Miracle-dz/UniFAR-FTUs huggingface dataset:
Intelligent Data Analytics for Diagnosing Melanoma Skin Lesions via Deep Learning in IoT System

Melanoma is considered to be one of the most dangerous human malignancy, which is diagnosed visually or by dermoscopic analysis and histopathological examination. However, as these traditional methods are based on human experience and implemented manually, there have been great limitations for general usability in current clinical practice. In this paper, a novel hybrid machine learning approach is proposed to identify melanoma for skin healthcare in various cases. The proposed approach consists of classic machine learning methods, including convolutional neural networks (CNNs), EfficientNet, and XGBoost supervised machine learning. In the proposed approach, a deep learning model is trained directly from raw pixels and image labels for classification of skin lesions. Then, solely based on modeling of various features from patients, an XGBoost model is adopted to predict skin cancer. Following that, a diagnostic system which composed of the deep learning model and XGBoost model is developed to further improve the prediction efficiency and accuracy. Different from experience-based methods and solely image-based machine learning methods, the proposed approach is developed based on the theory of deep learning and feature engineering. Experiments show that the hybrid model outperforms single model like the traditional deep learning model or XGBoost model. Moreover, the data-driven-based characteristics can help the proposed approach develop a guideline for image analysis in other medical applications.
A 6-switch single-phase 5-level current-source inverter

The new 6-switch single-phase 5-level current-source inverter proposed in this paper was developed by properly simplifying the traditional 8-switch single-phase 5-level current-source inverter, and its operational principle was analyzed. Just like the problem of voltage-unbalance between different levels existing in voltage-source multilevel inverters, a similar problem of current-unbalance between different levels whether for the 8-switch single-phase 5-level current-source inverter, or for the new 6-switch 5-level current-source inverter also exists. A simple current-balance control method via DC current feedback is presented here to implement the current-balance control between different levels. And to reduce the output current harmonics, PWM control technique was used. Simulation and experimental results showed that this new 6-switch topology operates correctly and that the balance-inductor can almost equally distribute the total DC current.
Optimal sectionalizing switches allocation in distribution networks

Automatic devices that locate and automatically sectionalize faulted branches in MV power distribution systems restrict drastically the extent of disruption caused by long power interruptions when properly positioned. Some algorithms and automatic calculation procedures are proposed for determining the optimum number and location of automatic sectionalizing switching devices. Using these algorithms, the optimal solution can be found for both radial and meshed systems. The procedure is based on Bellmann's optimality principle which, combined with thinning techniques, yields the optimal solution in a few ms for real size problems.
Robust structured convex nonnegative matrix factorization for data representation

Nonnegative Matrix Factorization (NMF) is a popular technique for machine learning. Its power is that it can decompose a nonnegative matrix into two nonnegative factors whose product well approximates the nonnegative matrix. However, the nonnegative constraint of the data matrix limits its application. Additionally, the representations learned by NMF fail to respect the intrinsic geometric structure of the data. In this paper, we propose a novel unsupervised matrix factorization method, called Robust Structured Convex Nonnegative Matrix Factorization (RSCNMF). RSCNMF not only achieves meaningful factorizations of the mixed-sign data, but also learns a discriminative representation by leveraging local and global structures of the data. Moreover, it introduces the L2,1-norm loss function to deal with noise and outliers, and exploits the L2,1-norm feature regularizer to select discriminative features across all the samples. We develop an alternate iterative scheme to solve such a new model. The convergence of RSCNMF is proven theoretically and verified empirically. The experimental results on eight real-world data sets show that our RSCNMF algorithm matches or outperforms the state-of-the-art methods.
Psychiatric Comorbidities in 1p36 Deletion Syndrome and Their Treatment—A Case Report

1p36 deletion syndrome represents the most common terminal deletion observed in humans. Major clinical findings comprise developmental delay/intellectual disability, poor or absent expressive language, congenital central muscular hypotonia, brain anomalies, brachydactyly/camptodactyly, short feet, and characteristic facial features like straight eyebrows, deep-set eyes, and midface hypoplasia. So far, there is very limited knowledge about comorbid psychiatric disorders and their effective treatment in this special population. To fill this gap, this case report presents an initially four-year-old girl with 1p36.33–1p36.32 deletion, moderate intellectual disability, insomnia, oppositional-defiant disorder and attention deficit/hyperactivity disorder covering a period of time of about 1.5 years comprising initial psychological/psychiatric assessment, subsequent day clinic/outpatient treatment (amongst others including off-label use of melatonin and methylphenidate as well as parent-child interaction therapy) and follow-up assessment. Follow-up results indicated good efficacy of melatonin and methylphenidate medication without any adverse effects. Multidisciplinarity in diagnosis and treatment are mandatory to meet needs of patients with complex genetic disorders like 1p36 deletion syndrome. Off-label use of melatonin (for insomnia) and methylphenidate (for attention deficit/hyperactivity disorder) should be considered in young children with 1p36 deletion syndrome if behavioral interventions are not sufficient.
A Deep Learning Approach for DDoS Attack Detection Using Supervised Learning

This research presents a novel combined learning method for developing a novel DDoS model that is expandable and flexible property of deep learning. This method can advance the current practice and problems in DDoS detection. A combined method of deep learning with knowledge-graph classification is proposed for DDoS detection. Whereas deep learning algorithm is used to develop a classifier model, knowledge-graph system makes the model expandable and flexible. It is analytically verified with CICIDS2017 dataset of 53.127 entire occurrences, by using ten-fold cross validation. Experimental outcome indicates that 99.97% performance is registered after connection. Fascinatingly, significant knowledge ironic learning for DDoS detection varies as a basic behavior of DDoS detection and prevention methods. So, security professionals are suggested to mix DDoS detection in their internet and network.
Method for enhancing the process of software tool evaluation and selection: COTS, heritage, and custom software reviewed

For many organizations today, software evaluation and selection to meet the computing needs of that organization is critical. In recent years, the role of software has become essential to the integration of hardware systems of greater and greater complexity. As a result, the choice to purchase Commercial Off-The-Shelf software (COTS), adapt existing heritage or legacy Software, or to develop custom software can mean literally 'the success or failure of project. Yet frequently this decision is delegated to an individual who is not in alignment with the system or organization as a whole. Decisions are too often based solely on personal preference, familiarity and experience with one product with little regard for peripheral information. So how does a project effectively evaluate the software available? What are the factors and criteria that a decision maker should focus on and understand to make the most logical and strategic choice for software solutions? These fundamental challenges can be found throughout organizations of any business in nearly every industry. As software becomes increasingly complex with advancements in Information Technology, the need for accurate tools, which will help decision-makers faced with this decision, also increases. Additionally, as standardization becomes more mainstream, companies in all industries are looking to COTS systems to cut costs, meet demanding schedule needs, and increase robustness. These espoused capab software can give organizations a competitive advantage but only if implemented in the appropriate way, at the appropriate time and with the appropriate resources. However, if a software selection and implementation strategy is executed without proper understanding of the project as a system, then any software decision can lead to cost overruns, delays in the schedule and even project failure. In today's competitive market place, this risk is unacceptable. Through interviews with software decision-makers and managers, this paper has captured both successful empirical methods and lessons-learned from previous software selection processes. This paper concludes with a cost-effective and strategic approach via template for establishing accurate software selection criteria. With this template, decision-makers will be better prepared to make informed and comprehensive software decisions for specific systems, subsystems, and interfaces. Ultimately, by adopting this methodology, organizations will be able to achieve a Return-On-investment (ROI) through accurate and effective software selection processes.
Survey On Disclosing Information To Children With Genetic Conditions And Their Siblings In Japan

Many parents face the dilemma of when, how, and what to disclose to their children regarding their genetic conditions. The purpose of this study was to learn about the experiences of parents regarding disclosing information to their children with genetic conditions.Methods: A questionnaire was sent to 378 parents of children and adolescents with the following genetic conditions: 22q11.2 deletion syndrome, Beckwith-Wiedemann syndrome, Noonan syndrome, Russell-Silver syndrome, Kabuki syndrome, Williams syndrome, Prader-Willi syndrome, and Sotos syndrome. Findings were analyzed using descriptive statistics for multiple-choice questions and thematic analysis for open-ended questions.Results: Of the parents surveyed, 158 (41.8 %) responded to the questionnaires. The average age of children with genetic conditions was 12 years. Sixty-seven parents had disclosed relevant information to their children, whereas 91 had not. Sixty-eight out of 91 respondents were planning to disclose information in the future. Many respondents who had disclosed information did not regret this. They felt good talking about genetic conditions, and had talked about genetic conditions with the affected children following disclosure.Conclusion: This study contributed to our understanding of the attitudes of parents towards disclosing information to children with genetic conditions.
Excited State Proton Transfers in Hybrid Compound Based on Indoline Spiropyran of the Coumarin Type and Azomethinocoumarin in the Presence of Metal Ions

Spectral-luminescence properties of a hybrid compound containing a coumarin-type spiropyran and an azomethinocoumarin fragment in toluene-acetonitrile solution in the presence of Li+, Ca2+, Zn2+ and Mg2+ ions are reported. Two excited state proton transfers can occur in the hybrid compound—the transfer of a proton from the OH group of the 7-hydroxy coumarin tautomer to the N atom of the C=N bond of the azomethine fragment leading to green ESIPT fluorescence with a maximum at 540 nm and from the OH group of the 7-hydroxy coumarin tautomer to the carbonyl group of the pyrone chromophore, which leads to the formation of the 2-hydroxyl-tautomer T of coumarin with blue fluorescence with a maximum at 475 nm. Dependence of these excited state proton transfers on the metal nature and irradiation with an external UV source is discussed.
Heat Transfer and Pressure Drop Evaluation in Thin Wedge-Shaped Trailing Edge

In modern high loaded transonic turbines the aerodynamic losses of turbine airfoils are mostly covered by the thickness and the wedge angle of the blade trailing edges. Due to the aerodynamic requirements the thin trailing edges are the life limiting parts of the airfoils. The aerodynamic design requirements lead to trailing edge slots with extreme aspect ratio and huge fillet radius in relation to the internal slot geometry. In most cases, the conventional design tools are not validated for these geometries, therefore an improved knowledge of flow and heat transfer in this area is necessary. This paper discusses the measurements of endwall heat transfer coefficient and pressure drops in a wedge-shaped duct with two different turbulators arrangement. The first one is concerning five different long ribs (pedestals) configurations disposed streamwise while the other one is related to three configurations of staggered pin fins. Pedestals and pin fins stand vertically on the bottom surface of the wedge–shaped duct. This surface, named endwall, is coated with a thin layer of thermochromic liquid crystals and several transient tests are run to obtain detailed heat transfer coefficient distributions. Both for the pedestal and pin fins several parametric studies has been performed, varying both Reynolds number range (from 9000 to 27000) and turbulators configurations while outlet Mach number was set to 0.3 for all tests. Investigated pedestal configurations are different for turbulators spanwise pitch while pin fins geometry have different pin diameter values. In all cases the wedge duct angle is 10°. Results indicate that the smallest long ribs pitch and pin fin diameter are most recommended because of its significant endwall heat transfer and moderate pressure-drop penalty. Long ribs and pin-fins are aluminium made in order to evaluate an average value of the heat transfer coefficient on their side surface. So a valuation of global heat transfer coefficient in the internal trailing edge cooling duct become possible.Copyright © 2003 by ASME
Model for Optimal Sizing of a Wind Energy Conversion System for Green-Mobile Applications

The goal of the green-mobile technology is to attain negligible anthropogenic emissions of carbon dioxide (from the GSM base station generators), which constitute by far the largest part of the emissions of greenhouse gases, thereby making the environment much more friendly and safe. This study established the effect of altitude on the output power of wind turbine generators, and proposed a robust model to account for this effect is proposed for optimal sizing of a wind energy conversion system (WECS) for green-mobile applications. The proposed model implementation using a perfectly fitted polynomial expression derived from the manufacturer's power profile. Adjustment of the observed mean wind speed data to a 75 m lattice tower of a mobile station indicates that the proposed model can be effectively powered by mean wind speed for three different locations (Abuja, Benin City, and Katsina) in Nigeria. Analysis indicates that WECS, with its turbine is placed at an altitude of 100 m, loses approximately 1% of its output power.
The Optimization Design of Hospital Bed Structure for Independently Separating Left and or Right Leg Using Genetic Algorithms

This paper deals with the new method to design the optimum design for hospital bed, which can separate the left and or right leg for patient‘s leg splint. GAs as an optimization method was selected to search the minimum mass of bed structure whilst fulfilling some structure constraints such as stress, displacement and buckling. The GAs and FE code were developed to analyze the structure in MATLAB. This paper showed the success in searching the minimum mass whilst the stress and displacement were accepted. The optimum design for the hospital bed was 49.25 kg.
Three phase inverter development using common mode voltage pulse width modulation (PWM) method

This master report presents a simulation voltage source control system for three phase inverter focusing on reducing the common mode voltage using diode clamped circuit. The model was implemented using MATLAB-Simulink with the SimPowerSystems Block set and also M-file. The twelve Insulated Gate Bipolar Transistor (IGBTs) was use as a switching device. In the three phase inverter circuit, an Alternating Current (AC) output is synthesized from a Direct Current (DC) input by closing and opening the switches in correct sequence or switching system. The Pulse Width Modulation (PWM) is a program in M-file to control the ON/OFF switching scheme of the IGBTs. An output voltage of an inverter with diode clamped before load and after load will be monitored, discussed and compared to the basic three phase inverter. This inverter circuit operate in open loop system where the inverter output and the load in series connection. The effectiveness of the method will be compared with the basic three phase inverter simulation model in MATLABSimulink program.
Spatiotemporal Trends and Variations of the Rainfall Amount, Intensity, and Frequency in TRMM Multi-satellite Precipitation Analysis (TMPA) Data

The spatiotemporal mean rain rate (MR) can be characterized by the rain frequency (RF) and the conditional rain rate (CR). We computed these parameters for each season using the TMPA 3-hourly, 0.25° gridded data for the 1998–2017 period at a quasi-global scale, 50°N~50°S. For the global long-term average, MR, RF, and CR are 2.83 mm/d, 10.55%, and 25.05 mm/d, respectively. The seasonal time series of global mean RF and CR show significant decreasing and increasing trends, respectively, while MR depicts only a small but significant trend. The seasonal anomaly of RF decreased by 5.29% and CR increased 13.07 mm/d over the study period, while MR only slightly decreased by −0.029 mm/day. The spatiotemporal patterns in MR, RF, and CR suggest that although there is no prominent trend in the total precipitation amount, the frequency of rainfall events becomes smaller and the average intensity of a single event becomes stronger. Based on the co-variability of RF and CR, the paper optimally classifies the precipitation over land and ocean into four categories using K-means clustering. The terrestrial clusters are consistent with the dry and wet climatology, while categories over the ocean indicate high RF and medium CR in the Inter Tropical Convergence Zone (ITCZ) region; low RF with low CR in oceanic dry zones; and low RF and high CR in storm track areas. Empirical Orthogonal Function (EOF) analysis was then performed, and these results indicated that the major pattern of MR is characterized by an El Niño-Southern Oscillation (ENSO) signal while RF and CR variations are dominated by their trends.
3.1.1 System of Systems Engineering Model by Multistage Analytical Target Cascading

This paper presents a multilevel, multistage approach to system of systems engineering optimization where a system design/selection is linked with system allocation along the multistage decision making horizon. The approach is composed of two parts: pseudo‐hierarchical formulation (i.e., how to model the stages of multiple, separate decision making processes), and multistage coordination (i.e., how efficiently the proposed model would perform). The pseudo‐hierarchical formulation expands the analytical target cascading previously developed by the author into multiple stages to capture level‐by‐level and stage‐by‐stage system of systems design optimization. The multistage coordination is based on the alternating directions method that is incorporated as an efficient means to solve this inherently large‐scale optimization problem. An airline example validates the methodology where an airline plans to introduce multiple new aircraft to capture dynamically changing future demand of the customers. The proposed methodology is validated against the all‐in‐one approach and the sequential approach.
Simulation of brassiere-wearing figures

This article proposes a simulation method that combines a three-dimensional shape model of a human body with the genetic algorithm (GA) for estimating shape change of the breasts by wearing a brassiere. The model can describe trunk shape of any female with 750 control points for fitting the surface to many 3D points on the trunk surface. Because the model structure is common among women, their body shapes can be statistically analysed by using the control points. First, we related naked 230 breasts of 115 Japanese women with those wearing a full-cup brassiere through the multi-regression analysis. In this process, we searched the best regression formulas among a plethora of combinations of terms, or coordinates of the 49 control points on the naked models through the GA. Second, the regression formulas obtained above were applied to another 22 naked breasts to estimate their brassiere-wearing shape. Visual and numerical evaluation of the simulated shape revealed that this method could predict brassiere-wearing breast shape based on naked ones and could be expected to serve in a design process and for sales without the need to try on.
Fuzzy Logic Model for Selection of Vertical Formwork Systems

Formwork systems have a considerable share in building construction costs. Accordingly, selecting an appropriate formwork system that respects project individualities plays an important yet challenging role in achieving significant cost savings. In Egypt, current practice in formwork selection primarily uses the subjective decisions of site engineers. This paper presents a fuzzy logic-based model that supports decision makers in selecting the appropriate vertical formwork system for projects. Ten commercial vertical formwork systems commonly used in Egypt are identified with the most important factors affecting their selection. The data were tabulated to serve as a knowledge-based system (KBS) to guide site engineers in selection. On the basis of the KBS, a fuzzy logic model with five input variables, representing the governing factors, is then developed to automate the selection process. The model is tested by applying it on a real-life case study. Results are acceptable and show a promising role for fuzzy logic in formwork selection. DOI: 10.1061/(ASCE)CO.1943-7862 . 0000490. © 2012 American Society of Civil Engineers. CE Database subject headings: Fuzzy sets; Construction management; Construction costs; Formwork (concrete construction). Author keywords: Vertical formwork system; Fuzzy logic; Construction engineering; Knowledge-base.
Active phased array antenna for mobile multimedia services via satellite

This paper introduces an active phased array antenna for mobile DBS service. The main idea for the antenna is to use twelve active array elements for cost effectiveness. For this purpose, the attractive hybrid tracking method with two-dimensional array structure is also used. The electronic beam scan coverage of this antenna is over 24 degrees wide in elevation, and 12 degrees in azimuth. The high-speed tracking capability of this antenna for fast moving vehicles gives other applications in satellite mobile multimedia services like mobile internet services by satellite hybrid link. Finally, this paper also introduces recent results for developing active phased array antennas for the high-speed data communications via satellite.