Search results for: post classification change detection

Authors: Emmanuel Okine Neokye, Xiuquan Wang, Krishna K. Thakur, Pedro Quijon, Rana Ali Nawaz, , Sana Basheer

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Oysters are enriched with high-quality protein and are widely known for their exquisite taste. The production of oysters plays an important role in the local economies of coastal communities in many countries, including Atlantic Canada, because of their high economic value. However, because of the changing climatic conditions in recent years, oyster aquaculture faces potentially negative impacts, such as increasing water acidification, rising water temperatures, high salinity, invasive species, algal blooms, and other environmental factors. Although a few isolated effects of climate change on oyster aquaculture have been reported in recent years, it is not well understood how climate change will affect oyster aquaculture from a systematic perspective. In the first part of this study, we present a systematic review of the impacts of climate change and some key environmental factors affecting oyster production on a global scale. The study also identifies knowledge gaps and challenges. In addition, we present key research directions that will facilitate future investigations.

Keywords: climate change, oyster production, oyster aquaculture, greenhouse gases

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Authors: Tahsien Mohamed Okasha

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We hypothesized that Post cardiac arrest patients with Glasgow coma scale (GCS) score of less than (8) and who will be exposed to therapeutic hypothermia protocol will exhibit improvement in their neurological performance. Purposive sample of 17 patients who were fulfilling the inclusion criteria during one year collected. The study carried out using Quasi-experimental research design. Four Tools used for data collection of this study: Demographic and medical data sheet, Post cardiac arrest health assessment sheet, Bedside Shivering Assessment Scale (BSAS), and Glasgow Pittsburgh cerebral performance category scale (CPC). Result: the mean age was X̅ ± SD = 53 ± 8.122 years, 47.1% were arrested because of cardiac etiology. 35.3% with initial arrest rhythm ventricular tachycardia (VT), 23.5% with ventricular fibrillation (VF), and 29.4% with A-Systole. Favorable neurological outcome was seen among 70.6%. There was significant statistical difference in WBC, Platelets, blood gases value, random blood sugar. Also Initial arrest rhythm, etiology of cardiac arrest, and shivering status were significantly correlated with cerebral performance categories score. therapeutic hypothermia has positive effects on neurological performance among post cardiac arrest patients with GCS score of less than (8). replication of the study on larger probability sample, with randomized control trial design. Further study for suggesting nursing protocol for patients undergoing therapeutic hypothermia.

Keywords: therapeutic hypothermia, neurological performance, after resuscitation from cardiac arrest., resuscitation

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Authors: Saman Namvarrechi, Armin A. Dormeny, Javad Dargahi, Mojtaba Kahrizi

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Since last two decades, minimally invasive surgery (MIS) has grown significantly due to its advantages compared to the traditional open surgery like less physical pain, faster recovery time and better healing condition around incision regions; however, one of the important challenges in MIS is getting an effective sensing feedback within the patient’s body during operations. Therefore, surgeons need efficient tactile sensing like determining the hardness of contact tissue for investigating the patient’s health condition. In such a case, MIS tactile sensors are preferred to be able to provide force/pressure sensing, force position, lump detection, and softness sensing. Among different pressure sensor technologies, the piezoelectric operating principle is the fittest for MIS’s instruments, such as catheters. Using PVDF with its copolymer, TrFE, as a piezoelectric material, is a common method of design and fabrication of a tactile sensor due to its ease of implantation and biocompatibility. In this research, PVDF-TrFE polymer is deposited via spin-coating method and treated with various post-deposition processes to investigate its piezoelectricity and amount of electroactive β phase. These processes include different post thermal annealing, the effect of spin-coating speed, different layer of deposition, and the presence of additional hydrate salt. According to FTIR spectroscopy and SEM images, the amount of the β phase and porosity of each sample is determined. In addition, the optimum experimental study is established by considering every aspect of the fabrication process. This study clearly shows the effective way of deposition and fabrication of a tactile PVDF-TrFE based sensor and an enhancement methodology to have a higher β phase and piezoelectric constant in order to have a better sense of touch at the end effector of biomedical devices.

Keywords: β phase, minimally invasive surgery, piezoelectricity, PVDF-TrFE, tactile sensor

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Authors: Endrick Barnacin, Jean-Luc Henry, Jimmy Nagau, Jack Molinie

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Palynology is a field of interest in many disciplines due to its multiple applications: chronological dating, climatology, allergy treatment, and honey characterization. Unfortunately, the analysis of a pollen slide is a complicated and time consuming task that requires the intervention of experts in the field, which are becoming increasingly rare due to economic and social conditions. That is why the need for automation of this task is urgent. A lot of studies have investigated the subject using different standard image processing descriptors and sometimes hand-crafted ones.In this work, we make a comparative study between classical feature extraction methods (Shape, GLCM, LBP, and others) and Deep Learning (CNN, Autoencoders, Transfer Learning) to perform a recognition task over 80 regional pollen species. It has been found that the use of Transfer Learning seems to be more precise than the other approaches

Keywords: pollens identification, features extraction, pollens classification, automated palynology

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Authors: Afsal Mohammed Kadavilpparampu, Haider A. J. Al Lawati, Fakhr Eldin O. Suliman, Salma M. Z. Al Kindy

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In this work, we evaluated the appropriateness of various oxidants that can be used potentially with Ru(bipy)32+ CL system while performing CL detection in a microfluidic device using eight common active pharmaceutical ingredients- ciprofloxacin, hydrochlorothiazide, norfloxacin, buspirone, fexofenadine, cetirizine, codeine, and dextromethorphan. This is because, microfludics have very small channel volume and the residence time is also very short. Hence, a highly efficient oxidant is required for on-chip CL detection to obtain analytically acceptable CL emission. Three common oxidants were evaluated, lead dioxide, cerium ammonium sulphate and ammonium peroxydisulphate. Results obtained showed that ammonium peroxydisulphate is the most appropriate oxidant which can be used in microfluidic setup and all the tested analyte give strong CL emission while using this oxidant. We also found that Ru(bipy)33+ generated off-line by oxidizing [Ru(bipy)3]Cl2.6H2O in acetonitrile under acidic condition with lead dioxide was stable for more than 72 hrs. A highly sensitive microbore HPLC- CL method using ammonium peroxydisulphate as an oxidant in a microfluidic on-chip CL detection has been developed for the analyses of fixed-dose combinations of pseudoephedrine (PSE), fexofenadine (FEX) and cetirizine (CIT) in biological fluids and pharmaceutical formulations with minimum sample pre-treatment.

Keywords: oxidants, microbore High Performance Liquid Chromatography, chemiluminescence, microfluidics

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Authors: Ana Cristina A. P. Carvalho, Solange Teles Da Silva

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In April, 174 countries signed the Paris Agreement, a multilateral agreement on climate change which deals with greenhouse gas emissions, mitigation, adaptation, finance, access to information, transparency, among other subjects related to the environment. Since then, Parties shall cooperate in taking measures, as appropriate, to enhance climate change education, training, public awareness, public participation and public access to information, recognizing the importance of these steps with respect to enhancing actions under this Agreement. This paper aims to analyze the consequences of this new rule in terms of the implementation of the Agreement, collecting data from Brazilian and Canadian legislations in order to identify if these countries have rules complying with the Treaty, the steps that have been already taken and if they could be used as examples for other countries. The analysis will take into consideration the different kinds of climate change information, means of transparency, reliability of the data and how to spread the information. The methodology comprehends a comparative legal research based on both the Paris Agreement and domestic laws of Brazil and Canada, as well as on doctrine and Court decisions. The findings can contribute to the implementation of the Paris Agreement through compliance with this Treaty at countries’ domestic and policy level.

Keywords: climate change information, domestic legislation, Paris Agreement, public policy

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Authors: Magdy B. Eteiba, Wael Ismael Wahba, Shimaa Barakat

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This paper presents a fault identification, classification and fault location estimation method based on Discrete Wavelet Transform and Adaptive Network Fuzzy Inference System (ANFIS) for medium voltage cable in the distribution system. Different faults and locations are simulated by ATP/EMTP, and then certain selected features of the wavelet transformed signals are used as an input for a training process on the ANFIS. Then an accurate fault classifier and locator algorithm was designed, trained and tested using current samples only. The results obtained from ANFIS output were compared with the real output. From the results, it was found that the percentage error between ANFIS output and real output is less than three percent. Hence, it can be concluded that the proposed technique is able to offer high accuracy in both of the fault classification and fault location.

Keywords: ANFIS, fault location, underground cable, wavelet transform

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Authors: Sai Snehitha Yadavalli, K. Sruthi, Swati Ghosh Acharyya

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Heavy metal ions are toxic to humans and all living species when exposed in large quantities or for long durations. Though Fe acts as a nutrient, when intake is in large quantities, it becomes toxic. These toxic heavy metal ions, when consumed through water, will cause many disorders and are harmful to all flora and fauna through biomagnification. Specifically, humans are prone to innumerable diseases ranging from skin to gastrointestinal, neurological, etc. In higher quantities, they even cause cancer in humans. Detection of these toxic heavy metal ions in water is thus important. Traditionally, the detection of heavy metal ions in water has been done by techniques like Inductively Coupled Plasma Mass Spectroscopy (ICPMS) and Atomic Absorption Spectroscopy (AAS). Though these methods offer accurate quantitative analysis, they require expensive equipment and cannot be used for on-site measurements. Anodic Stripping Voltammetry is a good alternative as the equipment is affordable, and measurements can be made at the river basins or lakes. In the current study, Square Wave Anodic Stripping Voltammetry (SWASV) was used to detect the heavy metal ions in water. Literature reports various electrodes on which deposition of heavy metal ions was carried out like Bismuth, Polymers, etc. The working electrode used in this study is a polyvinyl chloride (PVC) modified glassy carbon electrode (GCE). Ag/AgCl reference electrode and Platinum counter electrode were used. Biologic Potentiostat SP 300 was used for conducting the experiments. Through this work of simultaneous detection, four heavy metal ions were successfully detected at a time. The influence of modifying GCE with PVC was studied in comparison with unmodified GCE. The simultaneous detection of Cd⁺², Fe⁺², Co⁺², Pb⁺² heavy metal ions was done using PVC modified GCE by drop casting 1 wt.% of PVC dissolved in Tetra Hydro Furan (THF) solvent onto GCE. The concentration of all heavy metal ions was 0.2 mg/L, as shown in the figure. The scan rate was 0.1 V/s. Detection parameters like pH, scan rate, temperature, time of deposition, etc., were optimized. It was clearly understood that PVC helped in increasing the sensitivity and selectivity of detection as the current values are higher for PVC-modified GCE compared to unmodified GCE. The peaks were well defined when PVC-modified GCE was used.

Keywords: cadmium, cobalt, electrochemical sensing, glassy carbon electrodes, heavy metal Ions, Iron, lead, polyvinyl chloride, potentiostat, square wave anodic stripping voltammetry

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Authors: Muhammad Rasyid Angkotasan

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The soil is a dense granules and arrangement of the pores that are related to each other, so that the water can flow from one point which has higher energy to a point that has lower energy. The flow of water through the pores of the porous ground is urgently needed in water seepage estimates in ground water pumping problems, investigate for underground construction, as well as analyzing the stability of the construction of Weirs. Climate change resulted in long-term changes in the distribution of weather patterns are statistically throughout the period start time of decades to millions of years. In other words, changes in the average weather circumstances or a change in the distribution of weather events, on average, for example, the number of extreme weather events that increasingly a lot or a little. Climate change is limited to a particular regional or can occur in all regions of the Earth. Geographical location between two continents and two oceans and is located around the equator is klimatologis factor is the cause of flooding and drought in Indonesia. This caused Indonesia' geographical position is on a hemisphere with a tropical monsoon climate is very sensitive to climatic anomaly El Nino Southern Oscillation (ENSO). ENSO causes drought occurrence in sea surface temperature conditions in the Pacific Equator warms up to the middle part of the East (El Nino). Based on the analysis of the climate of the last 30 years show that there is a tendency, the formation of a new pattern of climate causes the onset of climate change. The impact of climate change on the occurrence of the agricultural sector is the bergesernya beginning of the dry season which led to the above-mentioned pattern planting due to drought. The impact of climate change (drought) which is very extreme in Indonesia affect the shrinkage dimensions grain land and reduced the value of a percentage of the soil Plasticity Index caused by climate change.

Keywords: climate change, soil shrinkage, plasticity index, shrinking dimensions

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Authors: Mohamed Haffar, Khalil Al-Hyari, Mohammed Khair Abu Zaid, Ramadane Djbarni, Mohammed Hamdan

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While employee readiness for change (ERFC) is recognised as critical for total quality management (TQM) implementation, there is a lack of systematic and empirical studies regarding the relationship between ERFC dimensions and TQM. Therefore, this study proposes to fill this gap by providing empirical evidence leading to advancement in the understanding of the influences of ERFC components on TQM implementation. The empirical data for this study was drawn from a survey of 400 middle and senior managers of Jordanian firms. The analysis of the collected data, which was conducted using Structural Equation Modeling technique, revealed that three of the ERFC components, namely personally beneficial, change self-efficacy and management support are the most supportive ERFC dimensions for TQM implementation. Therefore, this paper makes a novel contribution by providing a refined and deeper comprehension of the relationships between ERFCs and TQM implementation.

Keywords: total quality management, employee readiness for change, manufacturing organisations, Jordan

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Authors: Meihua Fang, Tao Fei

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Post-processing can effectively improve the resistance to laser damage in multilayer films used in a high power laser system. In this work, HfO₂/SiO₂ multilayer films are prepared by e-beam evaporation and then β-ray irradiation is employed as the post-processing method. The particle irradiation affects the laser induced damage threshold (LIDT), which includes defects, surface roughness, packing density, and residual stress. The residual stress that is relaxed during irradiation changes from compressive stress into tensile stress. Our results indicate that appropriate tensile stress can improve LIDT remarkably. In view of the fact that LIDT rises from 8 J/cm² to 12 J/cm², i.e., 50% increase, after the film has been irradiated by 2.2×10¹³/cm² β-ray, the particle irradiation can be used as a controllable and desirable post-processing method to improve the resistance to laser induced damage.

Keywords: β-ray irradiation, multilayer film, residual stress, laser-induced damage threshold

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Authors: Karim Saeidi

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Safflower capsule fly, Acanthiophilus helianthi Rossi (Diptera: Tephritidae), is a key pest of safflower in Iran. The toxicity of Methidathion, Malathion, Deltamethrin, and Lufenuron to adult males and females of Acanthiophilus helianthi was studied under laboratory conditions. Malathion was the most toxic among the tested compounds followed by Methidathion, Lufenuron, and Deltamethrin to Acanthiophilus helianthi at 24 h post treatment, the respective LC50 values were 0.40 ppm, 0.68 ppm, 10.99 ppm, and 11.75 ppm for males and 0.46 ppm, 0.97 ppm, 13.45 ppm, and 16.32 ppm for females. At 48 h post treatment, Malathion was the most toxic followed by Methidathion, Deltamethrin, and Lufenuron to Acanthiophilus helianthi, LC50 values were 0.08 ppm, 0.54 ppm, 1.80 ppm, and 1.96 ppm for males and 0.34 ppm, 0.64 ppm, 1.88 ppm, and 2.37 ppm for females. At 72 h post treatment, Malathion was the most toxic followed by Methidathion, Lufenuron, and Deltamethrin to Acanthiophilus helianthi LC50 values were 0.04 ppm, 0.33 ppm, 0.44 ppm, and 0.71 ppm for males and 0.09 ppm, 0.36 ppm, 0.75 ppm, and 0.82 ppm for females. It is observed that LC50 values for treated adult females increased more than in the treated adult males at 24 h, 48 h, and 72 h post treatment. It means that the adult males were more susceptible to the tested insecticides than the adult females.

Keywords: safflower, Methidathion, Deltamethrin, Lufenuron, Malathion, Tephritidae, safflower capsule fly, Acanthiophilus helianthi

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Authors: Julia DeVoy, Olivia Berlin

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The United States exports over 1.6 billion pounds of post-consumer textiles every year, primarily to countries in the Global South. These textiles make their way to landfills and open-air dumps where they decompose, contaminating water systems and releasing harmful greenhouse gases. Through this inequitable system of waste disposal, countries with less political and economic power are coerced into accepting the environmental and health consequences of over-consumption in the Global North. Thus, the global trade of post-consumer textile waste represents a serious issue of environmental justice and a public health hazard. Our research located, characterizes, and quantifies the environmental and human health risks that occur when post-consumer textiles are left to decompose in landfills and open-air dumps in the Global South. In our work, we make use of United Nations International Trade Statistics data to map the global distribution of post-consumer textiles exported from the United States. Next, we present our landfill simulating reactor designed to measure toxicity of leachate resulting from the decomposition of textiles in developing countries and to quantify the related greenhouse gas emissions. This design makes use of low-cost and sustainable materials to promote frugal innovation and make landfill reactors more accessible. Finally, we describe how the data generated from these tools can be leveraged to inform individual consumer behaviors, local policies around textile waste disposal, and global advocacy efforts to mitigate the environmental harms caused by textile waste.

Keywords: sustainability, textile design, public health, built environment

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Authors: Aly Elshafei, Daniela Romano

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With the development of autonomous vehicles, a human-machine interaction (HMI) system is needed for a safe transition of control when a takeover request (TOR) is required. An important part of the HMI system is the ability to monitor the level of situational awareness (SA) of any driver in real-time, in different scenarios, and without any pre-calibration. Presenting state-of-the-art machine learning models used to measure SA is the purpose of this systematic review. Investigating the limitations of each type of sensor, the gaps, and the most suited sensor and computational model that can be used in driving applications. To the author’s best knowledge this is the first literature review identifying online and offline classification methods used to measure SA, explaining which measurements are subject or session-specific, and how many classifications can be done with each classification model. This information can be very useful for researchers measuring SA to identify the most suited model to measure SA for different applications.

Keywords: situational awareness, autonomous driving, gaze metrics, EEG, ECG

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Authors: Ashlesha Khanapure, Harsh Kashyap, Abhinav Anand, Sanjana Habib, Anupama Bidargaddi

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Technologies that are developing quickly are being developed daily in a variety of disciplines, particularly the medical field. For the purpose of detecting bone fractures in X-ray pictures of different body segments, our work compares the ResNet-50 and MobileNetV3 architectures. It evaluates accuracy and computing efficiency with X-rays of the elbow, hand, and shoulder from the MURA dataset. Through training and validation, the models are evaluated on normal and fractured images. While ResNet-50 showcases superior accuracy in fracture identification, MobileNetV3 showcases superior speed and resource optimization. Despite ResNet-50’s accuracy, MobileNetV3’s swifter inference makes it a viable choice for real-time clinical applications, emphasizing the importance of balancing computational efficiency and accuracy in medical imaging. We created a graphical user interface (GUI) for MobileNet V3 model bone fracture detection. This research underscores MobileNetV3’s potential to streamline bone fracture diagnoses, potentially revolutionizing orthopedic medical procedures and enhancing patient care.

Keywords: CNN, MobileNet V3, ResNet-50, healthcare, MURA, X-ray, fracture detection

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Authors: Nambiar Ritu, Ali Ban, Munawar Farida, Israell Imelda, T. Farouk Eman Rasheeda, Jangalgi Renuka, S. Boma Nellie

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Aim: To define the ultrasonographic endometrial thickness (USG ET) cutoff for evacuation of retained pieces of conception (ERPC). Background: Studies of conservative management of 1st trimester miscarriage have questioned the need for post miscarriage curettage. Therapeutic decision making with transvaginal scan post miscarriage endometrial thickness in patients clinically thought to be incomplete miscarriage is often not clear. Method: Retrospective analysis of all 1ST trimester ERPC at Al Rahba Hospital from June 2012 to July 2013 was done. Total of 164 patients underwent ERPC. All cases were reviewed for pre-operative USG ET and post ERPC histopathological examination. TVS was done to evaluate the maximum ET of the uterine cavity along the long axis of the uterus and features of retained products was noted. All cases without preoperative USG ET measurement were excluded from the study, therefore only 62 out of 164 cases were included in the study. The patients were divided into three groups: o Group A: have retained products within endometrial cavity. o Group B: endometrial thickness equal or more than 20 mm. o Group C: endometrial thickness equal or less than 19.9 mm. o Post ERPC product was sent for HPE and the results were compared. Transvaginal sonographic findings can be used as a deciding factor in the management of patients with 1st trimester miscarriage who need ERPC. Our proposed cutoff in clinically stable patients requiring ERPC is more than 20 mm.

Keywords: ERPC, histopathological examination, long axis of the uterus, USG ET

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Authors: Abdelrahman Elsehsah, Abdelazim Negm, Eid Ashour, Mohamed Elsahabi

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Water resources management is a critical field that encompasses the planning, development, conservation, and allocation of water resources to meet societal needs while ensuring environmental sustainability. This paper reviews the key concepts and challenges in water resources management, emphasizing the significance of a holistic approach that integrates social, economic, and environmental factors. Traditional water management practices, characterized by supply-oriented strategies and centralized control, are increasingly inadequate in addressing contemporary challenges such as water scarcity, climate change impacts, and ecosystem degradation. Emerging technologies, particularly machine learning and remote sensing, offer innovative solutions to enhance decision-making processes in water management. Machine learning algorithms facilitate accurate water demand forecasting, quality monitoring, and leak detection, while remote sensing technologies provide vital data for assessing water availability and quality. This review highlights the need for integrated water management strategies that leverage these technologies to promote sustainable practices and foster resilience in water systems. Future research should focus on improving data quality, accessibility, and the integration of diverse datasets to optimize the benefits of these technological advancements.

Keywords: water resources management, water scarcity, climate change, machine learning, remote sensing, water quality, water governance, sustainable practices, ecosystem management

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Authors: Ledi Neçaj

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Introduction: Cardio-respiratory rehabilitation is the set of coordinated interventions needed to provide the best physical, psychological, and social conditions so that patients with chronic or post-acute cardiopulmonary disease, with their efforts, maintain or resume optimal functioning in society through improved health behaviors. Purpose: To study the effectiveness of the application of Cardio-Respiratory Rehabilitation in the typology of patients with chronic or post-acute cardiomyopathy and chronic respiratory diseases in order to facilitate their therapeutic use and to improve the overall quality of life. Material and Method: This is a prospective study including patients with COPD and cardiac disease who were included in the rehabilitation program during the period January 2019 - November 2021. The study was conducted at the University Hospital Center "Mother Teresa" in Tirana, University Hospital "SHEFQET NDROQI", AMERICAN Hospital, HYGEA Hospital, and "Our Lady of Good Counsel, Tirana". An individual chart was used to collect sociodemographic, physical, clinical, and functional examinations for each patient. Results: The study included 253 patients, with a mean age of 62.1 (± 7.9) years, ranging from 48 to 82 years. (67.6%) of the patients were males, and (32.4%) female. Male patients predominated in all age groups, with a statistically significant difference with females (p<0.01). The most common cardiac pathologies are coronary artery bypass (24%), cerebral stroke (9%), myocardial infarction (17%), Stent placement (8%) (p<0.01). Correlation matrix of risk factors found a significant correlation of alcohol consumption with diabetes, smoking, dyslipidemia, sedentary life, obesity, AVC, and hypertension. Functional capacity estimated by change in metabolic equivalents (MET) improved by 46% from 4. ±2.2 to 7.2± .8 METs (p<0.01). Duration of exercise after rehabilitation was increased by 21% compared to baseline (p<0.01). The mean score of all three subscales of the questionnaire: symptoms (p=0.03), activity (p<0.01), and impact (p<0.01) after rehabilitation, was lower compared to pre-rehabilitation. Conclusions: The rehabilitation program has impacted on improving the quality of life, reducing symptoms, reducing the impact of negative factors on daily life, and reducing dyspnea during daily activities.

Keywords: cardio-respiratory rehabilitation, physical exercise, quality of life, diseases

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Authors: Maria Angela Bedini, Fabio Bronzini

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The risk of natural disasters affects all the countries of the world, whether it refers to seismic events or tsunamis or hydrogeological disasters. In most cases, the risk can be considered in its three components: hazard, exposure, vulnerability (and urban vulnerability). The aim of this paper is to evaluate how the Italian scientific community has related the contribution of these three components, superimposing the three different maps that summarize the fundamental structure of the risk. Based on the three components considered, the study applies the Regional Planning methodology on the three phases of the risk protection and mitigation process: the prevention phase, the emergency intervention phase, the post-disaster phase. The paper illustrates the Italian experience of the pre-during-post-earthquake intervention. Main results: The study deepens these aspects in the belief that “a historical center” and an “island” can present similar problems at the international level, both in the phase of prevention (earthquake, tsunamis, hydrogeological disasters), in emergency phase (protocols and procedures of intervention) and in the post-disaster phase. The conclusions of the research identify the need to plan in advance how to deal with the post-disaster phase and consider it a priority with respect to the simple reconstruction of destroyed buildings. In fact the main result of the post-disaster intervention must be the return and the social and economic support of the indigenous population, and not only the construction of new housing and equipment. In this sense, the results of the research show that the elderly inhabitants of a historic center can be compared to the indigenous population of an atoll of fishermen, as both constitute the most important resource: the human resource. Their return in conditions of security testifies, with their presence, the culture, customs, and values rooted in the history of a people.

Keywords: post-disaster interventions, risk of natural disasters in Italy and abroad, seismic events in Italy, social and economic protection and support for the native population of historical centers

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Authors: Chia-Ling Chang, Hao-Bo Chang

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Global climate change alters rainfall characteristics, while the variation of these characteristics further influences environmental conditions, such as hydrologic responses, landslide areas, and the amounts of diffuse pollution. The variations of environmental conditions may impact the stability of water resource systems. The objective of this study is to assess the present conditions of major water resource systems in Taiwan. The impact of climate change on each system is also discussed herein. Compared to the water resource systems in northern Taiwan, the ratio of the precipitation during the rainy season to that during the dry season has a larger increase in southern Taiwan. This variation of hydrologic condition impacts the stability of water resource systems and increases the risk of normal water supply. The findings in this work can be important references for water resource management.

Keywords: basin management, climate change, water resource system, water resource management

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Authors: Ghada A. Alfattni

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Analysing unbalanced datasets is one of the challenges that practitioners in machine learning field face. However, many researches have been carried out to determine the effectiveness of the use of the synthetic minority over-sampling technique (SMOTE) to address this issue. The aim of this study was therefore to compare the effectiveness of the SMOTE over different models on unbalanced datasets. Three classification models (Logistic Regression, Support Vector Machine and Nearest Neighbour) were tested with multiple datasets, then the same datasets were oversampled by using SMOTE and applied again to the three models to compare the differences in the performances. Results of experiments show that the highest number of nearest neighbours gives lower values of error rates. 

Keywords: imbalanced datasets, SMOTE, machine learning, logistic regression, support vector machine, nearest neighbour

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Authors: Ki Hyun Park, Hye Min Park, Jeong Ho Kim, Chan Jong Park, Koan Sik Joo

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In the modern days, the use of radioactive substances is on the rise in the areas like chemical weaponry, industrial usage, and power plants. Although there are various technologies available to detect and monitor radioactive substances in the air, the technologies to detect underwater radioactive substances are scarce. In this study, computer simulation of the underwater detection system measuring beta-ray, a radioactive substance, has been done through MCNP. CaF₂, YAP(Ce) and YAG(Ce) have been used in the computer simulation to detect beta-ray as scintillator. Also, the source used in the computer simulation is Sr-90 and Y-90, both of them emitting only pure beta-ray. The distance between the source and the detector was shifted from 1mm to 10mm by 1 mm in the computer simulation. The result indicated that Sr-90 was impossible to measure below 1 mm since its emission energy is low while Y-90 was able to be measured up to 10mm underwater. In addition, the detector designed with CaF₂ had the highest efficiency among 3 scintillators used in the computer simulation. Since it was possible to verify the detectable range and the detection efficiency according to modeling through MCNP simulation, it is expected that such result will reduce the time and cost in building the actual beta-ray detector and evaluating its performances, thereby contributing the research and development.

Keywords: Beta-ray, CaF₂, detector, MCNP simulation, scintillator

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Authors: Hongmei Chi

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The Blockchain has become a necessity for many different societal industries and ordinary lives including cryptocurrency technology, supply chain, health care, public safety, education, etc. Therefore, training our future blockchain developers to know blockchain programming vulnerability and I.T. students' cyber security is in high demand. In this work, we propose a framework including learning modules and hands-on labs to guide future I.T. professionals towards developing secure blockchain programming habits and mitigating source code vulnerabilities at the early stages of the software development lifecycle following the concept of Secure Software Development Life Cycle (SSDLC). In this research, our goal is to make blockchain programmers and I.T. students aware of the vulnerabilities of blockchains. In summary, we develop a framework that will (1) improve students' skills and awareness of blockchain source code vulnerabilities, detection tools, and mitigation techniques (2) integrate concepts of blockchain vulnerabilities for IT students, (3) improve future IT workers’ ability to master the concepts of blockchain attacks.

Keywords: software vulnerability detection, hands-on lab, static analysis tools, vulnerabilities, blockchain, active learning

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Authors: Nicholas Mavrogiannis, Francesca Crivellari, Zachary Gagnon

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Development of low-cost, rapid, sensitive and portable biosensing systems are important for the detection and prevention of disease in developing countries, biowarfare/antiterrorism applications, environmental monitoring, point-of-care diagnostic testing and for basic biological research. Currently, the most established commercially available and widespread assays for portable point of care detection and disease testing are paper-based dipstick and lateral flow test strips. These paper-based devices are often small, cheap and simple to operate. The last three decades in particular have seen an emergence in these assays in diagnostic settings for detection of pregnancy, HIV/AIDS, blood glucose, Influenza, urinary protein, cardiovascular disease, respiratory infections and blood chemistries. Such assays are widely available largely because they are inexpensive, lightweight, and portable, are simple to operate, and a few platforms are capable of multiplexed detection for a small number of sample targets. However, there is a critical need for sensitive, quantitative and multiplexed detection capabilities for point-of-care diagnostics and for the detection and prevention of disease in the developing world that cannot be satisfied by current state-of-the-art paper-based assays. For example, applications including the detection of cardiac and cancer biomarkers and biothreat applications require sensitive multiplexed detection of analytes in the nM and pM range, and cannot currently be satisfied with current inexpensive portable platforms due to their lack of sensitivity, quantitative capabilities and often unreliable performance. In this talk, inexpensive label-free biomolecular detection at liquid interfaces using a newly discovered electrokinetic phenomenon known as fluidic dielectrophoresis (fDEP) is demonstrated. The electrokinetic approach involves exploiting the electrical mismatches between two aqueous liquid streams forced to flow side-by-side in a microfluidic T-channel. In this system, one fluid stream is engineered to have a higher conductivity relative to its neighbor which has a higher permittivity. When a “low” frequency (< 1 MHz) alternating current (AC) electrical field is applied normal to this fluidic electrical interface the fluid stream with high conductivity displaces into the low conductive stream. Conversely, when a “high” frequency (20MHz) AC electric field is applied, the high permittivity stream deflects across the microfluidic channel. There is, however, a critical frequency sensitive to the electrical differences between each fluid phase – the fDEP crossover frequency – between these two events where no fluid deflection is observed, and the interface remains fixed when exposed to an external field. To perform biomolecular detection, two streams flow side-by-side in a microfluidic T-channel: one fluid stream with an analyte of choice and an adjacent stream with a specific receptor to the chosen target. The two fluid streams merge and the fDEP crossover frequency is measured at different axial positions down the resulting liquid

Keywords: biodetection, fluidic dielectrophoresis, interfacial polarization, liquid interface

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Authors: Sergio V Davalos, Alison L. Watkins

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User generated content (UGC) such as website post has data associated with it: time of the post, gender, location, type of device, and number of words. The text entered in user generated content (UGC) can provide a valuable dimension for analysis. In this research, each user post is treated as a collection of terms (words). In addition to the number of words per post, the frequency of each term is determined by post and by the sum of occurrences in all posts. This research focuses on one specific aspect of UGC: sentiment. Sentiment analysis (SA) was applied to the content (user posts) of two sets of political forums related to the US presidential elections for 2012 and 2016. Sentiment analysis results in deriving data from the text. This enables the subsequent application of data analytic methods. The SASA (SAIL/SAI Sentiment Analyzer) model was used for sentiment analysis. The application of SASA resulted with a sentiment score for each post. Based on the sentiment scores for the posts there are significant differences between the content and sentiment of the two sets for the 2012 and 2016 presidential election forums. In the 2012 forums, 38% of the forums started with positive sentiment and 16% with negative sentiment. In the 2016 forums, 29% started with positive sentiment and 15% with negative sentiment. There also were changes in sentiment over time. For both elections as the election got closer, the cumulative sentiment score became negative. The candidate who won each election was in the more posts than the losing candidates. In the case of Trump, there were more negative posts than Clinton’s highest number of posts which were positive. KNIME topic modeling was used to derive topics from the posts. There were also changes in topics and keyword emphasis over time. Initially, the political parties were the most referenced and as the election got closer the emphasis changed to the candidates. The performance of the SASA method proved to predict sentiment better than four other methods in Sentibench. The research resulted in deriving sentiment data from text. In combination with other data, the sentiment data provided insight and discovery about user sentiment in the US presidential elections for 2012 and 2016.

Keywords: sentiment analysis, text mining, user generated content, US presidential elections

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Authors: Hui-Chi Huang, Su-Ju Yang, Ching-Wei Lin, Jui-Yao Tsai, Liang-Yiang

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Background: Evidence exists that pneumonia is a frequently encountered complication after stroke which is associated with a higher rate of mortality and increased long-term disability Purpose: To determine the predictors associated with the risk of one-year disability in acute stroke. Methods: Data for this longitudinal follow-up study were extracted from a tertiary referral medical center’s stroke registry database in Northern Taipei. Eligible patients with acute stroke admitted to the hospital and completed a one-year follow up were recruited for analysis. Favorable outcome was defined as a modified Rankin Scale score ≤ 2. SAS version 9.2 was used for the multivariable regression analyses to examine the factors correlated with the one-year disability in stroke patients. Results: From January 2012 to December 2013, a total of 1373 (mean age: 70.49±15.4 years, 913(66.5%) males) consecutively administered acute stroke patients were recruited. Overall, the rate of one-year disability was 37.20%(404/1086) in those without post-stroke pneumonia. It increased to 82.93 %(238/287) in patients developed post-stroke pneumonia. Factors associated with increased risk of disability were age ≧ 75(OR= 4.845, p<.0001), female /gender (OR=1.568, p =.0062), previous stroke (OR= 1.868, p = <. 0001) ,dementia (OR= 2.872, p =.0047), ventilator use (OR= 4.653, p <. 0001),age ≧ 75 /pneumonia (OR=1.236, p <. 0001) , ICU admission (OR=3.314, p <.0001) , nasogastric tube insertion (OR= 4.28, p <.0001), speech therapy (OR= 1.79, p =.0142), urinary tract infection (OR= 1.865, p =.0018), estimated glomerular filtration rate (eGFR > 60 )(OR= 0.525, p= .0029), Admission NIHSS >11 (OR= 2.101, p = .0099), Length of hospitalization > 30(d) (OR= 5.182, p <.0001). Conclusion: Older age, severe neurological deficit, complications, rehabilitation intervention, length of hospitalization >30(d), and cognitive impairment were significantly associated with Post-stroke functional impairment, especially those with post-stroke pneumonia. These findings could open new avenues in the management of stroke patients.

Keywords: stroke, risk, pneumonia, disability

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Authors: Chongya Song, Kang Yen, Alexander Pons, Jin Liu

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In the field of machine learning, the ensemble has been employed as a common methodology to improve the performance upon multiple base classifiers. However, the true predictions are often canceled out by the false ones during consensus due to a phenomenon called “curse of correlation” which is represented as the strong interferences among the predictions produced by the base classifiers. In addition, the existing practices are still not able to effectively mitigate the problem of imbalanced classification. Based on the analysis on our experiment results, we conclude that the two problems are caused by some inherent deficiencies in the approach of consensus. Therefore, we create an enhanced ensemble algorithm which adopts a designed rank-based chain-mode consensus to overcome the two problems. In order to evaluate the proposed ensemble algorithm, we employ a well-known benchmark data set NSL-KDD (the improved version of dataset KDDCup99 produced by University of New Brunswick) to make comparisons between the proposed and 8 common ensemble algorithms. Particularly, each compared ensemble classifier uses the same 22 base classifiers, so that the differences in terms of the improvements toward the accuracy and reliability upon the base classifiers can be truly revealed. As a result, the proposed rank-based chain-mode consensus is proved to be a more effective ensemble solution than the traditional consensus approach, which outperforms the 8 ensemble algorithms by 20% on almost all compared metrices which include accuracy, precision, recall, F1-score and area under receiver operating characteristic curve.

Keywords: consensus, curse of correlation, imbalance classification, rank-based chain-mode ensemble

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Authors: Mahmoud Mohamed Emam, Yasser Fathy Hendawy Al-Mahdy

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Higher education institutions (HEIs) in Arab countries have witnessed large scope transformations as a result of embracing globalised practices. The introduction of program academic accreditation in HEIs in the Arab context has been regarded as a change enterprise that has proponents and opponents. In essence, introducing new systems or practices trigger changes that may shatter employees at a given organization. Therefore, it is argued that the interaction between organizational, contextual, and individual-related variables are likely to determine how the organization succeeds in facing resistance to change. This study investigated a mediated-effects model of organizational support and citizenship behavior. The model proposes organizational support as an antecedent of citizenship behavior and commitment to change as a mediator in the organizational support–citizenship behavior relationship. Survey data were collected and analyzed from university faculty (n=221) using structural equation modeling. Findings showed that organizational support significantly contributes to increasedcitizenshipbehaviour and the commitment of university faculty to program accreditation as a change enterprise, which has a significant and direct impact on their citizenship behaviour. We conclude that university-level organizational support shapes faculty’s commitment to change both directly and indirectly. The findings have significant practical implications for HEIs in Arab countries when they introduce new practices that aim at improving institutional effectiveness.

Keywords: organizational support, accreditation, commitment, citizenship behaviour

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Authors: Mohamed Fathy Heweage, Xiao Wen, Ayman Mokhtar, Ahmed Eldamarawy

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In this paper, we are interested in modeling, simulation, and measurement of the laser spot position with a quadrant detector. We enhance detection and tracking of semi-laser weapon decoding system based on microcontroller. The system receives the reflected pulse through quadrant detector and processes the laser pulses through a processing circuit, a microcontroller decoding laser pulse reflected by the target. The seeker accuracy will be enhanced by the decoding system, the laser detection time based on the receiving pulses number is reduced, a gate is used to limit the laser pulse width. The model is implemented based on Pulse Repetition Frequency (PRF) technique with two microcontroller units (MCU). MCU1 generates laser pulses with different codes. MCU2 decodes the laser code and locks the system at the specific code. The codes EW selected based on the two selector switches. The system is implemented and tested in Proteus ISIS software. The implementation of the full position determination circuit with the detector is produced. General system for the spot position determination was performed with the laser PRF for incident radiation and the mechanical system for adjusting system at different angles. The system test results show that the system can detect the laser code with only three received pulses based on the narrow gate signal, and good agreement between simulation and measured system performance is obtained.

Keywords: four quadrant detector, pulse code detection, laser guided weapons, pulse repetition frequency (PRF), Atmega 32 microcontrollers

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Authors: Sonali Mohite

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Severe changes to Organizational Sustainability (OS) have been brought about by the COVID-19 pandemic. This situation forces organizations to tackle the competencies required to augment Employee Resilience (ER) and make profitable growth. This study explores how employee resilience contributes to both individual and organizational success in the wake of the COVID-19 pandemic. We suggest that employees who possess strong coping mechanisms and adaptability are better equipped to handle ongoing disruptions, resulting in improved individual performance metrics like productivity, engagement, and innovative thinking. Hence, exploring the efficiency of ER in improving EP and OS in post-pandemic (PP) is the aim of this research. By utilizing convenience sampling techniques, a total of 422 employees have been collected from numerous organizations. After that, the study’s hypothesis is analysed by using Structural Equation Modelling (SEM). As per the study’s findings, the ER factors of “Job Satisfaction (JS)”, “Self-Efficacy (SE)”, “Supervisors’ Support (SS)”, and “Facilitating Conditions (FC)” have positive and significant associations with organizational efficiency. Furthermore, the study’s findings also exhibited that there is the most important relation between SE and EOP.

Keywords: employee resilience, employee performance, organizational performance, sustainability, post-pandemic

Procedia PDF Downloads 31