The medical social platforms enable users to exchange their reviews that reflect their experience over the drugs. The classification of patients' reviews on drugs into positive or negative ratings and the discovery of the drugs that provoke an Adverse Drug Reaction (ADR) can guide the medical sector and the pharmaceutical sector to understand the patients' discomfort or the patients' satisfaction with specific drugs. This paper presents a model to predict the rating of drugs based on review analysis using natural language processing techniques and machine learning algorithms. The model enables drugs discovery which provokes ADRs via the sentiment extraction of the reviews using the syuzhet package in R-program. The proposed model was applied to the Drugs.com dataset and evaluated using another dataset (drugs.lib) that is not used during the training of the machine learning algorithms. The proposed model achieves an accuracy of 87% and 78% for the Drugs.com and DrugsLib.com testing. Furthermore, the model was applied on Drugs.com dataset to discover the ADRs. It classifies the side effects grading of each review based on its sentiment analysis result. The proposed model discovers 44534 patient reviews out of 213865 indicate that the patients suffer from moderate side effects. Also, it discovers 66 reviews out of 213865 indicate that the patients suffer from severe side effects. Both of the moderate and severe side effects are considered as a trigger of ADRs occurrence. In other words, 21.03% of drugs reviews indicate that the patient suffer from ADRs due the drug consumption.
The performance of the locomotion of a mobile robot on the ground can be improved by adapting the shape or construction of the wheels to different needs, from climbing stairs in a building to climbing an obstacle or an inclined terrain. Thus, various combinations between wheels, crawlers, and legs can be achieved, where each combination solves the problem in a specific way. In this study, we designed a mechanism that can augment an ordinary wheel, by adding retractable “claws”, like the claws of a cat. In our study, the actuation of the “claws” is done using a servomotor, at which point the robot is stopped from moving, to open the “claws”, then these can remain open while the robot moves in the chosen environment. The design of the “claws” can be adapted to various needs, from climbing stairs to climbing obstacles or moving on soft or slippery terrain.
In this work we present the design, development, and evaluation of an integrated system for monitoring hotels' environmental data, offering at the same time an app for the customers to preview these data in real-time. The system integrates a platform for calculating the environmental footprint of the hotels and a benchmarking tool for comparing hotels' environmental achievements, supporting decision-making from their managers. A number of sensors (pool sensor, weather station, indoor air quality sensors), installed in the hotel areas monitor and send the required data to the online monitoring platform. A dashboard is also available for a free preview, where the hotels are able to advertise their real-time measurements to the public. The system was evaluated using the ISO/IEC 25022:2016 and the results are promising so as usability is concerned but also as the satisfaction of the end users.
Given $A\in \mathbb{Z}^{m\times n}$ and $\boldsymbol{b}\in \mathbb{Z}^{m}$ , we provide a sharp upper bound for the $\ell_{\infty}$ -distance from any vertex of the polyhedron $P(A, \boldsymbol{b})=\left\{\boldsymbol{x} \in \mathbb{R}_{\geq 0}^n: A \boldsymbol{x}=\boldsymbol{b}\right\}$ to a nearby feasible integral point under a strong assumption regarding the dimensions of the matrix $A$ . It is hoped that this result provides motivation for conducting further research into providing more such upper bounds under certain additional assumptions.
A hybrid model built using parallel data combines the prerequisites of two or more models in its predecessors, it becomes necessary to reduce the number of these predecessors. For this, we consider it necessary to investigate the cause-and-effect relationships between the preconditions, which are the “main” and cause other precursors, which should become the subject of research and the main decisive factor in the process of making predictions. A hybrid model can only be learned from “necessary” models, that is why it is important to study the predecessor, to identify the “necessary” and “sufficient” predecessor.
In this paper we primarily focus on modifying comparison theorems with strict and nonstrict inequalities for Caputo-Hadamard fractional differential equations (FDEs). First, we point out that the proof of comparison theorem for Caputo-Hadamard FDEs in the paper (Fractals 2019, 27(3), 1950036) is incorrect. And then, we give a modified comparison theorem for solutions of Caputo-Hadamard FDEs of order $p\in(0,1)$ under strict inequalities, then extend order $p$ to arbitrary positive-order. Finally, we present a modified comparison theorem with nonstrict inequalities for solutions of Caputo-Hadamard FDEs.
The capacity of a steel cross-sections is determined by the maximum stresses that develop during the load application. If a connection or a cross-section with inclined walls are the research subject, the stresses have an arduous distribution. As stresses appear correlated to strains, their measurement becomes the focus point. Strain gages are inappropriate to be used due to uncertainty of the position of maximum strains and limited local information. Strains can be conveniently monitored using Digital Image Correlation for which, if the modulus of elasticity of the materials is known, the corresponding stress can be determined. Digital Image Correlation represents a technique which is influenced by the initial settings and surface preparation. Some of the impediments that can be experienced while processing the recorded images are presented from two experimental tests, i.e. (i) an in-line connection for Rectangular Hollow Section, and (ii) a custom built-up steel cross section with inclined parts of the web. The study highlights the benefits of using DIC in monitoring specific criteria i.e. separation of the elements in the connection and different plastic deformation areas in the built-up beam cross-section, respectively. Only 40% of the maximum capacity of the connection is reached for the separation serviceability criterion. More than 50% of the theoretical capacity can be attained by the hollow flange beam due to the plastic strains developed in the beam.
Determining the fair price of options and estimating the price sensitivities are important issues for dealing with financial risk. However, the calculation of these values can be a tedious process. This paper aims at option pricing and the estimation of price sensitivities via a module created by the authors in Python. Furthermore, as it is known, any information system is a collection of sub subsystems, which work together as a series of supportive components to a larger system. This module works to support any ‘Financial Information System’ in its algorithmic approach to option pricing and the estimation of price sensitivities. This module has been developed in Python, which can work side-by-side with any financial information system and supports the decision-making process of financial planning of any financial organization. This Python module is being developed into four subcomponents. A numerical example is provided for determining the fair value of options and estimating the price sensitivities using two different approaches. These values can be important inputs for hedging purposes.
The article's purpose is to study socio-economic development in the conditions of digital transformations, the implementation of strategic analysis, and the determination of further prospects. Approbation of the proposed methodological approaches and the corresponding mathematical toolkit was carried out, which allows calculating the economic potential of the IT sector's development in Ukraine. With the help of systematic approaches, the authors have singled out the regions with the highest prospects for socio-economic development based on SMART specializations. It has been proven that when forming strategies for the socio-economic development of regions, an essential element is to determine their SMART disciplines. The conducted analysis made it possible to assess the possibility of implementing SMART specialization in the IT regions of Ukraine, which can become a crucial priority direction of their strategic development.
This article examines solar tracker technology, focusing on how these components are controlled. It begins with a brief overview of photovoltaic solar panels before discussing the many current types and models of solar trackers. It focuses primarily on the design and modeling of the tracker control system, which includes two rotational axes and LDR sensors. In this work, the prototype was made to simplify the use of a tracker in all possible conditions, although the choice to use this technology depends mainly on the physical characteristics of the terrain. The simplification programs take into account the positions of the sun as well as the times of sunset and sunrise, the software constantly predicts this position after a predetermined period, and provides specific instructions to the engine to track the optimal position. This system does not stop at the control of the actuators, a sleep mode has been added for the idle time to optimize the consumption of the motors, also adding to this a reset of the system in the first position of the solar survey according to a single axis (east-west), in making easier the movement of the tracker to the initial position of the next day.
The fast growth in small satellite commercial-off-the-shelf technologies, that identify current and past periods of space industry, is exploited to design an 1U, 2U and 3U CubeSats able to provide a basic scientific return sufficient to improve quality of information and datasets for various human activities. The reaction wheel is currently the main technology for the attitude control. Normal operation of the reaction wheels unfortunately can cause various interferences on satellite's sensitive payload. After a short overview of the main components and their implications on the use of a reaction wheel, his paper provides a cleanliness assessment and magnetic measurements of a 4 set of reaction wheels targeted to CubeSat implementation.
The paper presents advanced technologies and equipment for metal powder production by grinding in planetary and drum ball mils. The production processes in both types of ball mills as well as the specific characteristics of the produced metal powder are analyzed and discussed.
In everyday life, people are dependent on public or private means of transport. Day by day, this phenomenon leads to a continuous increase in road traffic, a fact that implies the appearance of urban agglomerations, jeopardizing traffic safety, but also a major impact on the environment. Thanks to modern information and communication technologies, these aforementioned problems will be able to be given at least one pertinent advanced solution to lessen the number of transportation related problems we face today. These intelligent transport systems have a wide area of applicability in increasing road safety, minimizing the impact on the environment but also in improving traffic management and maximizing the benefits due to transport. By autonomous vehicle it is understood that the system assists the driver by maintaining a constant speed according to the requirements and conditions of the road segment on which the movement is carried out, by correctly entering the lane without inadvertently leaving it, but also by maintaining a safe distances from surrounding vehicles and obstacles, all this to ensure a safe and incident-free journey. By using a simulation environment such as Carla, we can create an autonomous driving scenario and its training model that we can later use, if it meets all the requirements, on a real vehicle. The simulation allows us to see if the model can be validated or where it still needs improvement without endangering someone's life and without material damage.
The paper presents modern technological methods and equipment used to obtain metal powders from molten and hard metal. The most commonly used atomization methods for metal powder production are surveyed and discussed.
Thermal energy storage (TES) is a practical solution to improve the flexibility of power systems involving renewable energy sources, like solar energy. In the past decades, single-tank thermocline TES has attracted much attention due to its high cost-effectiveness. In order to reduce the volume of heat transfer fluid (HTF) required for storage and improve the degree of stratification, some inexpensive solid materials are usually filled into the tanks. In practice, the non-uniformity of filler bed within a TES tank is unavoidable. Here, an analytical model for thermal transport within sensible heat thermocline tanks that hold non-uniform distributions of filler porosity is derived using Laplace transform. Based on this model, the effect of non-uniform distributed fillers on the thermal performance is investigated. It is demonstrated that the different porosity distributions will lead to significantly different behaviors of outlet temperature and thus varied charging and discharging efficiencies, even as the total amount of filler materials is fixed. This indicates manipulating the distribution of filler bed may be a feasible approach to improve the performance of thermocline tanks.
This paper describes how different sensors such as Soil Moisture sensor, Temperature and Humidity Sensor and Air Quality Sensor are combined with an Internet of Things (IoT) package to monitor the real-time data on an Android application and control the irrigation system used in an agriculture management system. Sensors are synchronized by using an embedded system and each dataset obtained from the sensors are sent wirelessly by an IoT device (Wi-Fi Module) to an Android application. This paper discusses the design of an approach which is expected to enable farmers to collect meaningful data, increase the yield, quantity and quality of agricultural products, enhance competitiveness and sustainability in their produce and reduce waste and human intervention in the agricultural field and to meet the demand of the exponentially growing population. The highlights of the paper are methods to obtain real-time data from sensors, displaying data on Android app and app controlled irrigation system. This system's adaptability and ability to be adjusted depending upon the state of the plants, the environment, etc., are the key features. Agriculture fields, parks, gardens, golf courses etc can all be monitored and watered using this approach.
In the medical domain, the cruelest phase is the diagnosis phase. Regarding the phase of diagnosis of the disease as Socrates said “understanding the questions is the half of the answer”, which means when we can make an accurate diagnosis that will be considered as reaching half of the healing process. This article proposes an accurate system for Parkinson's disease detection. Hence, we will interpret the efficacity of the wrapper methods Genetic Algorithm (GA), Binary Particle Swarm Optimization (BPSO), and machine learning algorithms in the diagnosis of Parkinson's disease the second most common neurologic disease after Alzheimer's disease. Based on the speech signal processing of patients uttering vowels by using the discrete wavelet transform DWT. Then extract the features matrix that contains Linear Predictive Coding (LPC), Zero-Crossing Rate (ZCR), Mel Frequency Cepstral Coefficient (MFCC), and wavelet Shannon entropy. Furthermore, a hybrid method applied the AdaBoost, KNN classifier, and the genetic algorithm to reduce the features and enhance the accuracy of detection. First, the genetic algorithm occurs in the selection of the features and the creation of a new population then applied a combination of KNN classifier and AdaBoost to validate the accuracy of the proposed system. A second time we use the BPSO to select the features. The best accuracy obtained was 100% by both of the models.
In the frame of applied mathematical modeling, a wide spectrum of that approximations of real processes has been proposed and used. The specifics of the quantitative research techniques can be suitably utilized in favour of real situations. In the case of an analysis of a big data set, the consequences between mathematical models can be interesting in the selection of appropriate models. Particularly in a regression analysis, the spectrum of model structures has been widely offered depending on the expert approach or regarding the quality criteria. The quality of the model may not be generally the priority whether on other aspects is a mathematical model focused. For purposes of description of various situations that occurred due to setting the appropriate structure of mathematical models, their fitting behavior is identified progressively in this paper. In this contribution, the selected type of models can be classified as multivariable regression models. The partial dependences of Cardinal-Variables' Dependences are analysed steeply from one-dimensional cases to multidimensional models. The applied research, in which the results can be particularly utilized regarding the progressively changed structure of model, the research within frame of PISA monitoring's Programme for International Student Assessment) is presented.
In the context of reducing air pollution in ports, which are often located in the urban environment of cities, such as the port of Piraeus or Thessaloniki in Greece, the European Directive 2014/94/EU requires the application of Cold Ironing in the shipping sector until the end of 2025. That is, the berthed ships need to be supplied by the electricity system of the port, turning off the operation of their thermal electrical power units. A key question that arises is whether the application of cold ironing is economically viable for various types of ships and under what conditions, without subsidy. In this article, a method for estimating the economic viability of connecting ships to the port network by simply ignoring the network constraints (assuming the availability of an infinite bus) is presented. The proposed method is applied to cruise ships, containerships, and bulk carriers, indicative for the port of Thessaloniki, incorporating standard Medium Voltage (MV) tariffs of the Greek electricity system, determining the allowable corrected annual construction & maintenance cost of a Cold Ironing (CI) investment.
