to a cloud storage server. The app is network and data-intensive. We describe the challenges we faced while developing the HifoCap app—e.g., ensuring the soft real-time requirement in the presence of uncertainty on the Android platform—along with our solutions to them. We measure both the time and space efficiency of our app and evaluate the effectiveness of our solutions quantitatively. We believe our solutions to be applicable to other soft real-time apps targeted for non-dedicated Android devices.

This application offers a computerized solution to the registration and geo-referenced visualization of patients, neoplasms and associated environmental contamination. The statistical information generated allows physicians and hospitals to evaluate in a timely manner the behavior of the disease and its association with the pollutants, also by means of algorithms to obtain clusters that allow the delimitation of high risk areas. In general, the application allows the study of pediatric patients with different neoplasms and different contaminants. The particular case presented here is the study and analysis of the electromagnetic contamination associated with leukemia in the infant population of the metropolitan area of Guadalajara, the application allows the registration of the general information of the patient as well as the measurements of electric and magnetic field in High and low frequency. The results shows the geographical distribution of patients, radiation values received, hospitals, schools, high voltage lines, telecommunication antennas and high risk areas for contamination using maps, graphs and data tables. As a conclusion, we now have a real-time tool that facilitates the creation of prevention policies to combat the impact of radiation as one of the possible causes in the development of leukemia in the child population considered as an additional element of health risk public.