Search results for: immunoenzyme techniques

Authors: Jennifer E. Lynette

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This study describes the development process of a methodological framework for quality standards used to measure the efficiency and quality of response efforts of trained personnel at emergency events. This paper describes the techniques used to develop the initial framework and its potential application to professions under the broader field of emergency management. The example described in detail in this paper applies the framework specifically to fire response activities by firefighters. Within the quality standards framework, the fire response process is chronologically mapped. Individual variables within the sequence of events are identified. Through in-person data collection, questionnaires, interviews, and the expansion of the incident reporting system, this study identifies and categorizes previously unrecorded variables involved in the response phase of a fire. Following a data analysis of each variable using a quantitative or qualitative assessment, the variables are ranked pertaining to the magnitude of their impact to the event outcome. Among others, key indicators of quality performance in the analysis involve decision communication, resource utilization, response techniques, and response time. Through the application of this framework and subsequent utilization of quality standards indicators, there is potential to increase efficiency in the response phase of an emergency event; thereby saving additional lives, property, and resources.

Keywords: emergency management, fire, quality standards, response

Procedia PDF Downloads 318

Authors: Samuel J. Ahmad, Michael Zhu, Andrew J. Kobets

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Segmentation tools continue to advance, evolving from manual methods to automated contouring technologies utilizing convolutional neural networks. These techniques have evaluated ventricular and hemorrhagic volumes in the past but may be applied in novel ways to assess posterior fossa-associated pathologies such as Chiari malformations. Herein, we summarize literature pertaining to segmentation in the context of this and other posterior fossa-based diseases such as trigeminal neuralgia, hemifacial spasm, and posterior fossa syndrome. A literature search for volumetric analysis of the posterior fossa identified 27 papers where semi-automated, automated, manual segmentation, linear measurement-based formulas, and the Cavalieri estimator were utilized. These studies produced superior data than older methods utilizing formulas for rough volumetric estimations. The most commonly used segmentation technique was semi-automated segmentation (12 studies). Manual segmentation was the second most common technique (7 studies). Automated segmentation techniques (4 studies) and the Cavalieri estimator (3 studies), a point-counting method that uses a grid of points to estimate the volume of a region, were the next most commonly used techniques. The least commonly utilized segmentation technique was linear measurement-based formulas (1 study). Semi-automated segmentation produced accurate, reproducible results. However, it is apparent that there does not exist a single semi-automated software, open source or otherwise, that has been widely applied to the posterior fossa. Fully-automated segmentation via such open source software as FSL and Freesurfer produced highly accurate posterior fossa segmentations. Various forms of segmentation have been used to assess posterior fossa pathologies and each has its advantages and disadvantages. According to our results, semi-automated segmentation is the predominant method. However, atlas-based automated segmentation is an extremely promising method that produces accurate results. Future evolution of segmentation technologies will undoubtedly yield superior results, which may be applied to posterior fossa related pathologies. Medical professionals will save time and effort analyzing large sets of data due to these advances.

Keywords: chiari, posterior fossa, segmentation, volumetric

Procedia PDF Downloads 106

Authors: Amritha Nair, Fleur Visser, Ian Maddock, Jonas Schoelynck

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Inland waters such as streams sustain a rich variety of species and are essentially hotspots for biodiversity. Submerged aquatic vegetation, also known as SAV, forms an important part of ecologically healthy river systems. Direct and indirect human influences, such as climate change are putting stress on aquatic plant communities, ranging from the invasion of non-native species and grazing, to changes in the river flow conditions and temperature. There is a need to monitor SAV, because they are in a state of deterioration and their disappearance will greatly impact river ecosystems. Like terrestrial plants, SAV can show visible signs of stress. However, the techniques used to map terrestrial vegetation from its spectral reflectance, are not easily transferable to a submerged environment. Optical remote sensing techniques are employed to detect the stress from remotely sensed images through multispectral imagery and Structure from Motion photogrammetry. The effect of the overlying water column in the form of refraction, attenuation of visible and near infrared bands in water, as well as highly moving targets, are NIR) key challenges that arise when remotely mapping SAV. This study looks into the possibility of mapping the changes in spectral signatures from SAV and their response to certain stresses.

Keywords: submerged aquatic vegetation, structure from motion, photogrammetry, multispectral, spectroscopy

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Authors: Andreas Kerstan, Darren Robey, Wesam Alvan, David Troiani

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Over the last 3.5 years, Quantum Cascade Lasers (QCL) technology has become increasingly important in infrared (IR) microscopy. The advantages over fourier transform infrared (FTIR) are that large areas of a few square centimeters can be measured in minutes and that the light intensive QCL makes it possible to obtain spectra with excellent S/N, even with just one scan. A firmly established solution of the laser direct infrared imaging (LDIR) 8700 is the analysis of microplastics. The presence of microplastics in the environment, drinking water, and food chains is gaining significant public interest. To study their presence, rapid and reliable characterization of microplastic particles is essential. Significant technical hurdles in microplastic analysis stem from the sheer number of particles to be analyzed in each sample. Total particle counts of several thousand are common in environmental samples, while well-treated bottled drinking water may contain relatively few. While visual microscopy has been used extensively, it is prone to operator error and bias and is limited to particles larger than 300 µm. As a result, vibrational spectroscopic techniques such as Raman and FTIR microscopy have become more popular, however, they are time-consuming. There is a demand for rapid and highly automated techniques to measure particle count size and provide high-quality polymer identification. Analysis directly on the filter that often forms the last stage in sample preparation is highly desirable as, by removing a sample preparation step it can both improve laboratory efficiency and decrease opportunities for error. Recent advances in infrared micro-spectroscopy combining a QCL with scanning optics have created a new paradigm, LDIR. It offers improved speed of analysis as well as high levels of automation. Its mode of operation, however, requires an IR reflective background, and this has, to date, limited the ability to perform direct “on-filter” analysis. This study explores the potential to combine the filter with an infrared reflective surface filter. By combining an IR reflective material or coating on a filter membrane with advanced image analysis and detection algorithms, it is demonstrated that such filters can indeed be used in this way. Vibrational spectroscopic techniques play a vital role in the investigation and understanding of microplastics in the environment and food chain. While vibrational spectroscopy is widely deployed, improvements and novel innovations in these techniques that can increase the speed of analysis and ease of use can provide pathways to higher testing rates and, hence, improved understanding of the impacts of microplastics in the environment. Due to its capability to measure large areas in minutes, its speed, degree of automation and excellent S/N, the LDIR could also implemented for various other samples like food adulteration, coatings, laminates, fabrics, textiles and tissues. This presentation will highlight a few of them and focus on the benefits of the LDIR vs classical techniques.

Keywords: QCL, automation, microplastics, tissues, infrared, speed

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Authors: A. K. Aswathy, Asha Manoharan, Arya Manoharan

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The purpose of this study are to define the nature of oral sensory issues in children with autism spectrum disorder (ASD), identify important components of the assessment and treatment of this issues specific to this population, and delineate specific therapeutic techniques designed to improve assessment and treatment within therapeutic settings. Literature review and case example is used to define the predominant nature of the oral sensory issues that are experienced by some children on the autism spectrum. Characteristics of this complex disorder that can have an impact on feeding skill and behavior are also identified. These factors are then integrated to create assessment and intervention techniques that can be used in conjunction with traditional feeding approaches to facilitate improvements in eating as well as reducing oral apraxic component in this unique population. The complex nature of ASD and its many influences on feeding skills and behavior create the need for modification to both assessment and treatment approaches. Additional research is needed to create therapeutic protocols that can be used by speech-language pathologists to effectively assess and treat feeding and oro motor apraxic difficulties that are commonly encountered in children with ASD.

Keywords: autism, assessment, feeding, intervention, oral sensory issues, oral apraxia

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Authors: Meryem Imane Babaghayou, Asma Abdelhafidi, Salem Fouad Chabira, Mohammed Sebaa

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A challenge of plastics industries is the realization of materials that resist the degradation in its application environment, and that to guarantee a longer life time therefore an optimal time of use. Blown extruded films of low-density polyethylene (LDPE) supplied by SABIC SAUDI ARABIA blown and extruded in SOFIPLAST company in Setif ALGERIA , have been subjected to climatic ageing in a sub-Saharan facility at Laghouat (Algeria) with direct exposure to sun. Samples were characterized by X-ray diffraction (XRD) and differential scanning calorimetry (DSC) techniques after prescribed amounts of time up to 8 months. It has been shown via these two techniques the impact of UV irradiation on the morphological development of a plastic material, especially the crystallinity degree which increases with exposure time. The reason of these morphological changes is related to photooxidative reactions leading to cross linking in the beginning and to chain scissions for an advanced stage of ageing this last ones are the first responsible. The crystallinity degree change is essentially controlled by the secondary crystallization of the amorphous chains whose mobility is enhanced by the chain scission processes. The diffusion of these short segments integrates the surface of the lamellae increasing in this way their thicknesses. The results presented highlight the complexity of the involved phenomena.

Keywords: Low Density poly (Ethylene), crystallinity, ageing, XRD, DSC

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Authors: Gheida J. Shahrour, Martin J. Russell

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The 3D body movement signals captured during human-human conversation include clues not only to the content of people’s communication but also to their culture and personality. This paper is concerned with automatic extraction of this information from body movement signals. For the purpose of this research, we collected a novel corpus from 27 subjects, arranged them into groups according to their culture. We arranged each group into pairs and each pair communicated with each other about different topics. A state-of-art recognition system is applied to the problems of person, culture, and topic recognition. We borrowed modeling, classification, and normalization techniques from speech recognition. We used Gaussian Mixture Modeling (GMM) as the main technique for building our three systems, obtaining 77.78%, 55.47%, and 39.06% from the person, culture, and topic recognition systems respectively. In addition, we combined the above GMM systems with Support Vector Machines (SVM) to obtain 85.42%, 62.50%, and 40.63% accuracy for person, culture, and topic recognition respectively. Although direct comparison among these three recognition systems is difficult, it seems that our person recognition system performs best for both GMM and GMM-SVM, suggesting that inter-subject differences (i.e. subject’s personality traits) are a major source of variation. When removing these traits from culture and topic recognition systems using the Nuisance Attribute Projection (NAP) and the Intersession Variability Compensation (ISVC) techniques, we obtained 73.44% and 46.09% accuracy from culture and topic recognition systems respectively.

Keywords: person recognition, topic recognition, culture recognition, 3D body movement signals, variability compensation

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Authors: H. S. S. Abou El-Mal, H. E. M. Sallam

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This paper presents experimental and analytical study on the behavior of repaired and strengthened shear critical RC beams using externally bonded CFRP bi-directional fabrics. The use of CFRP sheets to repair or strengthen RC beams has been repetitively studied and proven feasible. However, the use of combined repair techniques and applying that method to both plain and FRC beams can maximize the shear capacity of RC shear deficient beams. A total of twelve slender beams were tested under four-point bending. The test parameters included CFRP layout, number of layers and fiber direction, injecting cracks before applying repairing sheets, enhancing the flexural capacity to differentiate between shear repair and strengthening techniques, and concrete matrix types. The findings revealed that applying CFRP sheets increased the overall shear capacity, the amount and orientation of wrapping is of prime importance in both repairing and strengthening, CFRP wrapping could change the failure mode from shear to flexural shear, the use of crack injection combined to CFRP wrapping further improved the shear capacity while, applying the previous method to FRC beams enhanced both shear capacity and failure ductility. Acceptable agreement was found between predicted shear capacities using the Canadian code and the experimental results of the current study.

Keywords: CFRP, FRC, repair, shear strengthening

Procedia PDF Downloads 349

Authors: Abdul Umaro Tholley

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The preservation and packaging of cucumbers are essential to maintain their shelf life and quality. Cucumbers are a perishable food item that is highly susceptible to spoilage due to their high-water content and delicate nature. Therefore, proper preservation and packaging techniques are crucial to extend their shelf life and prevent economic loss. There are several methods of preserving cucumbers, including refrigeration, canning, pickling, and dehydration. Refrigeration is the most used preservation method, as it slows down the rate of deterioration and maintains the freshness and quality of the cucumbers. Canning and pickling are also popular preservation methods that use heat treatment and acidic solutions, respectively, to prevent microbial growth and increase shelf life. Dehydration involves removing the water content from cucumbers to increase their shelf life, but it may affect their texture and taste. Packaging also plays a vital role in preserving cucumbers. The packaging materials should be selected based on their ability to maintain the quality and freshness of the cucumbers. The most used packaging materials for cucumbers are polyethylene bags, which prevent moisture loss and protect the cucumbers from physical damage. Other packaging materials, such as corrugated boxes and wooden crates, may also be used, but they offer less protection against moisture loss and damage. The quality of cucumbers is affected by several factors, including storage temperature, humidity, and exposure to light. Cucumbers should be stored at temperatures between 7 and 10 °C, with a relative humidity of 90-95%, to maintain their freshness and quality. Exposure to light should also be minimized to prevent the formation of yellowing and decay. In conclusion, the preservation and packaging of cucumbers are essential to maintain their quality and extend their shelf life. Refrigeration, canning, pickling, and dehydration are common preservation methods that can be used to preserve cucumbers. The packaging materials used should be carefully selected to prevent moisture loss and physical damage. Proper storage conditions, such as temperature, humidity, and light exposure, should also be maintained to ensure the quality and freshness of cucumbers. Overall, proper preservation and packaging techniques can help reduce economic loss and provide consumers with high-quality cucumbers.

Keywords: cucumbers, preservation, packaging, shelf life

Procedia PDF Downloads 96

Authors: Visith Siriphuwanun, Yodying Punjasawadwong, Suwinai Saengyo, Kittipan Rerkasem

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Objective: To determine incidences and factors associated with perioperative cardiac arrest in trauma patients who received anesthesia for emergency surgery. Design and setting: Retrospective cohort study in trauma patients during anesthesia for emergency surgery at a university hospital in northern Thailand country. Patients and methods: This study was permitted by the medical ethical committee, Faculty of Medicine at Maharaj Nakorn Chiang Mai Hospital, Thailand. We clarified data of 19,683 trauma patients receiving anesthesia within a decade between January 2007 to March 2016. The data analyzed patient characteristics, traumas surgery procedures, anesthesia information such as ASA physical status classification, anesthesia techniques, anesthetic drugs, location of anesthesia performed, and cardiac arrest outcomes. This study excluded the data of trauma patients who had received local anesthesia by surgeons or monitoring anesthesia care (MAC) and the patient which missing more information. The factor associated with perioperative cardiac arrest was identified with univariate analyses. Multiple regressions model for risk ratio (RR) and 95% confidence intervals (CI) were used to conduct factors correlated with perioperative cardiac arrest. The multicollinearity of all variables was examined by bivariate correlation matrix. A stepwise algorithm was chosen at a p-value less than 0.02 was selected to further multivariate analysis. A P-value of less than 0.05 was concluded as statistically significant. Measurements and results: The occurrence of perioperative cardiac arrest in trauma patients receiving anesthesia for emergency surgery was 170.04 per 10,000 cases. Factors associated with perioperative cardiac arrest in trauma patients were age being more than 65 years (RR=1.41, CI=1.02–1.96, p=0.039), ASA physical status 3 or higher (RR=4.19–21.58, p < 0.001), sites of surgery (intracranial, intrathoracic, upper intra-abdominal, and major vascular, each p < 0.001), cardiopulmonary comorbidities (RR=1.55, CI=1.10–2.17, p < 0.012), hemodynamic instability with shock prior to receiving anesthesia (RR=1.60, CI=1.21–2.11, p < 0.001) , special techniques for surgery such as cardiopulmonary bypass (CPB) and hypotensive techniques (RR=5.55, CI=2.01–15.36, p=0.001; RR=6.24, CI=2.21–17.58, p=0.001, respectively), and patients who had a history of being alcoholic (RR=5.27, CI=4.09–6.79, p < 0.001). Conclusion: Incidence of perioperative cardiac arrest in trauma patients receiving anesthesia for emergency surgery was very high and correlated with many factors, especially age of patient and cardiopulmonary comorbidities, patient having a history of alcoholic addiction, increasing ASA physical status, preoperative shock, special techniques for surgery, and sites of surgery including brain, thorax, abdomen, and major vascular region. Anesthesiologists and multidisciplinary teams in pre- and perioperative periods should remain alert for warning signs of pre-cardiac arrest and be quick to manage the high-risk group of surgical trauma patients. Furthermore, a healthcare policy should be promoted for protecting against accidents in high-risk groups of the population as well.

Keywords: perioperative cardiac arrest, trauma patients, emergency surgery, anesthesia, factors risk, incidence

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Authors: Muhammad Fiaz Qamar, Uzma Mehreen, Muhammad Arfan Zaman, Kazim Ali

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Ovine Theileriosis is a world-wide concern, especially in tropical and subtropical areas, due to having tick abundance that has received less awareness in different developed and developing areas due to less worth of sheep, low to the middle level of infection in different small ruminants herd. Across Asia, the prevalence reports have been conducted to provide equivalent calculation of flock and animal level prevalence of Theileriosisin animals. It is a challenge for veterinarians to timely diagnosis & control of Theileriosis and famers because of the nature of the organism and inadequacy of restricted plans to control. All most work is based upon the development of such a technique which should be farmer-friendly, less expensive, and easy to perform into the field. By the timely diagnosis of this disease will decrease the irrational use of the drugs, and other plan was to determine the prevalence of Theileriosis in District Jhang by using the conventional method, PCR and qPCR, and LAMP. We quantify the molecular epidemiology of T.lestoquardiin sheep from Jhang districts, Punjab, Pakistan. In this study, we concluded that the overall prevalence of Theileriosis was (32/350*100= 9.1%) in sheep by using Giemsa staining technique, whereas (48/350*100= 13%) is observed by using PCR technique (56/350*100=16%) in qPCR and the LAMP technique have shown up to this much prevalence percentage (60/350*100= 17.1%). The specificity and sensitivity also calculated in comparison with the PCR and LAMP technique. Means more positive results have been shown when the diagnosis has been done with the help of LAMP. And there is little bit of difference between the positive results of PCR and qPCR, and the least positive animals was by using Giemsa staining technique/conventional method. If we talk about the specificity and sensitivity of the LAMP as compared to PCR, The cross tabulation shows that the results of sensitivity of LAMP counted was 94.4%, and specificity of LAMP counted was 78%. Advances in scientific field must be upon reality based ideas which can lessen the gaps and hurdles in the way of scientific research; the lamp is one of such techniques which have done wonders in adding value and helping human at large. It is such a great biological diagnostic tools and has helped a lot in the proper diagnosis and treatment of certain diseases. Other methods for diagnosis, such as culture techniques and serological techniques, have exposed humans with great danger. However, with the help of molecular diagnostic technique like LAMP, exposure to such pathogens is being avoided in the current era Most prompt and tentative diagnosis can be made using LAMP. Other techniques like PCR has many disadvantages when compared to LAMP as PCR is a relatively expensive, time consuming, and very complicated procedure while LAMP is relatively cheap, easy to perform, less time consuming, and more accurate. LAMP technique has removed hurdles in the way of scientific research and molecular diagnostics, making it approachable to poor and developing countries.

Keywords: distribution, thelaria, LAMP, primer sequences, PCR

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Authors: Mawloud Mosbah, Bachir Boucheham

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We present here the results for a comparative study of some techniques, available in the literature, related to the relevance feedback mechanism in the case of a short-term learning. Only one method among those considered here is belonging to the data mining field which is the K-Nearest Neighbours Algorithm (KNN) while the rest of the methods is related purely to the information retrieval field and they fall under the purview of the following three major axes: Shifting query, Feature Weighting and the optimization of the parameters of similarity metric. As a contribution, and in addition to the comparative purpose, we propose a new version of the KNN algorithm referred to as an incremental KNN which is distinct from the original version in the sense that besides the influence of the seeds, the rate of the actual target image is influenced also by the images already rated. The results presented here have been obtained after experiments conducted on the Wang database for one iteration and utilizing colour moments on the RGB space. This compact descriptor, Colour Moments, is adequate for the efficiency purposes needed in the case of interactive systems. The results obtained allow us to claim that the proposed algorithm proves good results; it even outperforms a wide range of techniques available in the literature.

Keywords: CBIR, category search, relevance feedback, query point movement, standard Rocchio’s formula, adaptive shifting query, feature weighting, original KNN, incremental KNN

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Authors: Irena Alperyte

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Since the regaining of the Independence, the Lithuanian state has been confronting an increasingly dramatic challenge because of the lack of funding sources dedicated to the film industries. During the Soviet times, Lithuanian film was under a total supervision of the Soviet functioners. This means that the responsibility of the state to make movies was of a monopolist character. The filmmakers’ community of the newly independent state needed to learn how to develop their fundraising skills, co-production and marketing techniques. Currently, Lithuanian film is experiencing a new phase concerning its funding: it is exploring the possibilities of motivating the public to invest in entertainment via crowd funding and crowd sourcing techniques and making these activities an alternative way of funding films. The paper aims at the exploration of the existing film financing practices in Lithuania and abroad and provides recommendations on how to improve the alternative Lithuanian film financing strategy via employing new possibilities, such as crowd funding and other alternative marketing tools. Objectives: 1) To examine the theories on creative industries and possibilities for their application. 2) To analyze the current situation in the film industry Lithuania. 3) To analyze the statistical data on movie theater visitors in Lithuania. 4) To discuss alternative options for film financing system. 5) To look through the alternative funding strategies tailored for Lithuanian film industry. 6) To propose recommendations for alternative funding strategies in Lithuanian film fundraising.

Keywords: creative industries, film, funding, fun theory

Procedia PDF Downloads 347

Authors: Ruchi Makani, B. V. R. Reddy

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Mobile Adhoc Networks (MANETs) are gaining popularity due to their potential of providing low-cost mobile connectivity solutions to real-world communication problems. Integrating Intrusion Detection Systems (IDS) in MANETs is a tedious task by reason of its distinctive features such as dynamic topology, de-centralized authority and highly controlled/limited resource environment. IDS primarily use automated soft-computing techniques to monitor the inflow/outflow of traffic packets in a given network to detect intrusion. Use of machine learning techniques in IDS enables system to make decisions on intrusion while continuous keep learning about their dynamic environment. An appropriate IDS model is essential to be selected to expedite this application challenges. Thus, this paper focused on fuzzy-logic based machine learning IDS technique for MANETs and presented their applicability for achieving effectiveness in identifying the intrusions. Further, the selection of appropriate protocol attributes and fuzzy rules generation plays significant role for accuracy of the fuzzy-logic based IDS, have been discussed. This paper also presents the critical attributes of MANET’s routing protocol and its applicability in fuzzy logic based IDS.

Keywords: AODV, mobile adhoc networks, intrusion detection, anomaly detection, fuzzy logic, fuzzy membership function, fuzzy inference system

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Authors: A. Elsayed, M. H. Dewaidar, M. Ghali, M. Elkemary

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The high production cost of the conventional solar cells requires the search for economic methods suitable for solar energy conversion. Cadmium Sulfide (CdS) is one of the most important semiconductors used in photovoltaics, especially in large area solar cells; and can be prepared in a thin film form by a wide variety of deposition techniques. The preparation techniques include vacuum evaporation, sputtering and molecular beam epitaxy. Other techniques, based on chemical solutions, are also used for depositing CdS films with dramatically low-cost compared to other vacuum-based methods. Although this technique is widely used during the last decades, due to simplicity and low-deposition temperature (~100°C), there is still a strong need for more information on the growth process and its relation with the quality of the deposited films. Here, we report on deposition of high-quality CdS thin films; with low-surface roughness ( < 3.0 nm) and sharp optical absorption edge; on low-temperature glass substrates (70°C) using a new method based on the room-temperature chemical solution. In this method, a mixture solution of cadmium acetate and thiourea at room temperature was used under special growth conditions for deposition of CdS films. X-ray diffraction (XRD) measurements were used to examine the crystal structure properties of the deposited CdS films. In addition, UV-VIS transmittance and low-temperature (4K) photoluminescence (PL) measurements were performed for quantifying optical properties of the deposited films. The deposited films show high optical quality as confirmed by observation of both, sharp edge in the transmittance spectra and strong PL intensity at room temperature. Furthermore, we found a strong effect of the growth conditions on the optical band gap of the deposited films; where remarkable red-shift in the absorption edge with temperature is clearly seen in both transmission and PL spectra. Such tuning of both optical band gap of the deposited CdS films can be utilized for tuning the electronic bands' alignments between CdS and other light-harvesting materials, like CuInGaSe or CdTe, for potential improvement in the efficiency of solar cells devices based on these heterostructures.

Keywords: chemical deposition, CdS, optical properties, surface, thin film

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Authors: Ana Miguel

Abstract:

Purpose: Glaucoma is the second cause of worldwide blindness and the first cause of irreversible blindness. Trabeculectomy, the standard glaucoma surgery, has a success rate between 36.0% and 98.0% at three years and a high complication rate, leading to the development of different surgeries, micro-invasive glaucoma surgeries (MIGS). MIGS devices are diverse and have various indications, risks, and effectiveness. We intended to review MIGS’ surgical techniques, indications, contra-indications, and IOP effect. Methods: We performed a literature review of MIGS to differentiate the devices and their reported effectiveness compared to traditional surgery (tubes and blebs). We also conducted a video review of the last 1000 glaucoma surgeries of the author (including MIGS, but also trabeculectomy, deep sclerectomy, and tubes of Ahmed and Baerveldt) performed at glaucoma and advanced anterior segment fellowship in Canada and France, to describe preferred surgical techniques for each. Results: We present the videos with surgical techniques and pearls for each surgery. Glaucoma surgeries included: 1- bleb surgery (namely trabeculectomy, with releasable sutures or with slip knots, deep sclerectomy, Ahmed valve, Baerveldt tube), 2- MIGS with bleb, also known as MIBS (including XEN 45, XEN 63, and Preserflo), 3- MIGS increasing supra-choroidal flow (iStar), 4-MIGS increasing trabecular flow (iStent, gonioscopy-assisted transluminal trabeculotomy - GATT, goniotomy, excimer laser trabeculostomy -ELT), and 5-MIGS decreasing aqueous humor production (endocyclophotocoagulation, ECP). There was also needling (ab interno and ab externo) performed at the operating room and irido-zonulo-hyaloïdectomy (IZHV). Each technique had different indications and contra-indications. Conclusion: MIGS are valuable in glaucoma surgery, such as traditional surgery with trabeculectomy and tubes. All glaucoma surgery can be combined with phacoemulsification (there may be a synergistic effect on MIGS + cataract surgery). In addition, some MIGS may be combined for further intraocular pressure lowering effect (for example, iStents with goniotomy and ECP). A good surgical technique and postoperative management are fundamental to increasing success and good practice in all glaucoma surgery.

Keywords: glaucoma, migs, surgery, video, review

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Authors: Thales Maluf, Nazem Nascimento

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The development of society relies heavily on the total amount of energy obtained and its consumption. Over the years, there has been an advancement on energy attainment, which is directly related to some natural resources and developing systems. Some of these resources should be highlighted for its remarkable presence in world´s energy grid, such as water, petroleum, and gas, while others deserve attention for representing an alternative to diversify the energy grid, like geothermal sources. Therefore, because all these resources can be extracted from the underground, drilling wells is a mandatory activity in terms of exploration, and it involves a previous geological study and an adequate preparation. It also involves a cleaning process and an extraction process that can be executed by different procedures. For that reason, this research aims the enhancement of exploration processes through a comparative analysis of drilling costs and techniques used to produce them. The analysis itself is based on a bibliographical review based on books, scientific papers, schoolwork and mainly explore drilling methods and technologies, equipment used, well measurements, extraction methods, and production costs. Besides techniques and costs regarding the drilling processes, some properties and general characteristics of these sources are also compared. Preliminary studies show that there are some major differences regarding the exploration processes, mostly because these resources are naturally distinct. Water wells, for instance, have hundreds of meters of length because water is stored close to the surface, while oil, gas, and geothermal production wells can reach thousands of meters, which make them more expensive to be drilled. The drilling methods present some general similarities especially regarding the main mechanism of perforation, but since water is a resource stored closer to the surface than the other ones, there is a wider variety of methods. Water wells can be drilled by rotary mechanisms, percussion mechanisms, rotary-percussion mechanisms, and some other simpler methods. Oil and gas production wells, on the other hand, require rotary or rotary-percussion drilling with a proper structure called drill rig and resistant materials for the drill bits and the other components, mostly because they´re stored in sedimentary basins that can be located thousands of meters under the ground. Geothermal production wells also require rotary or rotary-percussion drilling and require the existence of an injection well and an extraction well. The exploration efficiency also depends on the permeability of the soil, and that is why it has been developed the Enhanced Geothermal Systems (EGS). Throughout this review study, it can be verified that the analysis of the extraction processes of energy resources is essential since these resources are responsible for society development. Furthermore, the comparative analysis of costs and well drilling techniques for water, geothermal energy, oil, and gas production, which is the main goal of this research, can enable the growth of energy generation field through the emergence of ideas that improve the efficiency of energy generation processes.

Keywords: drilling, water, oil, Gas, geothermal energy

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Authors: Jan Muhammad, Saad Malik, Fadia W. Al-Azawi, Ali Imran

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In the era of climate variability, rising temperatures are the most significant aspect. In this study PRECIS model data and observed data are used for assessing the temperature change scenarios of Sindh province during the first half of present century. Observed data from various meteorological stations of Sindh are the primary source for temperature change detection. The current scenario (1961–1990) and the future one (2010-2050) are acted by the PRECIS Regional Climate Model at a spatial resolution of 25 * 25 km. Regional Climate Model (RCM) can yield reasonably suitable projections to be used for climate-scenario. The main objective of the study is to map the simulated temperature as obtained from climate model-PRECIS and their comparison with observed temperatures. The analysis is done on all the districts of Sindh in order to have a more precise picture of temperature change scenarios. According to results the temperature is likely to increases by 1.5 - 2.1°C by 2050, compared to the baseline temperature of 1961-1990. The model assesses more accurate values in northern districts of Sindh as compared to the coastal belt of Sindh. All the district of the Sindh province exhibit an increasing trend in the mean temperature scenarios and each decade seems to be warmer than the previous one. An understanding of the change in temperatures is very vital for various sectors such as weather forecasting, water, agriculture, and health, etc.

Keywords: PRECIS Model, real observed data, Arc GIS, interpolation techniques

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Authors: Alaa Koaik, Bruno Jurkiewiez, Sylvain Bel

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Recently, the use of GFRP pultruded profiles increased in the domain of civil engineering especially in the construction of sandwiched slabs and footbridges. However, under heavy loads, the risk of using these profiles increases due to their high deformability and instability as a result of their weak stiffness and orthotropic nature. A practical solution proposes the assembly of these profiles with concrete slabs to create a stiffer hybrid element to support higher loads. The connection of these two elements is established either by traditional means of steel studs (bolting in our case) or bonding technique. These two techniques have their advantages and disadvantages regarding the mechanical behavior and in-situ implementation. This paper presents experimental results of interface characterization and bending behavior of two hybrid beams, PB7 and PB8, designed and constructed using both connection techniques. The results obtained are exploited to design and build a hybrid footbridge BPBP1 which is tested within service limits (elastic domain). Analytical methods are also developed to analyze the behavior of these structures in the elastic range and the ultimate phase. Comparisons show acceptable differences mainly due to the sensitivity of the GFRP moduli as well as the non-linearity of concrete elements.

Keywords: analytical model, concrete, flexural behavior, GFRP pultruded profile, hybrid structure, interconnection slip, push-out

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Authors: Daxa Mishra, R. Harihara, Ankita

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Trapezius muscle pain is the most common musculoskeletal disorder occurring in individuals who work with awkward positions, have repetitive movements and movements with precision demands. Treatment techniques like active release technique (ART) and myofascial release (MFR) can be used to relieve muscle spasm. The aim of the study is to compare the effect of ART and MFR on the upper trapezius muscle spasm. Methodology: A series of 60 patients of both sexes between the age group of 20 and 55 with upper trapezius spasm were divided into two groups by computerized randomization. Subjects in each group received treatment in the form of either ART or MFR for the period of seven days. cervical range of motion (ROM), neck disability index scale (NDI) and visual analog scale (VAS) tools were used to measure the outcome. Results: Paired Sample ‘t’ test was used to compare the Outcome differences within each group, while Independent ‘t’ test was used to compare the differences between the two groups for the same outcome measures. The improvement was found in both the groups at 7th day following intervention, but the group which received ART showed significant improvements as compared to group which received MFR. Conclusion: Although both techniques are effective in alleviation of symptoms and associated disability in upper trapezius muscle spasm, ART gave better results as compared to MRF.

Keywords: goniometer, myofascial release, active release, physiotherapy

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Authors: Aschalew C. Workneh, K. S. Hari Prasad, C. S. P. Ojha

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The crop water stress index (CWSI) is a cost-effective, non-destructive, and simple technique for tracking the start of crop water stress. This study investigated the feasibility of CWSI derived from canopy temperature to detect the water status of wheat crops. Artificial intelligence (AI) techniques have become increasingly popular in recent years for determining CWSI. In this study, the performance of two AI techniques, adaptive neuro-fuzzy inference system (ANFIS) and self-organizing maps (SOM), are compared while determining the CWSI of paddy crops. Field experiments were conducted for varying irrigation water applications during two seasons in 2022 and 2023 at the irrigation field laboratory at the Civil Engineering Department, Indian Institute of Technology Roorkee, India. The ANFIS and SOM-simulated CWSI values were compared with the experimentally calculated CWSI (EP-CWSI). Multiple regression analysis was used to determine the upper and lower CWSI baselines. The upper CWSI baseline was found to be a function of crop height and wind speed, while the lower CWSI baseline was a function of crop height, air vapor pressure deficit, and wind speed. The performance of ANFIS and SOM were compared based on mean absolute error (MAE), mean bias error (MBE), root mean squared error (RMSE), index of agreement (d), Nash-Sutcliffe efficiency (NSE), and coefficient of correlation (R²). Both models successfully estimated the CWSI of the paddy crop with higher correlation coefficients and lower statistical errors. However, the ANFIS (R²=0.81, NSE=0.73, d=0.94, RMSE=0.04, MAE= 0.00-1.76 and MBE=-2.13-1.32) outperformed the SOM model (R²=0.77, NSE=0.68, d=0.90, RMSE=0.05, MAE= 0.00-2.13 and MBE=-2.29-1.45). Overall, the results suggest that ANFIS is a reliable tool for accurately determining CWSI in wheat crops compared to SOM.

Keywords: adaptive neuro-fuzzy inference system, canopy temperature, crop water stress index, self-organizing map, wheat

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Authors: Dimitrios I. Tselentis, Simon P. Washington

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Considerable literature has been focused over the last few decades on forecasting the consumer demand of Energy Efficient Vehicles (EEVs). These methodological issues range from how to capture recent purchase decisions in revealed choice studies and how to set up experiments in stated preference (SP) studies, and choice of analysis method for analyzing such data. This paper reviews the plethora of published studies on the field of forecasting demand of EEVs since 1980, and provides a review and annotated bibliography of that literature as it pertains to this particular demand forecasting problem. This detailed review addresses the literature not only to Transportation studies, but specifically to the problem and methodologies around forecasting to the time horizons of planning studies which may represent 10 to 20 year forecasts. The objectives of the paper are to identify where existing gaps in literature exist and to articulate where promising methodologies might guide longer term forecasting. One of the key findings of this review is that there are many common techniques used both in the field of new product demand forecasting and the field of predicting future demand for EEV. Apart from SP and RP methods, some of these new techniques that have emerged in the literature in the last few decades are survey related approaches, product diffusion models, time-series modelling, computational intelligence models and other holistic approaches.

Keywords: demand forecasting, Energy Efficient Vehicles (EEVs), forecasting methodologies review, methodological approaches

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Authors: Suzan M. Shahin, Mohammed A. Salem

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Essential oils are expensive phytochemicals produced and extracted from specific species belonging to particular families in the plant kingdom. In the United Arab Emirates country (UAE), which is located in the arid region of the world, nine species, from the Lamiaceae family, having the capability to produce therapeutic grade essential oils. These species include; Mentha spicata, Ocimum forskolei, Salvia macrosiphon, Salvia aegyptiaca, Salvia macilenta, Salvia spinosa, Teucrium polium, Teucrium stocksianum, and Zataria multiflora. Although, such potential species are indigenous to the UAE, however, there are almost no studies available to investigate the chemical composition and the quality of the extracted essential oils under the UAE climatological conditions. Therefore, great attention has to be given to such valuable natural resources, through conducting highly supported research projects, tailored to the UAE conditions, and investigating different extraction techniques, including the application of the latest available technologies, such as superficial fluid CO2. This is crucially needed; in order to accomplish the greatest possibilities in the medicinal field, specifically in the discovery of new therapeutic chemotypes, as well as, to achieve the sustainability of this natural resource in the country.

Keywords: essential oils, extraction techniques, Lamiaceae, traditional medicine, United Arab Emirates (UAE)

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Authors: Ayad Dalloo, Sulaf Dalloo

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Electrocardiogram (ECG) recording is prone to complications, on analysis by physicians, due to noise and artifacts, thus creating ambiguity leading to possible error of diagnosis. Such drawbacks may be overcome with the advent of high resolution Methods, such as Discrete Wavelet Analysis and Digital Signal Processing (DSP) techniques. This ECG signal analysis is implemented in three stages: ECG preprocessing, features extraction and classification with the aim of realizing high resolution ECG diagnosis and improved detection of abnormal conditions in the heart. The preprocessing stage involves removing spurious artifacts (noise), due to such factors as muscle contraction, motion, respiration, etc. ECG features are extracted by applying DSP and suggested sloping method techniques. These measured features represent peak amplitude values and intervals of P, Q, R, S, R’, and T waves on ECG, and other features such as ST elevation, QRS width, heart rate, electrical axis, QR and QT intervals. The classification is preformed using these extracted features and the criteria for cardiovascular diseases. The ECG diagnostic system is successfully applied to 12-lead ECG recordings for 12 cases. The system is provided with information to enable it diagnoses 15 different diseases. Physician’s and computer’s diagnoses are compared with 90% agreement, with respect to physician diagnosis, and the time taken for diagnosis is 2 seconds. All of these operations are programmed in Matlab environment.

Keywords: ECG diagnostic system, QRS detection, ECG baseline removal, cardiovascular diseases

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Authors: Farid Khosravikia, Patricia Clayton

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The main objective of this work is to evaluate the advantages and disadvantages of various machine learning techniques in two key steps of seismic hazard and risk assessment of different types of structures. The first step is the development of ground-motion models, which are used for forecasting ground-motion intensity measures (IM) given source characteristics, source-to-site distance, and local site condition for future events. IMs such as peak ground acceleration and velocity (PGA and PGV, respectively) as well as 5% damped elastic pseudospectral accelerations at different periods (PSA), are indicators of the strength of shaking at the ground surface. Typically, linear regression-based models, with pre-defined equations and coefficients, are used in ground motion prediction. However, due to the restrictions of the linear regression methods, such models may not capture more complex nonlinear behaviors that exist in the data. Thus, this study comparatively investigates potential benefits from employing other machine learning techniques as statistical method in ground motion prediction such as Artificial Neural Network, Random Forest, and Support Vector Machine. The results indicate the algorithms satisfy some physically sound characteristics such as magnitude scaling distance dependency without requiring pre-defined equations or coefficients. Moreover, it is shown that, when sufficient data is available, all the alternative algorithms tend to provide more accurate estimates compared to the conventional linear regression-based method, and particularly, Random Forest outperforms the other algorithms. However, the conventional method is a better tool when limited data is available. Second, it is investigated how machine learning techniques could be beneficial for developing probabilistic seismic demand models (PSDMs), which provide the relationship between the structural demand responses (e.g., component deformations, accelerations, internal forces, etc.) and the ground motion IMs. In the risk framework, such models are used to develop fragility curves estimating exceeding probability of damage for pre-defined limit states, and therefore, control the reliability of the predictions in the risk assessment. In this study, machine learning algorithms like artificial neural network, random forest, and support vector machine are adopted and trained on the demand parameters to derive PSDMs for them. It is observed that such models can provide more accurate estimates of prediction in relatively shorter about of time compared to conventional methods. Moreover, they can be used for sensitivity analysis of fragility curves with respect to many modeling parameters without necessarily requiring more intense numerical response-history analysis.

Keywords: artificial neural network, machine learning, random forest, seismic risk analysis, seismic hazard analysis, support vector machine

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Authors: Jake Hindmarch, Edward Farley, Norman Eizenberg, Mark Midwinter

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There is a need to bring the anatomical knowledge of medical students up to the standards required by surgical specialties. Contention exists amongst anatomists, clinicians, and surgeons about the standard of anatomical knowledge medical students need. The aim of this study was to explore the standards which the Royal Australasian College of Surgeons are applying knowledge of anatomy. Furthermore, to align medical school teaching to what the surgical profession requires from graduates.: The 2018 volume of the ANZ Journal of Surgery was narrowed down to 254 articles by applying the search term “Anatomy”. The main topic was then extracted from each paper. The content of the paper was assessed for ‘novel description’ or ‘application’ of anatomical knowledge’ and classified accordingly. The majority of papers with an anatomical focus was from the general surgery specialty, which focused on surgical techniques, outcomes and management. Vascular surgery had the highest percentage of papers with a novel description and application of anatomy. Cardiothoracic and paediatric surgery had no papers with a novel description of anatomy. Finally, a novel application of anatomy was the main focus of each speciality. Firstly, a high proportion of novel applications and descriptions of anatomy are in general surgery. Secondly, vascular surgery had the largest proportion of novel application and description of anatomy, namely due to the rise of therapeutic imaging and endovascular techniques. Finally, all disciplines demonstrated a trend towards having a higher proportion of novel application of anatomical knowledge

Keywords: anatomical knowledge, anatomy, surgery, novel anatomy

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Authors: Saifullah Karimullah

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Additive manufacturing techniques are becoming more common with the latest technological advancements. It is composed to bring a revolution in the way products are designed, planned, manufactured, and distributed to end users. Fused deposition modeling (FDM) based 3D printing is one of those promising aspects that have revolutionized the prototyping processes. The purpose of this design and study project is to design a customized laboratory-scale FDM-based 3D printer from locally available sources. The primary goal is to design and fabricate the FDM-based 3D printer. After the fabrication, a tensile test specimen would be designed in Solid Works or [Creo computer-aided design (CAD)] software. A .stl file is generated of the tensile test specimen through slicing software and the G-codes are inserted via a computer for the test specimen to be printed. Different parameters were under studies like printing speed, layer thickness and infill density of the printed object. Some parameters were kept constant such as temperature, extrusion rate, raster orientation etc. Different tensile test specimens were printed for a different sets of parameters of the FDM-based 3d printer. The tensile test specimen were subjected to tensile tests using a universal testing machine (UTM). Design Expert software has been used for analyses, So Different results were obtained from the different tensile test specimens. The best, average and worst specimen were also observed under a compound microscope to investigate the layer bonding in between.

Keywords: additive manufacturing techniques, 3D printing, CAD software, UTM machine

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Authors: Anil S. Khopkar, Kartik S. Pandya

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Overvoltage in power systems is a phenomenon that cannot be avoided. However, it can be controlled to a certain extent. Power system equipment is to be protected against overvoltage to avoid system failure. Metal Oxide Surge Arresters (MOSA) are connected to the system for the protection of the power system against overvoltages. The MOSA will behave as an insulator under normal working conditions, where it offers a conductive path under voltage conditions. MOSA consists of zinc oxide elements (ZnO Blocks), which have non-linear V-I characteristics. ZnO blocks are connected in series and fitted in ceramic or polymer housing. This degrades due to the aging effect under continuous operation. Degradation of zinc oxide elements increases the leakage current flowing from the surge arresters. This Increased leakage current results in the increased temperature of the surge arrester, which further decreases the resistance of zinc oxide elements. As a result, leakage current increases, which again increases the temperature of a MOSA. This creates thermal runaway conditions for MOSA. Once it reaches the thermal runaway condition, it cannot return to normal working conditions. This condition is a primary cause of premature failure of surge arresters, as MOSA constitutes a core protective device for electrical power systems against transients. It contributes significantly to the reliable operation of the power system network. Hence, the condition monitoring of surge arresters should be done at periodic intervals. Online and Offline condition monitoring techniques are available for surge arresters. Offline condition monitoring techniques are not very popular as they require removing surge arresters from the system, which requires system shutdown. Hence, online condition monitoring techniques are very popular. This paper presents the evaluation technique for the surge arrester condition based on the leakage current analysis. Maximum amplitude of total leakage current (IT), Maximum amplitude of fundamental resistive leakage current (IR) and maximum amplitude of third harmonic resistive leakage current (I3rd) have been analyzed as indicators for surge arrester condition monitoring.

Keywords: metal oxide surge arrester (MOSA), over voltage, total leakage current, resistive leakage current

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Authors: Bhagwant Singh, Sikander Singh Cheema

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This paper examines firewall mechanisms routinely implemented for network security in depth. A firewall can't protect you against all the hazards of unauthorized networks. Consequently, many kinds of infrastructure are employed to establish a secure network. Firewall strategies have already been the subject of significant analysis. This study's primary purpose is to avoid unnecessary connections by combining the capability of the firewall with the use of additional firewall mechanisms, which include packet filtering and NAT, VPNs, and backdoor solutions. There are insufficient studies on firewall potential and combined approaches, but there aren't many. The research team's goal is to build a safe network by integrating firewall strength and firewall methods. The study's findings indicate that the recommended concept can form a reliable network. This study examines the characteristics of network security and the primary danger, synthesizes existing domestic and foreign firewall technologies, and discusses the theories, benefits, and disadvantages of different firewalls. Through synthesis and comparison of various techniques, as well as an in-depth examination of the primary factors that affect firewall effectiveness, this study investigated firewall technology's current application in computer network security, then introduced a new technique named "tight coupling firewall." Eventually, the article discusses the current state of firewall technology as well as the direction in which it is developing.

Keywords: firewall strategies, firewall potential, packet filtering, NAT, VPN, proxy services, firewall techniques

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Authors: Peter Adekunle, Clinton Aigbavboa, Matthew Ikuabe, Opeoluwa Akinradewo

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The future of machine learning (ML) in building may seem like a distant idea that will take decades to materialize, but it is actually far closer than previously believed. In reality, the built environment has been progressively increasing interest in machine learning. Although it could appear to be a very technical, impersonal approach, it can really make things more personable. Instead of eliminating humans out of the equation, machine learning allows people do their real work more efficiently. It is therefore vital to evaluate the factors influencing the implementation and challenges of implementing machine learning techniques in the South African built environment. The study's design was one of a survey. In South Africa, construction workers and professionals were given a total of one hundred fifty (150) questionnaires, of which one hundred and twenty-four (124) were returned and deemed eligible for study. Utilizing percentage, mean item scores, standard deviation, and Kruskal-Wallis, the collected data was analyzed. The results demonstrate that the top factors influencing the adoption of machine learning are knowledge level and a lack of understanding of its potential benefits. While lack of collaboration among stakeholders and lack of tools and services are the key hurdles to the deployment of machine learning within the South African built environment. The study came to the conclusion that ML adoption should be promoted in order to increase safety, productivity, and service quality within the built environment.

Keywords: machine learning, implementation, built environment, construction stakeholders

Procedia PDF Downloads 132