Lamia Tasnim Imam, Md. Syed-uz-Zaman

Prestressed transfer beam is a new context in structural design. It is used to reduce the number of columns by transferring loads from one column to the surrounding columns with the tensioning of high strength tendons in transfer beam. Different structural behavior under seismic load of a multistoried building is studied in this paper. As a densely populated mega city, multistoried buildings may mitigate the living problem in Dhaka. Prestressed transfer beam having different dimension and at different location can be used in mixed use building for minimizing seismic load. So, a plan of 25 storied residential cum commercial building with two basements had been selected in the context of Dhaka city. The structural behaviour of RCC and prestressed transfer beams have been investigated in this study. Two cases had been established to analyze the building with the use of ETABS 17.0.1. Case 1, in which RCC transfer beams are positioned and Case 2, in which prestressed transfer beams are positioned in different location in 6th floor. Comparison of various parameters like base shear, moments, maximum lateral deflection, inter story drift and rotation between RCC and prestressed transfer beams have been analyzed from the ETABS 17.0.1 software. Prestressed transfer beam must be designed with a proper purpose and functional requirement. Prestressed transfer beams are a typical feature in the multi-storied construction as far now.

Ricky B. Acanto, Van Helen S. Cuaderes

Split gill mushroom (Schizophyllum commune) is one of the most widespread fungal species with various uses among communities, especially in the countryside. With its favorable characteristics, this macrofungi shows potential to be utilized in the field of natural products. The study aims to ascertain the antimicrobial effects and determine the active components present in the ethanolic extracts. The extract’s antibacterial activity was determined using Kirby-Bauer Disk Diffusion Assay, antifungal susceptibility through Poisoned Food Method, and minimum inhibitory concentration (MIC) through Microtiter Well Assay. Qualitative phytochemical analysis was carried out using the test tube method. Results revealed that gram-negative bacteria were resistant to the different concentrations of the extracts; however, gram-positive test bacteria were susceptible to any extract concentration. Additionally, MICs showed that a lower concentration of the extract was required to inhibit the growth of gram-positive than the gram-negative bacteria. The increasing concentration of extracts showed more significant fungal growth inhibition. Saponins, tannins, alkaloids, flavonoids, terpenoids, proteins, and carbohydrates were identified through the phytochemical screening. Ethanolic extracts of S. commune showed effectiveness against the growth of gram-positive bacteria and fungi due to different active components present. Further studies may be conducted to explore the potential of this macrofungi.

Sarah El Shahawy, Prof. Hayam Wahba

The aim of this study is to propose an improvement to the CAPM1 by adding the intellectual capital components to the it to help in improving the calculation of the excess return. In order to assess the relationship, the quarterly panel data of the 100 firms listed in the EGX 1002, for the period from December 2013 till September 2018, were used to conduct the test. The author tested whether the intellectual capital components, as measured by Pulic (VAIC)3, can be used as a factor in measuring the excess return of a stock or not. The results of this paper showed that the excess return is cointegrated with all of the independent variables. Moreover, the results of the GLS regression and the Fama-MacBeth regression showed that the VAICCAPM4 outperformed the FF model. However, they also showed that both models cannot be used to estimate the stock’s return of the companies listed in the EGX100. Moreover, the GLS5 and the FM6 regressions showed that the CAPM model is the only model that can be used to estimate the stock’s return of the companies listed in the EGX100. The original CAPM model is the simplest and the most used model to assess the risk and the risk premium of a certain investment. However, this model has a lot of criticism because of its simplicity. One of the limitations is that it doesn’t take into consideration the performance of the company when calculating the excess return. Even though many authors in the past tried to come up with new models to improve the original CAPM model, they all were only interested in the financial factors that affect the company’s performance. This paper is one of the first researches done that adds the intellectual capital of the firm to the capital asset pricing model. Moreover, the author then compares this model’s performance to the CAPM and the FF7 models.

Giang Truong Le, Thang Viet Tran, Phuc Thinh Doan, Trong Hai Nguyen

A novel radio frequency (RF) gateway is designed and implemented by using an open-source real-time operating system for wireless communication between sensor node and server over the internet network. The proposed RF gateway consists of a Dual-core microcontroller unit, a wireless transceiver module that operates at a frequency of 433 MHz and a local user interface website configuration. By using three low-power wireless sensor nodes, we can experiment with the designed RF gateway, that is, connected to commercial environment sensors and collecting data such as water temperature sensors. The proposed RF gateway can simultaneously execute multitasking with a set of different priorities and in particular, it can collect and store measured sensor data in 30 days, and as a server transferring measurement results from nodes to an IoT dashboard by using Websocket protocols. In addition, a friendly portable interface website is designed to manage and illustrate parameters and as control wireless actuator node in offline mode. This system was implemented by using an open-source real-time operation system (FreeRTOS) and a single high-speed multicore microcontroller unit that is a promising option for most of the applications in the Internet of Things.

Osei Wusu Brempong Jnr

The mission of the Ghana Education Service (GES) [1], is to ensure that all Ghanaian children of school-going age are provided with inclusive and equitable quality formal education and training through effective and efficient management of resources to make education delivery relevant to the manpower needs of the nation. The GES uses a computerized school selection and placement system that assigns senior high schools to students based on their test scores from previous Junior secondary schools. The computerized school selection and placement system (CSSPS) uses a deferred acceptance algorithm for each school assignment. Under these procedure students are ranked according to their priority levels (that is Test scores in the case of the CSSPS) [2]; they are then proposed as a match to their first-choice school in order of their test score rankings. Students are assigned to their first choice if there is a space available in the schools. What the CSSPS failed in doing is to determine the average number of students that can be allocated to each school during the placement selection process. The objective of this research is to use machine learning (linear regression) to predict the increase in student enrollment for schools in each region based on the school’s average test score performance i.e. average GPA from the previous year. Firstly, we investigate the relationship between increase in student’s applications for each school and the school average GPA (test score) from previous year. A sample dataset from 10 senior high schools in the capital region of Ghana was used for this research. Supervise machine learning models and associated algorithm (simple linear regression) to analyze data for regression helped in training the model to predict the increase in student’s enrollments for each school based on the school average GPA (test scores)

Osei Wusu Brempong Jnr

Machine learning, an application of Artificial intelligence uses computer algorithms designed to make decisions and predict outcomes based on analyzing huge data sets.[1] ML enables systems to automatically change and increase in accuracy without being programmed. One major advantage of ML technology in education is student’s selection and prediction of their academic performance. ML beneficial in education is its ability to track learner’s progress and also adjust courses to respond to student's needs which helps in increasing student and teacher engagement [2]. ML feedbacks also put instructors in position to analyze and understand student’s potential and interest, identify struggling students and provide extra support to struggling student’s to overcome learning challenges. GES (Ghana Education Service) has already begun digitalizing the Ghana education system by implementing the computerized school selection and placement system (CSSPS) which is an automated merit base computerized system that uses a deferred acceptance algorithm for assignment[3]. In this system, students are ranked according to their priority levels, they are then proposed as a match to their first choice school in order of their test score ranking. In this paper, we propose a machine learning algorithm K-means clustering to grouping students into ranks of their grades and to analyze their results based on cluster analysis. The student’s evaluation factors like average First and Second semester exams, mid-term quizzes are studied. This analysis will enable teachers and school academic administrators to establish prior knowledge of student's grades and predict their performance

Pandith Arismunandar, Sada Ukur Br. Barus, Endah Dwi Pangesti

Chronic kidney disease (CKD) is a decrease of kidney function in a few months or years that require kidney replacement therapy one of which is hemodialysis. Hemodialysis processs that takes ± 5 hours will cause symptom of fatigue which is a decrease in muscle strength. Interventions that can be done to reduce fatigue in patients CKD with hemodialysis management such as intradialytic exercise which is planned and structured movement exercise to improve one or more aspects of physical fitness using smooth muscle movements and slow movements. The purpose of this study was to determine the effect of intradialytic exercise on fatigue in hemodialysis patients in Dustira Hospital Cimahi. The research method was pre experimental design with one group pretest-posttest design for 4 weeks with 8 treatments. The level measurement of Fatigue was used Fatigue Severity Scale (FSS) before (pretest) and after (posttest) intervention. The sample of this study was 15 respondents using purposive sampling technique. The result of the study based on the dependent sample t test, p value obtained 0,000 because of p value < α (0,05) it can be concluded that there is a significant effect between intradialytic exercise with the level of fatigue in hemodialysis patients in Dustira Hospital Cimahi 2019. The suggested of this results especially for hemodialysis nurses can do intradialytic exercise to overcome fatigue in CKD patients with hemodialysis.

LAID Chaharazed

In this work, we consider the first nonlinear epidemic model with temporary immunity and saturated incidence rate and the second model witch is modified with the new parameters. Whenever infected and recovered people will return to the susceptible class after a period. Motivated by the references of this work, which deals with a model with temporary immunity and incidence rate, means that the recovered individual has temporary immunity against a disease and he enters the sensitive class after a certain time. We present: 1. Equilibrium and stability of the disease-free equilibrium and endemic 2. Existence of endemic equilibrium and its stability analysis. 3. Global stability of the disease-free equilibrium. 4. Modified model. 5. Global stability of the disease-free equilibrium of the modified model. The study of its sections are justified with theorems and demonstrations under certain conditions.

Russel V. Santos

School administrators understand the type and extent of their schools' adaptation to new normal situations and challenges in the education system is highly and significantly influenced by the level of their new normal school management actions. The same as with the land of Pangasinan, principals are challenged with school management priorities, hence, this investigation sought to find out the extent of a school management of the public secondary school along aspects of leadership and governance, curriculum and instruction, accountability of continuous improvement and management of resources; and the extent of implementation of Instructional Leadership, Fiscal Management, and Infrastructure. The study is descriptive by nature with the 117 public secondary school principals in Pangasinan Division II. The data were gathered using survey-questionnaires and were statistically treated using weighted mean and t-test. SPM tool was used in this study to collect data in order to assess the extent to which principals have implemented school management features Second, survey-questionnaires are used to collect information on their level of management implementation. It was found that in leadership and governance, majority of the respondents highly implemented a collaborative network established by the school community. For curriculum and instruction, majority of the respondents claimed that the programs in their schools are fully implemented to maintain harmonious environment. Meanwhile, accountability for continuous improvement, majority of the respondents cited that school-community development performance assessment is practiced. In terms of management of resources, most of the respondents claimed that stakeholders support judicious use of resource. Finally, the implementation of infrastructure is most used extensively than Instructional Leadership and Fiscal Management.

willmie wilfred, syahruddin awang ahmad

The increased number of Instagram users demonstrated that this platform is expected to grow in the current time and has the potential to influence the young generation because they are exposed to the platform on a daily basis. Instagram exposure is frequently associated with low self-esteem among users. Therefore, the current study was designed with two main objectives 1) to investigate the relationship between Instagram and self-esteem of namely university students, and 2) to investigate the influencing factor of Instagram in affecting the level of self-esteem of university students. Low self-esteem is often associated with negative emotions such as depression, antisocial behaviour, and suicidal thoughts. As for the student, self-esteem plays an important role in academic achievement as it is stated in this study which was conducted by using quantitative approach. Findings showed that student who have low self-esteem often experiencing in poor academic performance to be compared with those who have a high level of self-esteem. According to the findings, there is no significant relationship between Instagram and the third-year communication student's self-esteem. Aside from that, the results show that the number of likes on photos and videos on Instagram is an influencing factor in determining one's level of self-esteem.

Solomon Amenyo, Thomas Henaku, Augustus Buckman, Alice Amoako

The current study aimed to develop Assistive Learning, Awareness, and Emergency Response System (ALAERS) for Children with Autism, Parents, and Caregivers. Action research and participatory design methodologies were implemented with children with Autism Spectrum Disorder (ASD) along with the participation of their parents, teachers, caregivers, and field experts. The participatory design process involved three workshops with specialized units working with Autistic children, through which sensory exploration and idea generation for the design of the system and its elements were facilitated. Knowledge elicitation workshops with practitioners informed the design of the learning activities and the implementation of the user model. The system was perceived as entertaining, reader-friendly, memorable and engaging. The interactive nature of the assistive learning module was particularly helpful in raising satisfaction as they provided children with the opportunity to make their own learning decisions.

Thomas Henaku, Augustus Buckman, Solomon Amenyo

With the rising awareness of people in Android-based applications, it has been perceived that mobile devices can be used to surge the educational skills of children instead of allowing them to use all their time for playing games. Therefore, the development of an educational application is essentially required, especially, to improve the computer-related knowledge of children. There is the necessity to create a simple, interactive and easy to use Android-based application to enhance the knowledge of children in basic computer concepts. In this work, we developed an educational application, named “Whiz ICT” with Android Studio. It also expounds on the methods taken to make the project come into reality. The ADDIE (Analysis, Design, Development, Implementation, and Evaluation) model of the System Development Life Cycle was used to make sure the project meets the requirement of each and every stage. Furthermore, user and system requirements were the main components taken into consideration which helped in making the project come into existence.

Goboitshepo Ororiseng Leroke, Manoj Lall

Traffic congestion is a major challenge facing urban areas around the globe today. A common approach adopted by government agencies for the monitoring of traffic conditions is by making use of CCTV cameras or electronic sensors. These approaches requires the maintenance of a large network of sensors and cameras to monitor every street in the city. This is impractical and very costly. However, with the advancement of social media in all its forms, including blogs, online forums, Facebook, and Twitter, it is possible to treat social media as a human sensor network. In this article, an alternative traffic monitoring approach that is inexpensive and provides traffic information in near real-time is developed. The proposed approach makes use of Twitter data analytics to report on the prevailing traffic conditions in a particular locality. In addition, the reason behind the traffic congestion is also highlighted. Knowing the cause of the traffic congestion is important as it gives an indication of the severity of the problem. For the modelling of the proposed near real time Twitter-based model, 5 000 tweets collected over a period of six months were collected for a particular geographical location. The relevant Twitters were pre-processing to obtain the applicable features such as the location of the origin of a particular post, the time when the tweet was posted. Random Forest, Naïve Bayes, Support Vector Machine and K-Nearest Neighbour were used in the construction of the classification model. The best performing model (Naïve Bayes) was selected for real-time tweet classification. Python’s Natural Language Toolkit (NLTK) and associated libraries, was applied to enhance the suitability of tweets for conducting sentiment analysis and topic modelling. The emotions expressed in the tweets were captured by sentiment analysis and the reason behind traffic congestions were determined by topic modelling. The location, the sentiment and the reasons for the traffic congestions were visualized using street map. It is envisaged that such a model will assist commuters in making an informed decision on route selection.

Nani Sayekti Yuli Pratiwi, Waluyo

This study aims to prove the effect of professional competence and skepticism of tax examiners on the quality of tax audits with time pressure as moderating variable. This study using mixed method of quantitative (purposive survey) and qualitative, the data source used is primary data collected through sending questionnaires to respondents, while the qualitative research data source is by interview of several respondents. The results in this study indicate that competence has positive effect on quality of tax audits, while competency moderated by time pressure has no effect on quality of tax audits, professional skepticism has a positive effect on quality of tax audits, and the interaction of professional skepticism moderated by time pressure has a negative effect on quality of tax audits. The results of quantitative research is supported by qualitative research results. This study contributes to the development of theories in the field of tax auditing and accounting.

Lewechi Anyaogu, Chinenye Elizabeth Okere, Nnanna Obiabuchi Martin

This work presents the model for predicting the compressive strength of interlocking tiles made with recycled plastic bottles. The use of recycled plastic bottles in making interlocking tile is an approach to eliminating plastic from the environment. The interlocking tiles were produced with sand, granite dust, and recycled plastic bottles. Scheffe’s and Osadebe’s models are statistical methods used in this study to design mix and formulate the model. The melting of the plastic mixed with sand and granite dust was regulated at an average temperature of 194.41°c. The hot mixtures were cast and air-cured for 28days. A total of thirty-six (36) interlocking tiles were cast, comprising of three cubes for each mix-ratio of a total of twelve (12) mix ratios. The first six (6) mix ratios were used to determine the coefficients of the response function, while the other six were used to validate the response function. The highest and lowest experimental compressive strengths recorded in this work are 22.00 Nmm-2 and 20.33Nmm-2 respectively at observation points. The maximum and least experimental compressive strengths recorded in this work are 24.33 Nmm-2 and 21.00Nmm-2 respectively at control points. The results from the response function were compared favorably with the experimental results. The response functions were tested with the statistical student’s t-test and found to be adequate at a 95% confidence level. With the response function developed in this work; any desired compressive strength of interlocking tiles made from the mixture of sand, granite dust, and recycled plastic bottle can be predicted from known mix proportions and vice versa.

Taiwo Samuel Aina, Oluwaseun Olanrewaju Akinte, Babatunde Ademola, Iyaomolere, Innocent Iriaghuan Abode

The purpose of this work is to design an efficient image compression system using wavelet transforms and image approximation by modifying the wavelet coefficient. The efficiency of the system will be tested using a test image and determining the Mean Square Error (MSE). 2D-daubechies wavelet transformation with global threshold for wavelet coefficients and numerical presentation utilizing Matlab programming are the techniques used. The Discrete Wavelet Transform (DWT) has a basic principle of splitting signals into two parts namely; the high frequencies and low frequencies. For a number of repetitions, the low frequency section is further divided into high and low frequency parts, which are generally chosen by the application. The performance of an image compression system is commonly measured by calculating the MSE and the Peak Signal to Noise Ratio (PSNR).