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Keyword: ModelOrganizational Agility Assessment of a Moroccan Healthcare Organization in Times of COVID-19
Since its appearance, COVID-19 has severely impacted the healthcare sector all over the world. The healthcare organizations should be agile in order to cope with this new health crisis. Indeed, organization agility was highly recommended as an essential basis for flexibility, innovation, speed, as well competitiveness. Different research provided different conceptual models suitable to evaluate…
Read MoreDecision Making System for Improving Firewall Rule Anomaly Based on Evidence and Behavior
Firewalls are controlled by rules which often incur anomalies. The anomalies are considered serious problems that administrators do not desire to happen over their firewalls because they cause more vulnerabilities and decrease the overall performance of the firewall. Resolving anomaly rules that have already occurred on the firewall is difficult and mainly depends on the…
Read MoreNeural Network-Based Fault Diagnosis of Joints in High Voltage Electrical Lines
In this paper a classification system based on a complex-valued neural network is used to evaluate the health state of joints in high voltage overhead transmission lines. The aim of this method is to prevent breakages on the joints through the frequency response measurements obtained at the initial point of the network. The specific advantage…
Read MoreStudy of the Effect of Abnormalities in the External Ear Inducing Hearing Problems
Tinnitus is a phenomenon for which the patient hears sound in the absence of any external sound source. To this day, there is no cure for this phantom sound perception. But it can be masked temporarily to help relief the patient’s pain. In order to allow this, a better understanding of the phenomenon is needed.…
Read MoreAssessing the Operator’s Readiness to Perform Tasks of Controlling by the Unmanned Aerial Platforms
Together with the intensity of development in the field of technology of unmanned platforms and their effective use for solving various tasks of peacetime and war, the requirements for the training of the operator managing the platform also increase. This fully applies to personnel providing the flight of manned means. Nevertheless, there are significant differences…
Read MoreEffects of Oversampling SMOTE in the Classification of Hypertensive Dataset
Hypertensive or high blood pressure is a medical condition that can be driven by several factors. These factors or variables are needed to build a classification model of the hypertension dataset. In the construction of classification models, class imbalance problems are often found due to oversampling. This research aims to obtain the best classification model…
Read MoreA Framework of E-Procurement Technology for Sustainable Procurement in ISO 14001 Certified Firms in Malaysia
With the current emerging development pattern in Malaysia, E-Government has been unveiled by the Malaysian Government to be one of the multimedia super corridor flagship applications to implement digital technology to improve government operations. E-procurement was originally utilized by businesses to minimize turnaround times and prices, but recently it was often used as a platform…
Read MoreDevelopment of Soil Moisture Monitoring by using IoT and UAV-SC for Smart Farming Application
Soil moisture is a fundamental factor for smart farming that is used to control the water management system. In this paper, the unmanned aerial vehicle (UAV) small cell (UAV-SC) can provide Internet of things (IoT) as the hotspot mobility network, due to the minimum limitation energy of connected IoT. The development of ground sensor (GS)…
Read MoreDesign and Optimization of a Three Stage Electromechanical Power Unit using Numerical Methods
The advent of electric vehicles has changed the face of the automobile industry. The drive system properties of vehicles such as eBikes or electric cars differ fundamentally from those of a diesel engine. The lack of a conventional internal combustion engine has made the vehicles considerably silent. Nevertheless, previously hidden sources of vibration and noise…
Read MoreComputational Intelligence and Statistical Learning Performances on Predicting Dengue Incidence using Remote Sensing Data
Dengue is a viral infection disease transmitted to people through the bite of specific mosquito species living in a tropical zone. According to the World Health Organization, dengue has been listed among the top-ten diseases for 2019 as it makes 3.9 billion people in 128 countries be at risk of infection. One major cause of…
Read MoreLogistics Solutions in the Preparation Phase for the Appearance of Disasters
Natural disasters have caused not only economic but also human losses. These events bring with them, among other things, deficiencies in the supply of food, clothing, health and cleaning products, to name a few. This situation makes it imperative to locate facilities that can supply the needs, as mentioned earlier, to the victims in the…
Read MoreOptimization of the Procedures for Checking the Functionality of the Greek Railways: Data Mining and Machine Learning Approach to Predict Passenger Train Immobilization
Information is the driving force of businesses because it can ensure the ability of knowledge and prediction. The railway industry produces a huge volume of data, with the proper processing of them and the use of innovative technology, there is the possibility of beneficial information to be provided which constitute the deciding factor for the…
Read MoreUtilization of Data Mining to Predict Non-Performing Loan
In the banking industry, the existence of problem loans is inevitable. NPL (Non-Performing Loan) will certainly have an impact on the reduction in the capital of a bank. One good step in reducing the risk of credit default or the emergence of non-performing loans is to take proper care of debtors who begin to experience…
Read MoreMalware Classification Based on System Call Sequences Using Deep Learning
Malware has always been a big problem for companies, government agencies, and individuals because people still use it as a primary tool to influence networks, applications, and computer operating systems to gain unilateral benefits. Until now, malware detection with heuristic and signature-based methods are still struggling to keep up with the evolution of malware. Machine…
Read MoreA Survey on 3D Hand Skeleton and Pose Estimation by Convolutional Neural Network
Restoring, estimating the fully 3D hand skeleton and pose from the image data of the captured sensors/cameras applied in many applications of computer vision and robotics: human-computer interaction; gesture recognition, interactive games, Computer-Aided Design (CAD), sign languages, action recognition, etc. These are applications that flourish in Virtual Reality and Augmented Reality (VR/AR) technologies. Previous survey…
Read MoreRobust Static Output-Feedback Fault Tolerant Control for a Class of T-S Fuzzy Systems using Adaptive Sliding Mode Observer Approach
In this paper, the problems of actuator and sensor fault estimation (FE) and fault-tolerant control (FTC) for uncertain nonlinear systems represented by Takagi-Sugeno (T-S) fuzzy models are investigated. First, a robust fuzzy adaptive sliding mode observer (SMO) is designed to simultaneously estimate system states and both actuator and sensor faults. Then, using the obtained on-line…
Read MoreFraud Detection Call Detail Record Using Machine Learning in Telecommunications Company
Fraud calls have a serious impact on telecommunications operator revenues. Fraud detection is very important because service providers can feel a significant loss of income. We conducted a fraud research case study on one of the operators that experienced fraud in 2009 and 2018. Call Detail Record (CDR) containing records of customer conversations such as…
Read MoreEnergy Recovery Equipment and Control Strategies in Various Climate Regions
Different types of air-to-air energy recovery technologies such as coil loops, heat pipes, sensible wheels, and total energy wheels are frequently incorporated in HVAC systems in an attempt to reduce energy consumption. This study examines the impact of various types of energy recovery technologies and capacity control strategies on a building’s cooling, heating, and fan…
Read MoreAdapting to Individual Differences (ATID) For Inductive Thinking and Learning Purpose
The research in general aims to develop students’ writing skills by applying a model with reader response strategy and visual symbols to promote students’ morals. Specifically, this inquiry is expected to describe the acceptability, comparison, impact, strength, and shortcomings, and the model Adapting To Individual Differences (ATID) of Indonesian literature learning to promote writing skills.…
Read MoreOntologic Design of Software Engineering Knowledge Area Knowledge Components
The article sets forth the solution of the educational resources semantic context knowledge components development task, based on the learning technology project-oriented concepts, graduate’s competency model and ontological; engineering. The being considered ontology model and knowledge display formalisms allow, firstly, relevantly image the educational resources semantic context in the support concepts ontology format, and their…
Read MoreCitizen Behavior: The Evaluation of Complaint Application that Connected to Smart City
SIARAN is application which is created by Government of South Tangerang City, Indonesia. The application is e-government services social media based. It is designed for citizens to be able to report problems that occur around South Tangerang City. The research was conducted to find out the factors that affect the intention of SIARAN’s users. The…
Read MoreA Novel Representative k-NN Sampling-based Clustering Approach for an Effective Dimensionality Reduction-based Visualization of Dynamic Data
Visualization plays a crucial role in the exploratory analysis of Big Data. The direct visualization of Big Data is a challenging task and difficult to analyze. Dimensionality Reduction techniques extract the features in the context of visualization. Due to the unsupervised and non-parametric nature, most of the dimensionality reduction techniques are not evaluated quantitatively and…
Read MoreSolutions for Building a System to Support Motion Control for Autonomous Vehicle
With a model predictive control approach including boundary analysis and uncertain prediction of activities of different road participants, this paper proposes solutions that support motion control by steering control and appropriate acceleration to create safe motion trajectories for an autonomous vehicle. The motion control support element is determined by the principle of minimal intervention and…
Read MoreWarehouse Relocation of a Company in the Automotive Industry Using P-median
To have enough information on time can be helpful when companies try to reduce costs and operate more efficiently. An international company that supplies parts for the automotive industry is currently testing its new facilities in Mexico. The relocation of the raw materials and finished goods warehouses were tested using a P-Median model. The operating…
Read MoreA Fuzzy-PID Controller Combined with PSO Algorithm for the Resistance Furnace
The paper presents a novel control strategy applying the particle swarm optimization (PSO) algorithm to optimize the scaling weights coefficients of the fuzzy-PID controller for the resistance furnace temperature control system, called PSO-based fuzzy-PID controller/ algorithm. The proposed PSO-based fuzzy-PID controller in this paper consist of the fuzzy-PID controller and the PSO algorithm. The proposed…
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