3D Modeling Approach for Cultural Heritage Structures: The Case of Virgin of Loreto Chapel in Cusco, Peru

Nowadays, Heritage Building Information Modeling (HBIM) is considered an efficient tool to represent and manage information of Cultural Heritage (CH). The basis of this tool relies on a 3D model generally obtained from a Cloud-to-BIM procedure. There are different methods to create an HBIM model that goes from manual modeling based on the point cloud to the automatic detection of shapes and the creation of objects. The selection of these methods depends on the desired Level of Development (LOD), Level of Information (LOI), Grade of Generation (GOG) as well as on the availability of commercial software. This paper presents the 3D modeling of a stone masonry chapel using Recap Pro, Revit and Dynamo interface following a three-step methodology. The first step consists of the manual modeling of simple structural (e.g., regular walls, columns, floors, wall openings, etc.) and architectural (e.g., cornices, moldings and other minor details) elements using the point cloud as reference. Then, Dynamo is used for generative modeling of complex structural elements such as vaults, infills and domes. Finally, semantic information (e.g., materials, typology, state of conservation, etc.) and pathologies are added within the HBIM model as text parameters and generic models’ families respectively. The application of this methodology allows the documentation of CH following a relatively simple to apply process that ensures adequate LOD, LOI and GOG levels. In addition, the easy implementation of the method as well as the fact of using only one BIM software with its respective plugin for the scan-to-BIM modeling process means that this methodology can be adopted by a larger number of users with intermediate knowledge and limited resources, since the BIM software used has a free student license.

Knowledge, Attitude and Practice of Pregnant Women toward Antenatal Care at Public Hospitals in Sana'a City-Yemen

Background: Antenatal care can be defined as the care provided by skilled healthcare professionals to pregnant women and adolescent girls to ensure the best health conditions for both mother and baby during pregnancy. The components of Antenatal Care (ANC) include risk identification; prevention and management of pregnancy-related or concurrent diseases; and health education and health promotion. The aim of this study: to assess the knowledge, attitude, and practice of pregnant women regarding ANC. Methodology: A descriptive knowledge, attitude, and practice (KAP) study was conducted in public hospitals in Sana'a City, Yemen. The study population included all pregnant women that intended to the prenatal department and clinical outpatient department; the final sample size was 371 pregnant women. A self-administered questionnaire was used to collect the data, statistical package for social sciences SPSS was used to data analysis. The results: Most (79%) of pregnant women had correct answers in total knowledge regarding ANC, and about two-thirds (67%) of pregnant women had performance practice regarding ANC and two-third (68%) of pregnant women had a positive attitude. Conclusions: More than three quarter of pregnant women had good knowledge level, most of pregnant women had moderate practice level, and more than two-thirds of pregnant women had a positive attitude regarding antenatal care. There was a statistically significant association between overall knowledge and practice level toward ANC and demographic characteristics of pregnant women, at P-value ≤ 0.05. Recommendations: we recommended more education and training courses, lecturers, and education sessions in clinical facilitators focused on ANC, which relies on evidence-based interventions provided to women during pregnancy by skilled healthcare providers such as midwives, doctors, and nurses.

Comparison of Numerical and Laboratory Results of Pull-out Test on Soil–Geogrid Interactions

The knowledge of soil–reinforcement interaction parameters is particularly important in the design of reinforced soil structures. The pull-out test is one of the most widely used tests in this regard. The results of tensile tests may be very sensitive to boundary conditions, and more research is needed for a better understanding of the pull-out response of reinforcement, so numerical analysis using the finite element method can be a useful tool for the understanding of the pull-out response of soil-geogrid interaction. The main objective of the present study is to compare the numerical and experimental results of a pull-out test on geogrid-reinforced sandy soils interactions. Plaxis 2D finite element software is used for simulation. In the present study, the pull-out test modeling has been done on sandy soil. The effect of geogrid hardness was also investigated by considering two different types of geogrids. The numerical results curve had a good agreement with the pull-out laboratory results.

Development of a Basic Robot System for Medical and Nursing Care for Patients with Glaucoma

Medical methods to completely treat glaucoma are yet to be developed. Therefore, ophthalmologists manage patients mainly to delay disease progression. Patients with glaucoma are mainly elderly individuals. In elderly people's houses, having an equipment that can provide medical treatment and care can release their family from their care. For elderly people with the glaucoma to live by themselves as much as possible, we developed a support robot having five functions: elderly people care, ophthalmological examination, trip assistance to the neighborhood, medical treatment, and data referral to a hospital. The medical and nursing care robot should approach the visual field that the patients can see at a speed suitable for their eyesight. This is because the robot will be dangerous if it approaches the patients from the visual field that they cannot see. We experimentally developed a robot that brings a white cane to elderly people with glaucoma. The base part of the robot is a carriage, which is a Megarover 1.1, and it has two infrared sensors. The robot moves along a white line on the floor using the infrared sensors and has a special arm, which does not use electricity. The arm can scoop the block attached to the white cane. Next, we also developed a direction detector comprised of a charge-coupled device camera (SVR41ResucueHD; Sun Mechatronics), goggles (MG-277MLF; Midori Anzen Co. Ltd.), and biconvex lenses with a focal length of 25 mm (Edmund Co.). Some young people were photographed using the direction detector, which was put on their faces. Image processing was performed using Scilab 6.1.0 and Image Processing and Computer Vision Toolbox 4.1.2. To measure the people's line of vision, we calculated the iris's center of gravity using five processes: reduction, trimming, binarization or gray scale, edge extraction, and Hough transform. We compared the binarization and gray scale processes in image processing. The binarization process was better than the gray scale process. For edge extraction, we compared five methods: Sobel, Prewitt, Laplacian of Gaussian, fast Fourier transform, and Canny. The Canny method was the optimal extraction method. We performed the Hough transform to search for the main coordinates from the iris's edge, and we found that the Hough transform could calculate the center point of the iris.

Integrating Blockchain and Internet of Things Platforms: An Empirical Study on Immunization Cold Chain

The adoption of Blockchain technology introduces the possibility to decentralize cold chain systems. This adaptation enhances them to be more efficient, accessible, verifiable, and data security. Additionally, the Internet of Things (IoT) concept is considered as an added-value to various application domains. Cargo tracking and cold chain are a few to name. However, the security of the IoT transactions and integrated devices remains one of the key challenges to the IoT application’s success. Consequently, Blockchain technology and its consensus protocols have been used to solve many information security problems. In this paper, we discuss the advantages of integrating Blockchain technology into IoT platform to improve security and provide an overview of existing literature on integrating Blockchain and IoT platforms. Then, we present the immunization cold chain solution as a use-case that could be applied to any critical goods based on integrating Hyperledger fabric platform and IoT platform.

New Chances of Reforming Pedagogical Approach in Secondary English Class in China under the New English Curriculum and National College Entrance Examination Reform

Five years after the newest English curriculum, reform policy was enacted in China and hand-wringing spread among teachers who accused that this is another “wearing new shoes to walk the old road” policy. This paper provides a thoroughly philosophical policy analysis of serious efforts that had been made to support this reform and revealed the hindrances that bridled the reform to yield the desired effect. Blame could be easily put on teachers for their insufficient pedagogical content knowledge, conservative resistance, and the handicaps of large class sizes and limited teaching times and so on. However, the underlying causes for this implementation failure are the interrelated factors in the NCEE-centred education system, such as the reluctance from students, the lack of school and education bureau support and insufficient teacher training. A further discussion of the 2017 to 2020’s NCEE reform on English prompts new possibilities for the authentic pedagogical approach reform in secondary English classes. In all, the pedagogical approach reform at the secondary level is heading towards a brighter future with the initiation of new NCEE reform.

Readiness of Intellectual Capital Measurement: A Review of the Property Development and Investment Industry

In the knowledge economy, the financial indicator is not the unique instrument to gauge the performance of a company. The role of intellectual capital contributing to the company performance is increasing. To measure the company performance due to intellectual capital, the value-added intellectual capital (VAIC) model is adopted to measure the intellectual capital utilization efficiency of the subject companies. The purpose of this study is to review the readiness of measuring intellectual capital for the Hong Kong listed companies in the property development and property investment industry by using VAIC model. This study covers the financial reports from the representative Hong Kong listed property development companies and property investment companies in the period 2014-2019. The findings from this study indicated the industry is ready for IC measurement employing VAIC framework but not yet ready for using the extended VAIC model.

Barriers to the Use of Factoring Accounts Receivables: The Ghanaian Contractor’s Perception

Factoring accounts receivable is widely accepted as an alternative financing source and utilized in almost every industry that sells business-to-business or business-to-government. However, its patronage in the construction industry is very limited as some barriers hinder its application in the construction industry. This study aims at assessing the barriers to the use of factoring accounts receivables in the Ghanaian construction industry. The study adopted the sequential exploratory research method where structured and unstructured questionnaires were conveniently distributed to D1K1 and D2K2 construction firms in Ghana. Using the one-sample t-test and Kendall’s Coefficient of concordance data were analyzed. The most severe challenge concluded is the high cost of factoring patronage. Other critical challenges identified were low knowledge on factoring processes, inadequate access to information on factoring, and high risks involved in factoring. Hence, it is recommended that contractors should be made aware of the prospects of factoring of accounts receivables in the construction industry. This study serves as basis for further rigorous research into factoring of accounts receivables in the industry.

Auditory Brainstem Response in Wave VI for the Detection of Learning Disabilities

The use of brain stem auditory evoked potential (BAEP) is a common way to study the hearing function of people, a way to learn the functionality of a part of the brain neuronal groups that intervene in the learning process by studying the behaviour of wave VI. The latest advances in neuroscience have revealed the existence of different brain activity in the learning process that can be highlighted through the use of innocuous, low-cost and easy-access techniques such as, among others, the BAEP that can help us to detect early possible neurodevelopmental difficulties for their subsequent assessment and cure. To date and the authors best knowledge, only the latency data obtained, observing the first to V waves and mainly in the left ear, were taken into account. This work shows that it is essential to consider both ears; with these latest data, it has been possible to diagnose more precisely some cases than with the previous data had been diagnosed as “normal”despite showing signs of some alteration that motivated the new consultation to the specialist.

Generation of 3D Models Obtained with Low-Cost RGB and Thermal Sensors Mounted on Drones

Nowadays it is common to resort to aerial photography to carry out the prospection and/or exploration of archaeological sites. In recent years, Unmanned Aerial Vehicles (UAVs) have been applied as the vehicles that carry the sensor. This implies certain advantages, such as the possibility of including low-cost sensors, given that these vehicles can carry the sensor at relatively low altitudes. Due to this, low-cost dual sensors have recently begun to be used. This new equipment can collaborate with classic Digital Elevation Models (DEMs) in the exploration of archaeological sites, but this entails the need for a methodological setting to optimize the acquisition, processing and exploitation of the information provided by low-cost dual sensors. This research focuses on the design of an appropriate workflow to obtain 3D models with low-cost sensors carried on UAVs, both in the RGB and thermal domains. All the foregoing has been applied to the archaeological site of Juliobriga, located in Cantabria (Spain). To this end, a flight with this type of sensors has been planned, developed and analyzed. It has been applied to the archaeological site of Juliobriga (Cantabria, Spain). A strong dependence of the thermal sensor on the GSD, and the capability of this technique to interpret underground materials. This research allows to state that the thermal nature of the site does not provide main information about the site itself, but with combination with other types of information, such as the DEM, the typology of materials, etc., can produce very positive results with respect to the exploration and knowledge of the site. 

A Practical Construction Technique to Enhance the Performance of Rock Bolts in Tunnels

In Swedish tunnel construction, a critical issue that has been repeatedly acknowledged is corrosion and, consequently, failure of the rock bolts in rock support systems. The defective installation of rock bolts results in the formation of cavities in the cement mortar that is regularly used to fill the area under the dome plates. These voids allow for water-ingress to the rock bolt assembly, which results in corrosion of rock bolt components and eventually failure. In addition, the current installation technique consists of several manual steps with intense labor works that are usually done in uncomfortable and exhausting conditions, e.g., under the roof of the tunnels. Such intense tasks also lead to a considerable waste of materials and execution errors. Moreover, adequate quality control of the execution is hardly possible with the current technique. To overcome these issues, a non-shrinking/expansive cement-based mortar filled in the paper packaging has been developed in this study which properly fills the area under the dome plates without or with the least remaining cavities, ultimately that diminishes the potential of corrosion. This article summarizes the development process and the experimental evaluation of this technique for the installation of rock bolts. In the development process, the cementitious mortar was first developed using specific cement and shrinkage reducing/expansive additives. The mechanical and flow properties of the mortar were then evaluated using compressive strength, density, and slump flow measurement methods. In addition, isothermal calorimetry and shrinkage/expansion measurements were used to elucidate the hydration and durability attributes of the mortar. After obtaining the desired properties in both fresh and hardened conditions, the developed dry mortar was filled in specific permeable paper packaging and then submerged in water bath for specific intervals before the installation. The tests were enhanced progressively by optimizing different parameters such as shape and size of the packaging, characteristics of the paper used, immersion time in water and even some minor characteristics of the mortar. Finally, the developed prototype was tested in a lab-scale rock bolt assembly with various angles to analyze the efficiency of the method in real life scenario. The results showed that the new technique improves the performance of the rock bolts by reducing the material wastage, improving environmental performance, facilitating and accelerating the labor works, and finally enhancing the durability of the whole system. Accordingly, this approach provides an efficient alternative for the traditional way of tunnel bolt installation with considerable advantages for the Swedish tunneling industry.

Three-Dimensional State with Doublet Mechanics

In this study, it is aimed to obtain general stress expressions for the examination of mechanical behaviors of planar straight axis nano rods by using doublet mechanics. The superiority of this method over other scale dependent methods is that it is directly related to the structure of nanomaterial and it models solid structure with points at finite distances between them. In other words, value of small scale effect is known exactly. To the best of authors’ knowledge, after micro modulus matrix is obtained by using Generalized Hooke’s Law and the essential transformation matrix expressing relationships between macro and micro stress and strain matrix, the stress equations that include the effect of axial extension are acquired for the three-dimensional state for the first time in the literature. In plane and out of plane static and dynamic behaviors can be studied using analytical and/or numerical approaches without any restrictions. Since the value of the small scale size parameter is precisely known in the theory used, it is thought that the results to be obtained will be more accurate than other scale size theories.

Predictive Maintenance of Industrial Shredders: Efficient Operation through Real-Time Monitoring Using Statistical Machine Learning

The shredding of waste materials is a key step in the recycling process towards circular economy. Industrial shredders for waste processing operate in very harsh operating conditions, leading to the need of frequent maintenance of critical components. The maintenance optimization is particularly important also to increase the machine’s efficiency, thereby reducing the operational costs. In this work, a monitoring system has been developed and deployed on an industrial shredder located at a waste recycling plant in Austria. The machine has been monitored for several months and methods for predictive maintenance have been developed for two key components: the cutting knives and the drive belt. The large amount of collected data is leveraged by statistical machine learning techniques, thereby not requiring a very detailed knowledge of the machine or its live operating conditions. The results show that, despite the wide range of operating conditions, a reliable estimate of the optimal time for maintenance can be derived. Moreover, the trade-off between the cost of maintenance and the increase in power consumption due to the wear state of the monitored components of the machine is investigated. This work proves the benefits of real-time monitoring system for efficient operation of industrial shredders.

Finite Element Modelling of Log Wall Corner Joints

The paper presents outcomes of the numerical research performed on standard and dovetail corner joints under lateral loads. An overview of the past research on log shear walls is also presented. To the authors’ best knowledge, currently, there are no specific design guidelines available in the code for the design of log shear walls, implying the need to investigate the performance of log shear walls. This research explores the performance of the log shear wall corner joint system of standard joint and dovetail types using numerical methods based on research available in the literature. A parametric study is performed to study the effect of gap size provided between two orthogonal logs and the presence of wood and steel dowels provided as joinery between log courses on the performance of such a structural system. The research outcomes are the force-displacement curves. Variability of 8% is seen in the reaction forces with the change of gap size for the case of the standard joint, while a variation of 10% is observed in the reaction forces for the dovetail joint system.

Evaluating the Performance of Offensive Lineman in the NFL

In this paper we objectively measure the performance of an individual offensive lineman in the NFL. The existing literature proposes various measures that rely on subjective assessments of game film, but has yet to develop an objective methodology to evaluate performance. Using a variety of statistics related to an offensive lineman’s performance, we develop a framework to objectively analyze the overall performance of an individual offensive lineman and determine specific linemen who are overvalued or undervalued relative to their salary. We identify eight players across the 2013-2014 and 2014-2015 NFL seasons that are considered to be overvalued or undervalued and corroborate the results with existing metrics that are based on subjective evaluation. To the best of our knowledge, the techniques set forth in this work have not been utilized in previous works to evaluate the performance of NFL players at any position, including offensive linemen.

Graph Codes-2D Projections of Multimedia Feature Graphs for Fast and Effective Retrieval

Multimedia Indexing and Retrieval is generally de-signed and implemented by employing feature graphs. These graphs typically contain a significant number of nodes and edges to reflect the level of detail in feature detection. A higher level of detail increases the effectiveness of the results but also leads to more complex graph structures. However, graph-traversal-based algorithms for similarity are quite inefficient and computation intensive, espe-cially for large data structures. To deliver fast and effective retrieval, an efficient similarity algorithm, particularly for large graphs, is mandatory. Hence, in this paper, we define a graph-projection into a 2D space (Graph Code) as well as the corresponding algorithms for indexing and retrieval. We show that calculations in this space can be performed more efficiently than graph-traversals due to a simpler processing model and a high level of parallelisation. In consequence, we prove that the effectiveness of retrieval also increases substantially, as Graph Codes facilitate more levels of detail in feature fusion. Thus, Graph Codes provide a significant increase in efficiency and effectiveness (especially for Multimedia indexing and retrieval) and can be applied to images, videos, audio, and text information.

Impact on Course Registration and SGPA of the Students of BSc in EEE Programme due to Online Teaching during the COVID-19 Pandemic

Most educational institutions were compelled to switch over to the online mode of teaching, learning, and assessment due to the lockdown when the corona pandemic started around the globe in the early part of the year 2020. However, they faced a unique set of challenges in delivering knowledge and skills to their students as well as formulating a proper assessment policy. This paper investigates whether there is an impact on the student Semester Grade Point Average (SGPA) due to the online mode of teaching and learning assessment at the Department of Electrical and Electronic Engineering (EEE) of Southeast University (SEU). Details of student assessments are discussed. Then students’ grades were analyzed to find out the impact on SGPA based on the z-test by finding the standard deviation (). It also pointed out the challenges associated with the online classes and assessment strategies to be adopted during the online assessment. The student admission, course advising, and registration statistics were also presented in several tables and analyzed based on the change in percentage to observe the impact on it due to the pandemic. In summary, it was observed that the students’ SGPAs are not affected but student course advising and registration were affected slightly by the pandemic. Finally, the paper provides some recommendations to improve the online teaching, learning, assessment, and evaluation system.

Methodology of Personalizing Interior Spaces in Public Libraries

Creating public spaces which are tailored for the specific demands of the individuals is one of the challenges for the contemporary interior designers. Improving the general knowledge as well as providing a forum for all walks of life to exploit is one of the objectives of a public library. In this regard, interior design in consistent with the demands of the individuals is of paramount importance. Seemingly, study spaces, in particular, those in close relation to the personalized sector, have proven to be challenging, according to the literature. To address this challenge, attributes of individuals, namely, perception of people from public spaces and their interactions with the so-called spaces, should be analyzed to provide interior designers with something to work on. This paper follows the analytic-descriptive research methodology by outlining case study libraries which have personalized public libraries with the investigation of the type of personalization as its primary objective and (I) recognition of physical schedule and the know-how of the spatial connection in indoor design of a library and (II) analysis of each personalized space in relation to other spaces of the library as its secondary objectives. The significance of the current research lies in the concept of personalization as one of the most recent methods of attracting people to libraries. Previous research exists in this regard, but the lack of data concerning personalization makes this topic worth investigating. Hence, this study aims to put forward approaches through real-case studies for the designers to deal with this concept.

A Comprehensive Survey on Machine Learning Techniques and User Authentication Approaches for Credit Card Fraud Detection

With the increase of credit card usage, the volume of credit card misuse also has significantly increased, which may cause appreciable financial losses for both credit card holders and financial organizations issuing credit cards. As a result, financial organizations are working hard on developing and deploying credit card fraud detection methods, in order to adapt to ever-evolving, increasingly sophisticated defrauding strategies and identifying illicit transactions as quickly as possible to protect themselves and their customers. Compounding on the complex nature of such adverse strategies, credit card fraudulent activities are rare events compared to the number of legitimate transactions. Hence, the challenge to develop fraud detection that are accurate and efficient is substantially intensified and, as a consequence, credit card fraud detection has lately become a very active area of research. In this work, we provide a survey of current techniques most relevant to the problem of credit card fraud detection. We carry out our survey in two main parts. In the first part, we focus on studies utilizing classical machine learning models, which mostly employ traditional transnational features to make fraud predictions. These models typically rely on some static physical characteristics, such as what the user knows (knowledge-based method), or what he/she has access to (object-based method). In the second part of our survey, we review more advanced techniques of user authentication, which use behavioral biometrics to identify an individual based on his/her unique behavior while he/she is interacting with his/her electronic devices. These approaches rely on how people behave (instead of what they do), which cannot be easily forged. By providing an overview of current approaches and the results reported in the literature, this survey aims to drive the future research agenda for the community in order to develop more accurate, reliable and scalable models of credit card fraud detection.

Energy Policy in Nigeria: Prospects and Challenges

Energy is the major force that drives any country`s socio-economic development. Without electricity, the country could be at risk of losing many potential investors. As such, good policy implementation could play a significant role in harnessing all the available energy resources. Nigeria has the prospects of meeting its energy demand and supply if there are good policies and proper implementation of them. The current energy supply needs to improve in order to meet the present and future demand. Sustainable energy development is the way forward. Renewable energy plays a significant role in socio-economic development of any country. Nigeria is a country blessed with abundant natural resources such as, solar radiation for solar power, water for hydropower, wind for wind power, and biomass from both plants and animal’s waste. Both conventional energy (fossil fuel) and unconventional energy (renewable) could be harmonized like in the case of energy mix or biofuels. Biofuels like biodiesel could be produced from biomass and combined with petro-diesel in different ratios. All these can be achieved if good policy is in place. The challenges could be well overcome with good policy, masses awareness, technological knowledge and other incentives that can attract investors in Nigerian energy sector.