Abstract: Identification of plant diseases has been performed using machine learning and deep learning models on the datasets containing images of healthy and diseased plant leaves. The current study carries out an evaluation of some of the deep learning models based on convolutional neural network architectures for identification of plant diseases. For this purpose, the publicly available New Plant Diseases Dataset, an augmented version of PlantVillage dataset, available on Kaggle platform, containing 87,900 images has been used. The dataset contained images of 26 diseases of 14 different plants and images of 12 healthy plants. The CNN models selected for the study presented in this paper are AlexNet, ZFNet, VGGNet (four models), GoogLeNet, and ResNet (three models). The selected models are trained using PyTorch, an open-source machine learning library, on Google Colaboratory. A comparative study has been carried out to analyze the high degree of accuracy achieved using these models. The highest test accuracy and F1-score of 99.59% and 0.996, respectively, were achieved by using GoogLeNet with Mini-batch momentum based gradient descent learning algorithm.
Abstract: Developing new medicine and health solutions and improving patient health currently rely on the successful execution of clinical trials, which generate relevant safety and efficacy data. For their success, recruitment and retention of participants are some of the most challenging aspects of protocol adherence. Main barriers include: i) lack of awareness of clinical trials; ii) long distance from the clinical site; iii) the burden on participants, including the duration and number of clinical visits, and iv) high dropout rate. Most of these aspects could be addressed with a new paradigm, namely the Remote Decentralized Clinical Trials (RDCTs). Furthermore, the COVID-19 pandemic has highlighted additional advantages and challenges for RDCTs in practice, allowing participants to join trials from home and not depending on site visits, etc. Nevertheless, RDCTs should follow the process and the quality assurance of conventional clinical trials, which involve several processes. For each part of the trial, the Building Blocks, existing software and technologies were assessed through a systematic search. The technology needed to perform RDCTs is widely available and validated but is yet segmented and developed in silos, as different software solutions address different parts of the trial and at various levels. The current paper is analyzing the availability of technology to perform RDCTs, identifying gaps and providing an overview of Basic Building Blocks and functionalities that need to be covered to support the described processes.
Abstract: Continuous improvement activities are becoming a key organizational success factor; those improvement activities include but are not limited to kaizen, six sigma, lean production, and continuous improvement projects. Kaizen is a Japanese philosophy of continuous improvement by making small incremental changes to improve an organization’s performance, reduce costs, reduce delay time, reduce waste in production, etc. This research aims at proposing a measuring system for kaizen activities from a sustainable balanced scorecard perspective. A survey was developed and disseminated among kaizen experts in both Egypt and Japan with the purpose of allocating key performance indicators for both kaizen process (critical success factors) and result (kaizen benefits) into the five sustainable balanced scorecard perspectives. This research contributes to the extant literature by presenting a kaizen measurement of both kaizen process and results that will illuminate the benefits of using kaizen. Also, the presented measurement can help in the sustainability of kaizen implementation across various sectors and industries. Thus, grasping the full benefits of kaizen implementation will contribute to the spread of kaizen understanding and practice. Also, this research provides insights on the social and cultural differences that would influence the kaizen success. Determining the combination of the proper kaizen measures could be used by any industry, whether service or manufacturing for better kaizen activities measurement. The comparison between Japanese implementation of kaizen, as the pioneers of continuous improvement, and Egyptian implementation will help recommending better practices of kaizen in Egypt and contributing to the 2030 sustainable development goals. The study results reveal that there is no significant difference in allocating kaizen benefits between Egypt and Japan. However, with regard to the critical success factors some differences appeared reflecting the social differences and understanding between both countries, a single integrated measurement was reached between the Egyptian and Japanese allocation highlighting the Japanese experts’ opinion as the ultimate criterion for selection.
Abstract: Additive Friction Stir Manufacturing, or AFSM, is a new industrial process that follows the emergence of friction-based processes. The AFSM process is a solid-state additive process using the energy produced by the friction at the interface between a rotating non-consumable tool and a substrate. Friction depends on various parameters like axial force, rotation speed or friction coefficient. The feeder material is a metallic rod that flows through a hole in the tool. There is still a lack in understanding of the physical phenomena taking place during the process. This research aims at a better AFSM process understanding and implementation, thanks to numerical simulation and experimental validation performed on a prototype effector. Such an approach is considered a promising way for studying the influence of the process parameters and to finally identify a process window that seems relevant. The deposition of material through the AFSM process takes place in several phases. In chronological order these phases are the docking phase, the dwell time phase, the deposition phase, and the removal phase. The present work focuses on the dwell time phase that enables the temperature rise of the system due to pure friction. An analytic modeling of heat generation based on friction considers as main parameters the rotational speed and the contact pressure. Another parameter considered influential is the friction coefficient assumed to be variable, due to the self-lubrication of the system with the rise in temperature or the materials in contact roughness smoothing over time. This study proposes through a numerical modeling followed by an experimental validation to question the influence of the various input parameters on the dwell time phase. Rotation speed, temperature, spindle torque and axial force are the main monitored parameters during experimentations and serve as reference data for the calibration of the numerical model. This research shows that the geometry of the tool as well as fluctuations of the input parameters like axial force and rotational speed are very influential on the temperature reached and/or the time required to reach the targeted temperature. The main outcome is the prediction of a process window which is a key result for a more efficient process implementation.
Abstract: The skin-gut axis defines the relationship between the intestinal microbiota and the development of pathological skin diseases. Low diversity within the gut can predispose to the development of allergic skin conditions, and a greater diversity of the gastrointestinal microflora has been associated with a reduction of skin flares in people with atopic dermatitis. Manipulation of the gut microflora has been used as a treatment option for several conditions in people, but there is limited data available on the use of fecal transplantation as a preventative measure in either people or dogs. Six, 4-month-old pups from a litter of 10 were presented for diarrhea and/or signs of skin disease (chronic scratching, otitis externa). Of these pups, two were given probiotics with a resultant resolution of diarrhea. The other four pups were given fecal transplantation, either as a sole treatment or in combination with other treatments. Follow-up on the litter of 10 pups was performed at 18 months of age. At this stage, three out of the four pups that had received fecal transplantation had resolved all clinical signs and had no recurrence of either skin or gastrointestinal symptoms, the other pup had one episode of Malassezia otitis. Of the remaining six pups from the litter, all had developed at least one episode of Malassezia otitis externa within the period of five to 18 months of age. Two pups had developed two Malassezia otitis infections, and one had developed three Malassezia otitis infections during this period. Favrot’s criteria for the diagnosis of canine atopic dermatitis include chronic or recurrent Malassezia infections by the age of three years. Early results from this litter predict a reduction in the development of canine atopic disease in dogs given fecal microbial transplantation. Follow-up studies at three years of age and within a larger population of dogs can enhance understanding of the impact of early fecal transplantation in the prevention of canine atopic dermatitis.
Abstract: This paper represents the conception that complex problems do not necessary need similar complex solutions in order to cope with the complexity. Furthermore, a simple solution based on established methods can provide a sufficient way dealing with the complexity. To verify this conception, the presented paper focuses on the field of change management as a part of new product development process in automotive sector. In the field of complexity management, dealing with increasing complexity is essential, while, only non-flexible rigid processes that are not designed to handle complexity are available. The basic methodology of this paper can be divided in four main sections: 1) analyzing the complexity of the change management, 2) literature review in order to identify potential solutions and methods, 3) capturing and implementing expertise of experts from change management filed of an automobile manufacturing company and 4) systematical comparison of the identified methods from literature and connecting these with defined requirements of the complexity of the change management in order to develop a solution. As a practical outcome, this paper provides a method to capture the complexity of engineering changes (EC) and includes it within the EC evaluation process, following case-related process guidance to cope with the complexity. Furthermore, this approach supports the conception that dealing with complexity is possible while utilizing rather simple and established methods by combining them in to a powerful tool.
Abstract: China’s declared transformation towards a ‘new electricity system dominated by renewable energy’ requires a cleaner electricity consumption mix with high shares of renewable energy sourced-electricity (RES-E). Unfortunately, integration of RES-E into Chinese electricity markets remains a problem pending more robust legal support, evidenced by the curtailment of wind and solar power due to integration constraints. The upcoming Energy Law of the PRC (Energy Law) is expected to provide such long-awaiting support and coordinate the existing diverse sector-specific laws to deal with the weak implementation that dampening the delivery of their desired regulatory effects. However, in the shadow of the COVID-19 crisis, it remains uncertain how this new Energy Law brings synergies to RES-E integration, mindful of the significant impacts of the pandemic. Through the theoretical lens of the interplay between China’s electricity market reform and legislative development, this paper investigates whether there is a paradigm shift in Energy Law regarding renewable energy integration compared with the existing sector-specific energy laws. It examines the 2020 Draft for Comments on the Energy Law and analyses its relationship with sector-specific energy laws focusing on RES-E integration. The comparison is drawn upon five critical aspects of the RES-E integration issue, including the status of renewables, marketisation, incentive schemes, consumption mechanisms, access to power grids and dispatching. The analysis shows that it is reasonable to expect a more open and well-organised electricity market, enabling the absorption of high shares of RES-E. The present paper concludes that a period of prosperous development of RES-E in the post-COVID-19 era can be anticipated with the legal support by the upcoming Energy Law. It contributes to understanding the signals China is sending regarding the transition towards a cleaner energy future.
Abstract: Run-of-river (RoR) hydropower projects represent a viable, clean, and cost-effective alternative to dam-based plants and provide decentralized power production. However, RoR schemes’ cost-effectiveness depends on the proper selection of site and design flow, which is a challenging task because it requires multivariate analysis. In this respect, this study presents the development of an investment decision support tool for assessing the optimal size of an RoR scheme considering the technical, environmental, and cost constraints. The net present value (NPV) from a project perspective is used as an objective function for supporting the investment decision. The tool has been tested by applying it to an actual RoR project recently proposed in Colombia. The obtained results show that the optimum point in financial terms does not match the flow that maximizes energy generation from exploiting the river's available flow. For the case study, the flow that maximizes energy corresponds to a value of 5.1 m3/s. In comparison, an amount of 2.1 m3/s maximizes the investors NPV. Finally, a sensitivity analysis is performed to determine the NPV as a function of the debt rate changes and the electricity prices and the CapEx. Even for the worst-case scenario, the optimal size represents a positive business case with an NPV of 2.2 USD million and an internal rate of return (IRR) 1.5 times higher than the discount rate.
Abstract: Obesity is a disease with an ever-increasing prevalence throughout the world. The metabolic network associated with obesity is very complicated. In metabolic syndrome (MetS), it becomes even more difficult to understand. Within this context, hormones, cytokines, and many others participate in this complex matrix. The collaboration among all of these parameters is a matter of great wonder. Cortisol, as a stress hormone, is closely associated with obesity. Thyroid hormones are involved in the regulation of energy as well as glucose metabolism with all of its associates. Fetuin A has been known for years; however, the involvement of this parameter in obesity discussions is rather new. Recently, it has been defined as one of the new generation markers of obesity. In this study, the aim was to introduce complex interactions among all to be able to make clear comparisons, at least for a part of this complicated matter. Morbid obese (MO) children participated in the study. Two groups with 46 MO children and 43 with MetS were constituted. All children included in the study were above 99th age- and sex-adjusted body mass index (BMI) percentiles according to World Health Organization criteria. Forty-three morbid obese children in the second group also had MetS components. Informed consent forms were filled by the parents of the participants. The institutional ethics committee has given approval for the study protocol. Data as well as the findings of the study were evaluated from a statistical point of view. Two groups were matched for their age and gender compositions. Significantly higher body mass index (BMI), waist circumference, thyrotropin, and insulin values were observed in the MetS group. Triiodothyronine concentrations did not differ between the groups. Elevated levels for thyroxin, cortisol, and fetuin-A were detected in the MetS group compared to the first group (p > 0.05). In MO MetS- group, cortisol was correlated with thyroxin and fetuin-A (p < 0.05). In the MO MetS+ group, none of these correlations were present. Instead, a correlation between cortisol and thyrotropin was found (p < 0.05). In conclusion, findings have shown that cortisol was the key player in severely obese children. The association of this hormone with the participants of thyroid hormone metabolism was quite important. The lack of association with fetuin A in the morbid obese MetS+ group has suggested the possible interference of MetS components in the behavior of this new generation obesity marker. The most remarkable finding of the study was the unique correlation between cortisol and thyrotropin in the morbid obese MetS+ group, suggesting that thyrotropin may serve as a target along with cortisol in the morbid obese MetS+ group. This association may deserve specific attention during the development of remedies against MetS in the pediatric population.
Abstract: Childhood obesity is an important clinical problem, because it may lead to chronic diseases during the adulthood period of the individual. Obesity is a metabolic disease associated with low-grade inflammation. The liver occurs at the center of metabolic pathways. Adropin, fibroblast growth factor-21 (FGF-21) and fetuin A are hepatokines. Due to the immense participation of the liver in glucose metabolism, these liver derived factors may be associated with insulin resistance (IR), which is a phenomenon discussed within the scope of obesity problems. The aim of this study is to determine the concentrations of adropin, FGF-21 and fetuin A in childhood obesity, to point out possible differences between the obesity groups and to investigate possible associations among these three hepatokines in obese and morbid obese children. A total of 132 children were included in the study. Two obese groups were constituted. The groups were matched in terms of mean±SD values of ages. Body mass index values of the obese and morbid obese groups were 25.0±3.5 kg/m2 and 29.8±5.7 kg/m2, respectively. Anthropometric measurements including waist circumference, hip circumference, head circumference, and neck circumference were recorded. Informed consent forms were taken from the parents of the participants and the Ethics Committee of the institution approved the study protocol. Blood samples were obtained after an overnight fasting. Routine biochemical tests including glucose- and lipid-related parameters were performed. Concentrations of the hepatokines (adropin, FGF-21, fetuin A) were determined by enzyme-linked immunosorbent assay. Insulin resistance indices such as homeostasis model assessment for IR (HOMA-IR), alanine transaminase-to aspartate transaminase ratio (ALT/AST), diagnostic obesity notation model assessment laboratory index, diagnostic obesity notation model assessment metabolic syndrome index as well as obesity indices such as diagnostic obesity notation model assessment-II index, and fat mass index were calculated using the previously derived formulas. Statistical evaluation of the study data as well as findings of the study were performed by SPSS for Windows. Statistical difference was accepted significant when p < 0.05. Statistically significant differences were found for insulin, triglyceride, high density lipoprotein cholesterol levels of the groups. A significant increase was observed for FGF-21 concentrations in the morbid obese group. Higher adropin and fetuin A concentrations were observed in the same group in comparison with the values detected in the obese group (p > 0.05). There was no statistically significant difference between the ALT/AST values of the groups. In all of the remaining IR and obesity indices, significantly increased values were calculated for morbid obese children. Significant correlations were detected between HOMA-IR and each of the hepatokines. The highest one was the association with fetuin A (r = 0.373, p = 0.001). In conclusion, increased levels observed in adropin, FGF-21 and fetuin A have shown that these hepatokines possess increasing potential going from the obese to morbid obese state. Out of the correlations found with IR index, the most affected hepatokine was fetuin A, the parameter possibly used as the indicator of the advanced obesity stage.
Abstract: As notifications become more common through mobile devices, it is important to understand the impact of wearable devices for improved user experience of man-machine interfaces. This study examined the use of a wearable device for a real-time system using a computer simulated petrochemical system. The key research question was to determine how using information provided by the wearable device can improve human performance through measures of situational awareness and decision making. Results indicate that there was a reduction in response time when using the watch and there was no difference in situational awareness. Perception of using the watch was positive, with 83% of users finding value in using the watch and receiving haptic feedback.
Abstract: Neodymium-iron-boron (NdFeB) magnets classified as high-power magnets are widely used in various applications such as automotive, electrical and medical devices. Because significant amounts of rare earth metals will be subjected to shortages in the future, therefore domestic NdFeB magnet waste recycling should therefore be developed in order to reduce social and environmental impacts towards a circular economy. Each type of wastes has different characteristics and compositions. As a result, these directly affect recycling efficiency as well as types and purity of the recyclable products. This research, therefore, focused on the recycling of manufacturing NdFeB magnet waste obtained from the sintering stage of magnet production and the waste contained 23.6% Nd, 60.3% Fe and 0.261% B in order to recover high purity neodymium oxide (Nd2O3) using hybrid metallurgical process via oxidative roasting and selective leaching techniques. The sintered NdFeB waste was first ground to under 70 mesh prior to oxidative roasting at 550–800 oC to enable selective leaching of neodymium in the subsequent leaching step using H2SO4 at 2.5 M over 24 h. The leachate was then subjected to drying and roasting at 700–800 oC prior to precipitation by oxalic acid and calcination to obtain Nd2O3 as the recycling product. According to XRD analyses, it was found that increasing oxidative roasting temperature led to an increasing amount of hematite (Fe2O3) as the main composition with a smaller amount of magnetite (Fe3O4) found. Peaks of Nd2O3 were also observed in a lesser amount. Furthermore, neodymium iron oxide (NdFeO3) was present and its XRD peaks were pronounced at higher oxidative roasting temperatures. When proceeded to acid leaching and drying, iron sulfate and neodymium sulfate were mainly obtained. After the roasting step prior to water leaching, iron sulfate was converted to form Fe2O3 as the main compound, while neodymium sulfate remained in the ingredient. However, a small amount of Fe3O4 was still detected by XRD. The higher roasting temperature at 800 oC resulted in a greater Fe2O3 to Nd2(SO4)3 ratio, indicating a more effective roasting temperature. Iron oxides were subsequently water leached and filtered out while the solution contained mainly neodymium sulfate. Therefore, low oxidative roasting temperature not exceeding 600 oC followed by acid leaching and roasting at 800 oC gave the optimum condition for further steps of precipitation and calcination to finally achieve Nd2O3.
Abstract: Nepal practiced a centralized unitary governing system for long and has gone through the federal system after the promulgation of the new constitution on 20 September 2015. There is a big paradigm shift in terms of governance after it. Now, there are three levels of governments, one federal government in the center, seven provincial governments and 753 local governments. Federalism refers to a political governing system with multiple tiers of government working together with coordination. It is preferred for self and shared rule. Though it has opened the door for rights of the people, political stability, state restructuring, and sustainable peace and development, there are many prospects and challenges for its proper implementation. This research analyzes the discourses of federalism implementation in Nepal with special reference to one of seven provinces, Gandaki. Federalism is a new phenomenon in Nepali politics and informed debates on it are required for its right evolution. This research will add value in this regard. Moreover, tracking its evolution and the exploration of the attitudes and behaviors of key actors and stakeholders in a new experiment of a new governing system is also important. The administrative and political system of Gandaki province in terms of service delivery and development will critically be examined. Besides demonstrating the performances of the provincial government and assembly, it will analyze the inter-governmental relation of Gandaki with the other two tiers of government. For this research, people from provincial and local governments (elected representatives and government employees), provincial assembly members, academicians, civil society leaders and journalists are being interviewed. The interview findings will be analyzed by supplementing with published documents. Just going into the federal structure is not the solution. As in the case of other provincial governments, Gandaki also had to start from scratch. It gradually took a shape of government and has been functioning sluggishly. The provincial government has many challenges ahead, which has badly hindered its plans and actions. Additionally, fundamental laws, infrastructures and human resources are found to be insufficient at the sub-national level. Lack of clarity in the jurisdiction is another main challenge. The Nepali Constitution assumes cooperation, coexistence and coordination as the fundamental principles of federalism which, unfortunately, appear to be lacking among the three tiers of government despite their efforts. Though the devolution of power to sub-national governments is essential for the successful implementation of federalism, it has apparently been delayed due to the centralized mentality of bureaucracy as well as a political leader. This research will highlight the reasons for the delay in the implementation of federalism. There might be multiple underlying reasons for the slow pace of implementation of federalism and identifying them is very tough. Moreover, the federal spirit is found to be absent in the main players of today's political system, which is a big irony. So, there are some doubts about whether the federal system in Nepal is just a keepsake or a substantive achievement.
Abstract: Wheelchair users spend long hours in a sitting position, and selecting the right cushion is highly critical in preventing pressure ulcers in that demographic. Pressure Mapping Systems (PMS) are typically used in clinical settings by therapists to identify the sitting profile and pressure points in the sitting area to select the cushion that fits the best for the users. A PMS is a flexible mat composed of arrays of distributed networks of pressure sensors. The output of the PMS systems is a color-coded image that shows the intensity of the pressure concentration. Therapists use the PMS images to compare different cushions fit for each user. This process is highly subjective and requires good visual memory for the best outcome. This paper aims to develop an image processing technique to analyze the images of PMS and provide an objective measure to assess the cushions based on their pressure distribution mappings. In this paper, we first reviewed the skeletal anatomy of the human sitting area and its relation to the PMS image. This knowledge is then used to identify the important features that must be considered in image processing. We then developed an algorithm based on those features to analyze the images and rank them according to their fit to the user's needs.
Abstract: The present study proposes a usability test method, Atmosphere, to assess the fitness of components and interaction patterns of design systems. The method covers the user’s perception of the components of the system, the efficiency of the logic of the interaction patterns, perceived ease of use as well as the user’s understanding of the intended outcome of interactions. These aspects are assessed by combining measures of first impression, visual affordance and expectancy. The method was applied to a design system developed for the design of an electronic health record system. The study was conducted involving 15 healthcare personnel. It could be concluded that the Atmosphere method provides tangible data that enable human-computer interaction practitioners to analyze and categorize components and patterns based on perceived usability, success rate of identifying interactive components and success rate of understanding components and interaction patterns intended outcome.
Abstract: In the current context, the engineering program educators need to think about how to develop the concepts and complex engineering problem-solving skills through various complex engineering activities by the undergraduate engineering students in various engineering courses. But most of them are facing challenges to assess and evaluate these skills of their students. In this study, detailed assessment and evaluation methods for the undergraduate Electrical and Electronic Engineering (EEE) program are stated using the Outcome-Based Education (OBE) approach. For this purpose, a final year course titled control systems has been selected. The assessment and evaluation approach, course contents, course objectives, course outcomes (COs), and their mapping to the program outcomes (POs) with complex engineering problems and activities via the knowledge profiles, performance indicators, rubrics of assessment, CO and PO attainment data, and other statistics, are reported for a student-cohort of control systems course registered by the students of BSc in EEE program in Spring 2021 Semester at the EEE Department of Southeast University (SEU). It is found that the target benchmark was achieved by the students of that course. Several recommendations for the continuous quality improvement (CQI) process are also provided.
Abstract: There are several methods for calculating the bearing capacity factors of foundations and retaining walls. In this paper, the bearing capacity factor Nγ (shape factor) for different types of foundation have been investigated. The formula for bearing capacity on c–φ–γ soil can still be expressed by Terzaghi’s equation except that the bearing capacity factor Nγ depends on the surcharge ratio, and friction angle φ. It is apparent that the value of Nγ increases irregularly with the friction angle of the subsoil, which leads to an excessive increment in Nγ of foundations with larger width. Also, the bearing capacity factor Nγ will significantly decrease with an increase in foundation`s width. It also should be highlighted that the effect of shape and dimension will be less noticeable with a decrease in the relative density of the soil. Hence, the bearing capacity factor Nγ relatively depends on foundation`s width, surcharge and roughness ratio. This paper presents the results of various studies conducted on the bearing capacity factor Nγ of: different types of shallow foundation and foundations with irregular geometry (ring footing, triangular footing, shell foundations and etc.) Further studies on the effect of bearing capacity factor Nγ on mat foundations and the characteristics of this factor with or without consideration for the presence of friction between soil and foundation are recommended.
Abstract: t-SNE is an embedding method that the data science community has widely used. It helps two main tasks: to display results by coloring items according to the item class or feature value; and for forensic, giving a first overview of the dataset distribution. Two interesting characteristics of t-SNE are the structure preservation property and the answer to the crowding problem, where all neighbors in high dimensional space cannot be represented correctly in low dimensional space. t-SNE preserves the local neighborhood, and similar items are nicely spaced by adjusting to the local density. These two characteristics produce a meaningful representation, where the cluster area is proportional to its size in number, and relationships between clusters are materialized by closeness on the embedding. This algorithm is non-parametric. The transformation from a high to low dimensional space is described but not learned. Two initializations of the algorithm would lead to two different embedding. In a forensic approach, analysts would like to compare two or more datasets using their embedding. A naive approach would be to embed all datasets together. However, this process is costly as the complexity of t-SNE is quadratic, and would be infeasible for too many datasets. Another approach would be to learn a parametric model over an embedding built with a subset of data. While this approach is highly scalable, points could be mapped at the same exact position, making them indistinguishable. This type of model would be unable to adapt to new outliers nor concept drift. This paper presents a methodology to reuse an embedding to create a new one, where cluster positions are preserved. The optimization process minimizes two costs, one relative to the embedding shape and the second relative to the support embedding’ match. The embedding with the support process can be repeated more than once, with the newly obtained embedding. The successive embedding can be used to study the impact of one variable over the dataset distribution or monitor changes over time. This method has the same complexity as t-SNE per embedding, and memory requirements are only doubled. For a dataset of n elements sorted and split into k subsets, the total embedding complexity would be reduced from O(n2) to O(n2/k), and the memory requirement from n2 to 2(n/k)2 which enables computation on recent laptops. The method showed promising results on a real-world dataset, allowing to observe the birth, evolution and death of clusters. The proposed approach facilitates identifying significant trends and changes, which empowers the monitoring high dimensional datasets’ dynamics.
Abstract: Atmospheric carbon dioxide (CO2) has dominated the discussion around the causes of climate change. This is a reflection of a 100-year time horizon for all greenhouse gases that became a norm. The 100-year time horizon is much too long – and yet, almost all mitigation efforts, including those set in the near-term frame of within 30 years, are still geared toward it. In this paper, we show that for a 30-year time horizon, methane (CH4) is the greenhouse gas whose radiative forcing exceeds that of CO2. In our analysis, we use the radiative forcing of greenhouse gases in the atmosphere, because they directly affect the rise in temperature on Earth. We found that in 2019, the radiative forcing (RF) of methane was ~2.5 W/m2 and that of carbon dioxide was ~2.1 W/m2. Under a business-as-usual (BAU) scenario until 2050, such forcing would be ~2.8 W/m2 and ~3.1 W/m2 respectively. There is a substantial spread in the data for anthropogenic and natural methane (CH4) emissions, along with natural gas, (which is primarily CH4), leakages from industrial production to consumption. For this reason, we estimate the minimum and maximum effects of a reduction of these leakages, and assume an effective immediate reduction by 80%. Such action may serve to reduce the annual radiative forcing of all CH4 emissions by ~15% to ~30%. This translates into a reduction of RF by 2050 from ~2.8 W/m2 to ~2.5 W/m2 in the case of the minimum effect that can be expected, and to ~2.15 W/m2 in the case of the maximum effort to reduce methane leakages. Under the BAU, we find that the RF of CO2 will increase from ~2.1 W/m2 now to ~3.1 W/m2 by 2050. We assume a linear reduction of 50% in anthropogenic emission over the course of the next 30 years, which would reduce the radiative forcing of CO2 from ~3.1 W/m2 to ~2.9 W/m2. In the case of "net zero," the other 50% of only anthropogenic CO2 emissions reduction would be limited to being either from sources of emissions or directly from the atmosphere. In this instance, the total reduction would be from ~3.1 W/m2 to ~2.7 W/m2, or ~0.4 W/m2. To achieve the same radiative forcing as in the scenario of maximum reduction of methane leakages of ~2.15 W/m2, an additional reduction of radiative forcing of CO2 would be approximately 2.7 -2.15 = 0.55 W/m2. In total, one would need to remove ~660 GT of CO2 from the atmosphere in order to match the maximum reduction of current methane leakages, and ~270 GT of CO2 from emitting sources, to reach "negative emissions". This amounts to over 900 GT of CO2.
Abstract: Currently, in the field of object posture estimation, there is research on estimating the position and angle of an object by storing a 3D model of the object to be estimated in advance in a computer and matching it with the model. However, in this research, we have succeeded in creating a module that is much simpler, smaller in scale, and faster in operation. Our 6D pose estimation model consists of two different networks – a classification network and a regression network. From a single RGB image, the trained model estimates the class of the object in the image, the coordinates of the object, and its rotation angle in 3D space. In addition, we compared the estimation accuracy of each camera position, i.e., the angle from which the object was captured. The highest accuracy was recorded when the camera position was 75°, the accuracy of the classification was about 87.3%, and that of regression was about 98.9%.