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Keyword: ERPThe Relationship of Coalition on Employee Spiritual Engagement: Interplay of Organisational Politics
The objective of the study was to establish the relationship between coalition and employee spiritual engagement. The research was quantitative, and data was administered and retrieved from employees at the selected private radio firms. Content validity was utilised to ascertain the validity of the instrument, and the reliability of the instrument was established using Cronbach’s…
Read MoreAn ML-optimized dRRM Solution for IEEE 802.11 Enterprise Wlan Networks
In an enterprise Wifi network, indoor and dense, co-channel interference is a major issue. Wifi controllers help tackle this problem thanks to radio resource management (RRM). RRM is a fundamental building block of any controller functional architecture. One aim of RRM is to process the radio plan such as to maximize the overall network transmit…
Read MoreITSM Software Ranking for Small Medium Enterprises Based on ITIL V3 Quick Win Criteria using Fuzzy SIR Method
There are various software related to the implementation of IT Service Management (ITSM) for a company, including those that are open source and commercial. An input is needed for companies in determining what software to choose from various software, especially for small and medium enterprises (SMEs) that have limited human and financial resources. In this…
Read MoreEducational Domain Management Knowledge Content Identification and Knowledge Updating Method, Based on Enterprise Management Information Interactions
The aim of this paper is to develop the educational domain management knowledge content identification and knowledge updating method, based on formal descriptions of enterprise management information interactions. This is very important because the progress of modern science leads to the emergence of new factual or conceptual knowledge. There is a need for proper methods…
Read MoreTheoretical developments for interpreting kernel spectral clustering from alternative viewpoints
To perform an exploration process over complex structured data within unsupervised settings, the so-called kernel spectral clustering (KSC) is one of the most recommended and appealing approaches, given its versatility and elegant formulation. In this work, we explore the relationship between (KSC) and other well-known approaches, namely normalized cut clustering and kernel k-means. To do…
Read MoreCognitive Artificial Intelligence Method for Interpreting Transformer Condition Based on Maintenance Data
A3S(Arwin-Adang-Aciek-Sembiring) is a method of information fusion at a single observation and OMA3S(Observation Multi-time A3S) is a method of information fusion for time-series data. This paper proposes OMA3S-based Cognitive Artificial-Intelligence method for interpreting Transformer Condition, which is calculated based on maintenance data from Indonesia National Electric Company (PLN). First, the proposed method is tested using…
Read MoreMethodology for Management of Information Security in Industrial Control Systems: A Proof of Concept aligned with Enterprise Objectives.
This article is an extended version of the study presented at the IEEE Ecuador Technical Chapters Meeting (ETCM)-2016. At that time, a methodological proposal was designed, implemented, and applied in a group of industrial plants for the management of the information security of the Industrial control systems (ICS). The present study displays an adaptation and…
Read MoreSystem Testing Evaluation for Enterprise Resource Planning to Reduce Failure Rate
Enterprise Resource Planning (ERP) systems are widely used applications to manage resources, communication and data exchange between different departments and modules with the purpose of managing the overall business process of the organization using one integrated software system. Due to the large scale and the complexity nature of these systems, many ERP implementation projects have…
Read MoreComputationally Efficient Explainable AI Framework for Skin Cancer Detection
Skin cancer stands among some of the fastest growing and fatal malignancies of the world as a result early and accurate diagnosis of skin cancer is essential in order to enhance patient survival and treatment prognosis. Conventional methods of diagnosis including dermoscopy and histopathological examinations are expensive and time consuming also subject to inter-observer error.…
Read MoreTIMeFoRCE: An Identity and Access Management Framework for IoT Devices in A Zero Trust Architecture
Zero Trust Architecture offers a transformative approach to network security by emphasizing ”never trust, always verify.” IoT devices, while increasingly integral to modern ecosystems, pose unique challenges for identity management and access control due to their constrained processing power, memory, and energy capabilities. In a Zero Trust framework, every IoT device is treated as a…
Read MoreImplementation and Simulation of Sequential Adverse Condition Scenarios for Autonomous Driving
Establishing an environment that allows for the quantitative evaluation of the ability of autonomous driving systems to respond to real-world adverse conditions is crucial to ensuring their safety and reliability. This study proposes a dynamic scenario-based simulation framework that simulates complex and sequential hazardous scenarios frequently encountered in actual road environments. The proposed scenarios are…
Read MoreIntegrating Speech and Gesture for Generating Reliable Robotic Task Configuration
This paper presents a system that combines speech and pointing gestures along with four distinct hand gestures to precisely identify both the object of interest and parameters for robotic tasks. We utilized skeleton landmarks to detect pointing gestures and determine their direction, while a pre-trained model, trained on 21 hand landmarks from 2D images, was…
Read MoreFrom Sensors to Data: Model and Architecture of an IoT Public Network
RetePAIoT of Emilia-Romagna region is an IoT Public Network, financed by Emilia-Romagna Region and developed by Lepida Scpa, where citizens, private companies and Public Administrations can integrate free of charge their own sensors of any type and anywhere in the region. The main objective of the project is to provide a facility to implement the…
Read MoreEvaluation of Various Deep Learning Models for Short-Term Solar Forecasting in the Arctic using a Distributed Sensor Network
The solar photovoltaic (PV) power generation industry has experienced substantial, ongoing growth over the past decades as a clean, cost-effective energy source. As electric grids use ever-larger proportions of solar PV, the technology’s inherent variability—primarily due to clouds—poses a challenge to maintaining grid stability. This is especially true for geographically dense, electrically isolated grids common…
Read MoreEnhancing the Network Anomaly Detection using CNN-Bidirectional LSTM Hybrid Model and Sampling Strategies for Imbalanced Network Traffic Data
The cybercriminal utilized the skills and freely available tools to breach the networks of internet-connected devices by exploiting confidentiality, integrity, and availability. Network anomaly detection is crucial for ensuring the security of information resources. Detecting abnormal network behavior poses challenges because of the extensive data, imbalanced attack class nature, and the abundance of features in…
Read MoreAnalysis of Emotions and Movements of Asian and European Facial Expressions
The aim of this study is to develop an advanced framework that not only recognize the dominant facial emotion, but also contains modules for gesture recognition and text-to-speech recognition. Each module is meticulously designed and integrated into unified system. The implemented models have been revised, with the results presented through graphical representations, providing prevalent emotions…
Read MoreOptimizing the Performance of Network Anomaly Detection Using Bidirectional Long Short-Term Memory (Bi-LSTM) and Over-sampling for Imbalance Network Traffic Data
Cybercriminal exploits integrity, confidentiality, and availability of information resources. Cyberattacks are typically invisible to the naked eye, even though they target a wide range of our digital assets, such as internet-connected smart devices, computers, and networking devices. Implementing network anomaly detection proves to be an effective method for identifying these malicious activities. The traditional anomaly…
Read MoreTree-Based Ensemble Models, Algorithms and Performance Measures for Classification
An ensemble method is a Machine Learning (ML) algorithm that aggregates the predictions of multiple estimators or models. The purpose of an ensemble module is to provide better predictive performance than any single contributing model. This can be achieved by producing a predictive model with reduced variance using bagging, and bias using boosting. The Tree-Based…
Read MoreSEVEN ReImagined: A Transmedia Storytelling Evolution Proposal
“Seven ReImagined” is an innovative transmedia storytelling project that reshapes the exploration of the seven deadly sins in a modern context. Building upon the original artwork “Seven”, this venture incorporates traditional media, digital tools, and the latest immersive technologies to cultivate profound user engagement and interaction. The project’s objective is to enhance understanding of timeless…
Read MoreColorized iVAT Images for Labeled Data
A 2-dimensional numerical data set X = {x1,…,xn} with associated category labels {l1,…,ln} can be accurately represented in a 2-dimensional scatterplot where color is used to represent each datum’s label. The colorized scatterplot indicates the presence or absence of spatial clusters in X and any special distribution of labels among those clusters. The same approach…
Read MoreApplication of Lean Practices in Food Supply Chain: The Case of Morocco
Recent studies show the benefits of lean manufacturing implementation in agri-food industries to improve operational and environmental performance. However, only a restricted number of studies have addressed the implementation of lean practices in food companies located in developing countries. This study aims to assess the current implementation status of lean practices in Moroccan agri-food companies,…
Read MoreA Circuit Designer’s Perspective to MOSFET Behaviour: Common Questions and Practical Insights
Metal Oxide Semiconductor Field-Effect Transistors are commonly taught in courses for electrical engineers as they are the most common components within integrated circuits. However, despite numerous papers and books on MOSFETs, students still struggle with understanding their behaviour, particularly in the saturation region. This paper presents an expanded explanation of MOSFET behaviour, with a consistent…
Read MoreInferring Student Needs Based on Facial Expression in Video Images
Limited interactive communication modes between students and teachers in online environments may lead to teachers misinterpreting or overlooking student needs during online teaching. Students learning online may also hesitate to make their needs known even when latent desires in teaching flow, pacing, and review, may be beneficial to the quality of the learning experience. The…
Read MoreHybrid Intrusion Detection Using the AEN Graph Model
The Activity and Event Network (AEN) is a new dynamic knowledge graph that models different network entities and the relationships between them. The graph is generated by processing various network security logs, such as network packets, system logs, and intrusion detection alerts, which allows the graph to capture security-relevant activity and events in the network.…
Read MoreMobility Intelligence: Machine Learning Methods for Received Signal Strength Indicator-based Passive Outdoor Localization
Knowledge of pedestrian and vehicle movement patterns can provide valuable insights for city planning. Such knowledge can be acquired via passive outdoor localization of WiFi-enabled devices using measurements of Received Signal Strength Indicator (RSSI) from WiFi probe requests. In this paper, which is an extension of the work initially presented in WiMob 2021, we continue…
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