Using CRF Tool for Analyzing the Resilience of Cities

The new sustainable development goals set by the UN include a goal of making cities inclusive, safe, sustainable, and resilient. Cities are growing at huge rates, and conditions of deteriorating QOL̛s are increasing in the form of poor access to services, and slums are remarkable, especially in the cities of the Middle East; hence, the research problem can arise from a lack of knowledge regarding the in determination of a way to assess the resilience of cities to develop mechanisms that will improve the quality of urban life. In this study, a tool called CRF has been applied for the assessment of the city's resilience principles of health and quality of life, economics and social, infrastructure and environmental systems, and the principles of governance and strategic leadership. The research aims to determine the efficiency of Kufa City in achieving the principles of resilience according to the CRF. The research is based on the descriptive analytical method. The research concluded that the city of Kufa achieves low levels of some indicators of resilience, especially on the imposition of security and the rule of law, transportation, and communications, and achieves reasonable rates of resilience regarding opportunities for creating a sustainable economy and achieving basic needs. Doi: 10.28991/CEJ-2022-08-10-013 Full Text: PD

Effect of Knives Type on Some Operational Characteristics fora Locally Assembly Motorized Vibration Cutter Used for Date Palm Fronds Pruning

The experiment was conducted to evaluate the effects of pruning cutting knives for locally assembly motorized vibration cutter on some operational characteristic used for date palm fronds. An implement was fabricated to cut the fronds around the date palm tree trunk. Three types of knife included A,B and Cwas used in this study .One frond cutting time, One palm frond cutting time, cutting level,productivity, noise level, vibration and efficiency was measured in this experiment . Complete block design with three replications was used in this study. Least significant differences (L.S.D) under 0.05 level was used to compeer the mean of treatment. The results showed thatB type gave a lower time in cutting one frond stood 3.11 sec. A type got lowest time of cutting three rows of fronds stood 1.74 min, also gave less differences in surface cutting level andlevel of noising stood 5.66 mm and 78.04 (db) respectively.B type knife got less vibration stood 5.25 m.sec-2. Also it gave the higher amount of productivitystood 8.80 palm /h. A type gave a high efficiency, it got 78.76%.Using manufacturing equipment for cutting date palm frond was successfully done

Comparison of the durations and complications of spinal anaesthesia between unilateral spinal anaesthesia and bilateral spinal anaesthesia for unilateral lower limb surgery

Despite the advantages of spinal anaesthesia when compared to general anaesthesia, it is associated with complications such as hypotension, bradycardia, shivering and nausea. Our study is set to compare the durations and complications between unilateral and bilateral spinal anaesthesia in patients undergoing unilateral lower limb surgeries. Method: Sixty four (64) American Society of Anesthesiology (ASA) 1 and 2 patients that were randomly assigned to two groups. Group U which is the unilateral spinal anaesthesia and group B which is the conventional bilateral spinal anaesthesia group to receive 2ml of 0.5% heavy bupivacaine plus 1ml of distilled water and 3ml of 0.5% heavy bupivacaine only respectively. The group U patients who had the procedure in the lateral decubitus position remained in that position for 20 minutes, while those in group B had the spinal injection in sitting position and immediately took the supine position after the injection. Results: The 64 adult patients who were randomly allocated into two groups with 32 patients each successfully had their surgeries done under the chosen technique. The mean duration of spinal anaesthesia was found to be 64±23.29 minutes and 100± 37.08 minutes in the group U and B respectively (p=0.001). There was no statistical differences in the general overall complications when the two groups were compared (p=0.03), however, on individual bases unilateral spinal anaesthesia has less complications compared to bilateral spinal anaesthesia for unilateral lower limb surgeries. Conclusion: The study showed that unilateral spinal anaesthesia with 2 ml of 0.5% bupivacaine had shorter duration of spinal anaesthesia with less complications compared to bilateral spinal anaesthesia for unilateral lower limb surgeries

Plasmonic temperature sensor using D-shaped photonic crystal fiber

Peer reviewe

Tooth wear in relation to physical salivary characteris-tics among gastroesophageal reflux disease

Background: Gastroesophageal reflux disease, is a quite prevalent gastrointestinal disease, among which gastric content (excluding the air) returns into the oral cavity. Many 0ral manifestations related t0 this disease include tooth wear, dental caries also changes in salivary flow rate and pH. This study was conducted among gastroesophageal reflux disease patients in order to assess tooth wear in relation to salivary flow rate and pH among these patients and the effect of gastroesophageal reflux disease duration on this relation. Materials and methods: One hundred patients participate in this cross-sectional study for both genders and having an age range of 20-40 years old, patients had been endoscopically identified as having gastroesophageal reflux disease using the classification of Los Angeles (LA), who were attending the Gastroenterology and Hepatology Teaching Hospital in Baghdad. and divided into two groups: group A with grade severity mucosal breakage not longer than 5 mm and Group B with grade severity mucosal breakage more than 5 mm long, Smith and Knight (1984) tooth wear index criteria were used for the assessment of tooth wear. For measurement of salivary flow rate and pH, saliva sample (unstimulated) had been collected. Results: Of the entire sample (90%) were having tooth wear. Tooth wear was higher in grade B severity than in grade A severity among patients with gastroesophageal reflux disease duration of two years or less, while it was higher in grade A than in grade B among patients with a duration of more than two years but all these results were statistically non-significant. Salivary flow rate and pH showed a non-significant reduction with increasing gastroesophageal reflux disease severity for both of groups concerning disease duration. The correlation of total tooth wear with salivary flow rate and pH was a significantly weak negative correlation in grade A, while a nonsignificant weak negative correlation in grade B. Conclusions: The findings of the present study concluded that patients with gastroesophageal reflux disease recorded a high occurrence of tooth wear and there was a negative correlation of tooth wear with salivary flow rate and pH among patients with gastroesophageal reflux disease

Brain Tumour Classification using Deep Learning with Residual Attention Network: A Comparative Study

— The main goal of this paper is to evaluate the performance of deep learning with Residual Attention Network (RAN) for brain tumour classification. Digitalised Magnetic Resonance Image (MRI) datasets obtained from Malaysian hospitals and other sources are utilised in this paper. The MRI datasets consist of information of those patients who are 20 years old and above, both male and female. The RAN algorithm is trained and tested using the MRI datasets. The algorithm performance is evaluated based on training accuracy, testing accuracy, validation accuracy, and validation loss metrices. Moreover, a comparative analysis is done with Residual Neural Network (ResNet) and Convolutional Neural Network (CNN) using the same datasets. The findings from this study prove that RAN provides the best performance among the three algorithms. ResNet has good performance, with an accuracy ranging from 67% to 87%. The standard CNN algorithm does not perform well, with a very inconsistent accuracy of between 57% and 71%. RAN produces the highest and most consistent accuracy, which is 94% and above. Further explanation is provided in this paper to prove the efficiency of RAN for the classification of brain tumour

The future of an intelligent and responsive architecture design after the COVID 19 epidemic

An intelligent building is much more than a set of walls; it’s a dynamic organism that employs integrated technologies to share data about the building among various systems to enhance efficiency and provide a better experience for its users. There are a number of challenges with intelligent buildings. They must respond to people’s requirements and needs, including their health and well-being; they must be resource-efficient, and they must include the most useful aspects of new technologies. The current COVID-19 outbreak has pushed architects to consider the future of architectural design technologies. Is it possible that the epidemic may influence the design of our buildings, causing them to become smarter or more intelligent? What role did architecture play throughout the epidemic and in the post-pandemic stage, as well? This paper aims to discuss the future of intelligent design technologies in light of the current Coronavirus epidemic and how it might reshape our architecture design. Finally, the impact of COVID-19 on people’s daily routines in the building design will be discussed

Environmental impact of using geothermal clean energy (heating and cooling systems) in economic sustainable modern buildings architecture design in Iraq:a review

Nowadays, with all the climate change problems that we face worldwide, engineers from different specialists work together towards Sustainability and finding solutions, and investigating its environmental impact thoroughly. Architectural, Chemical, environmental, civil engineers have always been closely linked in designing and constructing buildings. Geothermal energy is a local, resilient, reliable, ecologically benign, and sustainable form of the renewable energy system. This type of natural energy could be generated from the earth’s heat and takes a variety of purposes, including building heating and cooling, electricity generation, supplying warm/cold water for agricultural products in greenhouses, as well as balneological usage. Furthermore, geothermal energy isn’t affected by weather and could provide electricity and heat nearly constantly through the year. This study intends to investigate the opportunity of using geothermal energy in Iraq under the ground represents one of the sustainable energy resources we can use it will be a significant environmental benefit in our housing in air conditioning applications. This review gives a summary of geothermal energy systems in general. Topics addressed include: an introduction to the environments and the energy, also their relationship, a geothermal energy history brief, an overview of geothermal energy systems throughout the world and also through Iraq, and an overview of geothermal systems environmental impacts as well as the environmental impact of Sustainable buildings architecture design, are just a few of the topics covered. Hence, the achieved conclusions of this review can make changes towards sustainable environmental design

Forecasting Malaysian stock price using artificial neural networks (ANN)

Predicting a stock price is a very difficult task because it is complex and involves many factors. This has led to drop in the investment level in the Malaysian stock market. It is difficult to predict the stock market because its environments are unstable and dynamic. Recently, the demand for neural network in the business arena is on the increase. It is need to analyze vast data in order to search for information and knowledge that do not exist by using traditional methods. This included stock market prediction that is a very significant research in business area. In regard to Bursa Malaysia, Artificial Neural Network (ANNs). ANNs was only used to predict main index, i.e. Kuala Lumpur Composite Index (KLCI), but no attempt to predict share price and in particular banking sector. Since ANN has potential to predict non-linear behavior, this research attempts the use of ANNs to predict banking sector stock price in FTSE Bursa Saham Malaysia Kuala Lumpur Composite Index (FBM KLCI). One of the interesting topics of stock-market research is stock market prediction. Precise stock forecasting becomes the greatest challenge in the investment industry because stock data distribution changes over time. This paper investigates the use of ANN to predict Malaysian stock price, in particular Maybank Berhad stock price. The feedforward neural back-propagation network with Training Function Gradient Decent Training Algorithm is used in this study. The outcome of selected stocks, namely Maybank, are modeled and simulated and the results show that ANN offers a very accurate stock model and also generates competitive systems using all four trading strategies. The results also show that, neural network is a good tool to predict stock price movement with accuracy higher than 95%. Closing price is a good input for neural network model for stock price prediction