Development and Implementation of Sustainability IoT Based Curriculum

Sustainable development has three main pillars, economic, social, and environmental. In the strive for a sustainable world, environmental and social issues must be addressed as they affect the world economy. With the past industrial revolutions and their negative effects on our world, it is becoming essential to involve students in sustainability as engineering and technology are important elements into fixing the past negative effects on our planet. Consequently, educating engineering students on sustainable development is wide spreading in the past few years and is actually taking place worldwide in many modern faculties and universities. Aside from the United Nations mandates, it is those engineers who are to make the efforts in their respective fields to create ways to improve the sustainable world around us. There are many methods to go about teaching such a subject, some are direct and some uses indirect methods. Building upon the experience of others and the wide spectra of methods, a new curriculum is designed, based on innovations in technologies, to cover sustainability along with environmental and social implications. The curriculum relies on a mixture of learning techniques especially suitable for a developing and growing educational environment where the subject matter experts are not abundantly available. The method used in the design and implementation allows flexible usage and integration of the course by educational institutions and new universities. The results of applying the course content on a sample of 50 student is collected and analysed. The tabulated data and graphs show the strong points of the course materials as well as the areas of improvements. This work is licensed under a&nbsp;Creative Commons Attribution-NonCommercial 4.0 International License.</p

The hiring problem and its algorithmic applications

The hiring problem is a simple model for on-line decision-making under uncertainty, recently introduced in the literature. Despite some related work dates back to 2000, the name and the first extensive studies were written in 2007 and 2008. The problem has been introduced explicitly first by Broder et al. in 2008 as a natural extension to the well-known secretary problem. Soon afterwards, Archibald and Martínez in 2009 introduced a discrete (combinatorial) model of the hiring problem, where the candidates seen so far could be ranked from best to worst without the need to know their absolute quality scores. This thesis introduces an extensive study for the hiring problem under the formulation given by Archibald and Martínez, explores the connections with other on-line selection processes in the literature, and develops one interesting application of our results to the field of data streaming algorithms. In the hiring problem we are interested in the design and analysis of hiring strategies. We study in detail two hiring strategies, namely hiring above the median and hiring above the m-th best. Hiring above the median hires the first interviewed candidate then any coming candidate is hired if and only if his relative rank is better than the median rank of the already hired staff, and others are discarded. Hiring above the m-th best hires the first m candidates in the sequence, then any coming candidate is hired if and only if his relative rank is larger than the m-th best among all hired candidates, and others are discarded. For both strategies, we were able to obtain exact and asymptotic distributional results for various quantities of interest (which we call hiring parameters). Our fundamental parameter is the number of hired candidates, together with other parameters like waiting time, index of last hired candidate and distance between the last two hirings give us a clear picture of the hiring rate or the dynamics of the hiring process for the particular strategy under study. There is another group of parameters like score of last hired candidate, score of best discarded candidate and number of replacements that give us an indicator of the quality of the hired staff. For the strategy hiring above the median, we study more quantities like number of hired candidates conditioned on the first one and probability that the candidate with score q is getting hired. We study the selection rule 1/2-percentile rule introduced by Krieger et al., in 2007, and the seating plan (1/2,1) of the Chinese restaurant process (CRP) introduced by Pitman, which are very similar to hiring above the median. The connections between hiring above the m-th best and the notion of m-records, and also the seating plan (0,m) of the CRP are investigated here. We report preliminary results for the number of hired candidates for a generalization of hiring above the median; called hiring above the alpha-quantile (of the hired staff). The explicit results for the number of hired candidates enable us to design an estimator, called RECORDINALITY, for the number of distinct elements in a large sequence of data which may contain repetitions; this problem is known in the literature as cardinality estimation problem. We show that another hiring parameter, the score of best discarded candidate, can also be used to design a new cardinality estimator, which we call DISCARDINALITY. Most of the results presented here have been published or submitted for publication. The thesis leaves some open questions, as well as many promising ideas for future work. One interesting question is how to compare two different strategies; that requires a suitable definition of the notion of optimality, which is still missing in the context of the hiring problem. We are also interested in investigating other variants of the problem like probabilistic hiring strategies, that is when the hiring criteria is not deterministic, unlike all the studied strategies

Sensitivity analysis of sensors in a hydraulic condition monitoring system using CNN models

Condition monitoring (CM) is a useful application in industry 4.0, where the machine’s health is controlled by computational intelligence methods. Data-driven models, especially from the field of deep learning, are efficient solutions for the analysis of time series sensor data due to their ability to recognize patterns in high dimensional data and to track the temporal evolution of the signal. Despite the excellent performance of deep learning models in many applications, additional requirements regarding the interpretability of machine learning models are getting relevant. In this work, we present a study on the sensitivity of sensors in a deep learning based CM system providing high-level information about the relevance of the sensors. Several convolutional neural networks (CNN) have been constructed from a multisensory dataset for the prediction of different degradation states in a hydraulic system. An attribution analysis of the input features provided insights about the contribution of each sensor in the prediction of the classifier. Relevant sensors were identified, and CNN models built on the selected sensors resulted equal in prediction quality to the original models. The information about the relevance of sensors is useful for the system’s design to decide timely on the required sensorsPeer ReviewedPostprint (published version

Patient with Marfan syndrome and a novel variant in FBN1 presenting with bilateral popliteal artery aneurysm

We present a 43-year-old man with aortic root dilation, mitral valve prolapse, and marfanoid appearance, who presented with acute onset left leg pain. He underwent a Doppler ultrasound that revealed left popliteal artery aneurysm with thrombus. CT angiogram showed bilateral popliteal artery aneurysms. After repairing of his left popliteal artery aneurysm, he was sent for genetic evaluation. He was diagnosed with Marfan syndrome (MFS) based on the revised Ghent criteria and then underwent FBN1 sequencing and deletion/duplication analysis, which detected a novel pathogenic variant in gene FBN1, denoted by c.5872 T&gt;A (p.Cys1958Ser). MFS is a connective tissue disorder with an autosomal dominant inheritance due to pathogenic variants in FBN1 that encodes Fibrillin-1, a major element of the extracellular matrix, and connective tissue throughout the body. MFS involves multiple systems, most commonly the cardiovascular, musculoskeletal, and visual systems. In our case we present a rare finding of bilateral popliteal artery aneurysms in a male patient with MFS

The Impact of Geopolitical Risk on Sustainable Markets: A Quantile-Time-Frequency Analysis

We examine the impact of Geopolitical Risk (GPR) on green, clean, and socially responsible markets by employing the newly proposed Wavelet Quantile Correlation, Cross-quantilogram and Causality-in-quantiles. Unlike earlier studies, we incorporate the GPR index to encompass the risk linked to conflict, acts of terrorism, and political tensions. In brief, our findings show that GPR emerges as a significant factor influencing market behavior, with distinct patterns observed across different time scales and trading horizons. Our results are beneficial for investors and portfolio managers to adopt more rational investment strategies and for policymakers to make appropriate policy arrangements. 1 1 Corresponding author: Ahmed H. Elsayed ([email protected]

The Hiring Problem: An Analytic and Experimental Study

When a small, start-up company intends to grow, it has to hire employees. Because the company requires high quality staff, the employer has to interview a lot of candidates and thus, she may take long time to collect the required staff. Of course, there is another important demand which is the time taken by the hiring process which is required to be as short as possible or the company’s rate of growth which is required to go as quickly as possible. So, the company has two main demands and needs to achieve balance between them. This is an intuitive idea about hiring from which this case study problem bears its name. The hiring problem is just an abstract model of the real hiring process. It is clear that the hiring problem will not cover every aspect of real hiring processes but it investigates some important parameters under a simplified mathematical model. On the other hand, the statement of the problem - as we will see- will give a general mathematical question with many possible applications; it is relevant in many instances where one must make decisions under uncertainty

Utilization of earth observation technology for mapping spatio-temporal changes of urban water bodies (ponds) and its environmental impacts in Hadejia, Nigeria

Ponds locally called (Kududfi in Hausa) are either naturally or artificially created ditches which usually contained water and constitute significant elements of the settlement in Northern Nigeria which can be expanded beyond their natural depth. Many ponds in the urban centers of developing nations have inlets and outlets for transporting water from small ponds to large ones especially ponds that serve as reservoir for the domestic and rain water storage. Earth observation technology allowed researchers to accurately study the past, current and even predict the future of spatial temporal changes of urban environment including the water bodies (ponds). In developing nations like Nigeria many ancients’ cities became over crowded, this is likely because of their history, opportunities or economic advantages. Nevertheless, many of the ancient’s cities in Africa experienced regular annual urban flood that make the city centers as water logging throughout the wet season due to community culture toward destructions and claiming ownership of water bodies (ponds) either by government officials or individuals which normally serve as a domestic and rain water reservoir. Therefore, this research aimed on the utilization of geospatial technologies for mapping spatial temporal changes of urban water bodies (ponds) and its environment impacts in the study. Research also designed to map the geospatial distribution of ponds (urban water bodies) and how does human activities affect its functions. The satellite image data acquired for years 1999 and 2019 respectively. Nevertheless, the imageries were geometric and radiometric corrected using the quick atmospheric correction (QUAC). The findings indicated that most of the Ponds changed in their size, shape and mainly filled with solid waste. From the analysis of the research shown that annual urban flood is attributed from the destructions of ponds. Changes from other land use types also affect the water bodies such as schools, residential, commercial, etc. the findings also showed the impacts of ponds destructions such as making areas water logged, occurrence of urban flood, change in local climate and alteration of hydro-geomorphic nature of the area

Intelligent Greenhouse Monitoring and Control System Based Arduino UNO Microcontroller

Nowadays, there is a significant diminution in agricultural production due to the unpredictable control of crop climate conditions. Thus, to alleviate the crops exposure from excess cold or heat and unwanted pests, an intelligent environment monitoring and control system based Arduino UNO board consisting of ATmega 328P microcontroller has been developed for a small-scale agriculture namely greenhouse. The system user can monitor and control the greenhouse climate conditions remotely via web interface/mobile applications and GSM in a real-time manner. To deliver the environmental conditions in a timely manner, low-cost wireless sensor network (WSN) is used to monitor the temperature, humidity, soil moisture and light of the greenhouse. The sensor network constitutes a multi-hop network structure for large coverage. The developed system is implemented and tested in laboratory conditions using Proteus toolkit. Arduino Integrated Development Environment (IDE) tool is used to develop necessary software. The results show that the proposed system can closely monitor and evaluate greenhouse farming field conditions accurately. Finally, the user can send control decisions instantly to boost the yield growth conditions and thus, increase the crop production considerably