Open Access. Powered by Scholars. Published by Universities.®
- Institution
-
- Universitas Negeri Malang (103)
- Association of Arab Universities (7)
- The University of Akron (5)
- Old Dominion University (3)
- University of Connecticut (3)
-
- Air Force Institute of Technology (2)
- San Jose State University (2)
- University of Louisville (2)
- Clemson University (1)
- Dakota State University (1)
- Georgia Southern University (1)
- Louisiana State University (1)
- Penn State Dickinson Law (1)
- Portland State University (1)
- University of Arkansas, Fayetteville (1)
- University of Dayton (1)
- University of New Mexico (1)
- University of North Florida (1)
- University of Texas at Arlington (1)
- Virginia Commonwealth University (1)
- Walden University (1)
- Keyword
-
- Deep Learning (9)
- Classification (7)
- CNN (6)
- Deep learning (4)
- Convolutional Neural Network (3)
-
- Forecasting (3)
- LSTM (3)
- Machine Learning (3)
- Machine learning (3)
- Naïve Bayes (3)
- Random Forest (3)
- Artificial Intelligence (2)
- Association Rules (2)
- Bioinformatics (2)
- Blockchain (2)
- Counted data (2)
- Damage Analysis (2)
- Data Mining (2)
- Edge computing (2)
- Engineering (2)
- Herbarium Specimen (2)
- Home assistant (2)
- Image processing (2)
- Internet (2)
- K-Means (2)
- NBR (2)
- Neural Network (2)
- Parallel computing (2)
- Performance (2)
- Poisson Regression (2)
- Publication Year
- Publication
-
- Knowledge Engineering and Data Science (103)
- Future Computing and Informatics Journal (7)
- Williams Honors College, Honors Research Projects (5)
- Theses and Dissertations (3)
- Electronic Theses and Dissertations (2)
-
- Published Works (2)
- 2025 Spring Honors Capstone Projects - Archive (1)
- All Theses (1)
- Annual Research Symposium (1)
- College of Graduate Studies: Theses & Dissertations (1)
- Complex Systems Faculty Publications and Presentations (1)
- Computer Science and Computer Engineering Undergraduate Honors Theses (1)
- Cybersecurity Undergraduate Research Showcase (1)
- Dickinson Law Review (2017-Present) (1)
- Electrical & Computer Engineering Theses & Dissertations (1)
- Electrical and Computer Engineering ETDs (1)
- Electrical and Computer Engineering Faculty Publications (1)
- Engineering Management & Systems Engineering Faculty Publications (1)
- Faculty Research, Scholarly, and Creative Activity (1)
- International Journal of Applied Management and Technology (1)
- LSU Doctoral Dissertations (1)
- Library Philosophy and Practice (e-journal) (1)
- Master's Theses (1)
- UNF Graduate Theses and Dissertations (1)
- Publication Type
Articles 91 - 120 of 140
Full-Text Articles in Systems and Communications
Multilayer Perceptron With Auto Encoder Enabled Deep Learning Model For Recommender Systems, Subhashini Narayan
Multilayer Perceptron With Auto Encoder Enabled Deep Learning Model For Recommender Systems, Subhashini Narayan
Future Computing and Informatics Journal
In this modern world of ever-increasing one-click purchases, movie bookings, music, health- care, fashion, the need for recommendations have increased the more. Google, Netflix, Spotify, Amazon and other tech giants use recommendations to customize and tailor their search engines to suit the user’s interests. Many of the existing systems are based on older algorithms which although have decent accuracies, require large training and testing datasets and with the emergence of deep learning, the accuracy of algorithms has further improved, and error rates have reduced due to the use of multiple layers. The need for large datasets has declined as well. …
Data Forgery Detection In Automatic Generation Control: Exploration Of Automated Parameter Generation And Low-Rate Attacks, Yatish R. Dubasi
Data Forgery Detection In Automatic Generation Control: Exploration Of Automated Parameter Generation And Low-Rate Attacks, Yatish R. Dubasi
Computer Science and Computer Engineering Undergraduate Honors Theses
Automatic Generation Control (AGC) is a key control system utilized in electric power systems. AGC uses frequency and tie-line power flow measurements to determine the Area Control Error (ACE). ACE is then used by the AGC to adjust power generation and maintain an acceptable power system frequency. Attackers might inject false frequency and/or tie-line power flow measurements to mislead AGC into falsely adjusting power generation, which can harm power system operations. Various data forgery detection models are studied in this thesis. First, to make the use of predictive detection models easier for users, we propose a method for automated generation …
Automated Blind Control, Daniel Nahra, Matthew Lacek, Timothy Kurczewski, William Daulton Baksa
Automated Blind Control, Daniel Nahra, Matthew Lacek, Timothy Kurczewski, William Daulton Baksa
Williams Honors College, Honors Research Projects
The objective of this project would be to design and prototype an automated, light and temperature sensing window blinds system. The device would detect temperature, both inside and outside, and incoming sunlight to determine proper window blind position for maximum energy savings. The user would also have the ability to change the settings of the blind from a remote device to a setting that they desire at any given time
Simple Modification For An Apriori Algorithm With Combination Reduction And Iteration Limitation Technique, Adie Wahyudi Oktavia Gama, Ni Made Widnyani
Simple Modification For An Apriori Algorithm With Combination Reduction And Iteration Limitation Technique, Adie Wahyudi Oktavia Gama, Ni Made Widnyani
Knowledge Engineering and Data Science
Apriori algorithm is one of the methods with regard to association rules in data mining. This algorithm uses knowledge from an itemset previously formed with frequent occurrence frequencies to form the next itemset. An a priori algorithm generates a combination by iteration methods that are using repeated database scanning process, pairing one product with another product and then recording the number of occurrences of the combination with the minimum limit of support and confidence values. The a priori algorithm will slow down to an expanding database in the process of finding frequent itemset to form association rules. Modification techniques are …
Segmentation Method For Face Modelling In Thermal Images, Albar Albar, Hendrick Hendrick, Rahmat Hidayat
Segmentation Method For Face Modelling In Thermal Images, Albar Albar, Hendrick Hendrick, Rahmat Hidayat
Knowledge Engineering and Data Science
Face detection is mostly applied in RGB images. The object detection usually applied the Deep Learning method for model creation. One method face spoofing is by using a thermal camera. The famous object detection methods are Yolo, Fast Region Based Convolutional Neural Networks (RCNN), Faster RCNN, SSD, and Mask RCNN. We proposed a segmentation Mask RCNN method to create a face model from thermal images. This model was able to locate the face area in images. The dataset was established using 1600 images. The images were created from direct capturing and collecting from the online dataset. The Mask RCNN was …
Generating Javanese Stopwords List Using K-Means Clustering Algorithm, Aji Prasetya Wibawa, Hidayah Kariima Fithri, Ilham Ari Elbaith Zaeni, Andrew Nafalski
Generating Javanese Stopwords List Using K-Means Clustering Algorithm, Aji Prasetya Wibawa, Hidayah Kariima Fithri, Ilham Ari Elbaith Zaeni, Andrew Nafalski
Knowledge Engineering and Data Science
Stopword removal necessary in Information Retrieval. It can remove frequently appeared and general words to reduce memory storage. The algorithm eliminates each word that is precisely the same as the word in the stopword list. However, generating the list could be time-consuming. The words in a specific language and domain must be collected and validated by specialists. This research aims to develop a new way to generate a stop word list using the K-means Clustering method. The proposed approach groups words based on their frequency. The confusion matrix calculates the difference between the findings with a valid stopword list created …
Efficient Scheduling Of Plantation Company Workers Using Genetic Algorithm, Wayan Firdaus Mahmudy, Andreas Pardede, Agus Wahyu Widodo, Muh Arif Rahman
Efficient Scheduling Of Plantation Company Workers Using Genetic Algorithm, Wayan Firdaus Mahmudy, Andreas Pardede, Agus Wahyu Widodo, Muh Arif Rahman
Knowledge Engineering and Data Science
Workers at large plantation companies have various activities. These activities include caring for plants, regularly applying fertilizers according to schedule, and crop harvesting activities. The density of worker activities must be balanced with efficient and fair work scheduling. A good schedule will minimize worker dissatisfaction while also maintaining their physical health. This study aims to optimize workers' schedules using a genetic algorithm. An efficient chromosome representation is designed to produce a good schedule in a reasonable amount of time. The mutation method is used in combination with reciprocal mutation and exchange mutation, while the type of crossover used is one …
A Review Of Accessing Big Data With Significant Ontologies, Jumah Y.J Sleeman, Jehad A.H Hammad
A Review Of Accessing Big Data With Significant Ontologies, Jumah Y.J Sleeman, Jehad A.H Hammad
Knowledge Engineering and Data Science
Ontology Based Data Access (OBDA) is a recently proposed approach which is able to provide a conceptual view on relational data sources. It addresses the problem of the direct access to big data through providing end-users with an ontology that goes between users and sources in which the ontology is connected to the data via mappings. We introduced the languages used to represent the ontologies and the mapping assertions technique that derived the query answering from sources. Query answering is divided into two steps: (i) Ontology rewriting, in which the query is rewritten with respect to the ontology into new …
Convolutional Neural Network On Tanned And Synthetic Leather Textures, Faadihilah Ahnaf Faiz, Ahmad Azhari
Convolutional Neural Network On Tanned And Synthetic Leather Textures, Faadihilah Ahnaf Faiz, Ahmad Azhari
Knowledge Engineering and Data Science
Tanned leather is an output from complex processes called tanning. Leather tanning is an important step that used to protect the fiber or protein structure of animal’s skin. Another reason of tanning process is to prevent the animal’s skin from any defect or rot. After the tanning is complete, the leather can be applied to produce a wide variety of leather products. Thus, the leather prices usually more expensive because it takes longer time in process. Another way to get cheaper price is make non-animal leather that usually known as synthetic or imitation leather. The purpose of this paper is …
Query Rewriting With Thesaurus-Based For Handling Semantic Heterogeneity In Database Integration, I Made Riyan Adi Nugroho, I Wayan Budi Sentana
Query Rewriting With Thesaurus-Based For Handling Semantic Heterogeneity In Database Integration, I Made Riyan Adi Nugroho, I Wayan Budi Sentana
Knowledge Engineering and Data Science
Nowadays, studies on handling semantic heterogeneity still become a challenge for researcher. Several methods have been used to solve these problems, one of which is query rewriting, implemented by rewriting a query into the latest one by using the selected schema. Semantic query rewriting needs a framework in order to identify the connection through the data schema sources. This line is used as a basis for scheme selection. Also, ontology is a model which often be used in these specific cases. The lack of ontology becomes a significant problem that usually seen. Therefore, this paper will describe an alternative framework …
Flood Prediction Using Artificial Neural Networks: Empirical Evidence From Mauritius As A Case Study, A. Z. Dhunny, Reena H. Seebocus, Z. Allam, Mohammad Yasser Chuttur
Flood Prediction Using Artificial Neural Networks: Empirical Evidence From Mauritius As A Case Study, A. Z. Dhunny, Reena H. Seebocus, Z. Allam, Mohammad Yasser Chuttur
Knowledge Engineering and Data Science
Artificial Neural Networks (ANN) has been well studied for flood prediction. However, there is not enough empirical evidence to generalize ANN applicability to small countries with microclimates prevailing in a small geographical space. In this paper, we focus on the climatic conditions of Mauritius for which we seek to investigate the accuracy of using ANN to predict flooding using locally collected data from 11 meteorological stations spread across the country. The ANN model for flood prediction presented in this work is trained using 20,000 climate data records, collected over a period of two years for Mauritius. Our input climate features …
Human Intestinal Condition Identification Based-On Blended Spatial And Morphological Feature Using Artificial Neural Network Classifier, Ummi Athiyah, Arif Wirawan Muhammad, Ahmad Azhari
Human Intestinal Condition Identification Based-On Blended Spatial And Morphological Feature Using Artificial Neural Network Classifier, Ummi Athiyah, Arif Wirawan Muhammad, Ahmad Azhari
Knowledge Engineering and Data Science
Colon cancer is a type of disease that attacks the intestinal walls cell of humans. Colorectal endoscopic screening technique is a common step carried out by the health expert/gynecologist to determine the condition of the human intestine. Manual interpretation requires quite a long time to reach a result. Along with the development of increasingly advanced digital computing techniques, then some of the weaknesses of the manually endoscopic image interpretation analysis model can be corrected by automating the detection process of the presence or absence of cancerous cells in the gut. Identification of human intestinal conditions using an artificial neural network …
Earthquake Magnitude And Grid-Based Location Prediction Using Backpropagation Neural Network, Bagus Priambodo, Wayan Firdaus Mahmudy, Muh Arif Rahman
Earthquake Magnitude And Grid-Based Location Prediction Using Backpropagation Neural Network, Bagus Priambodo, Wayan Firdaus Mahmudy, Muh Arif Rahman
Knowledge Engineering and Data Science
Earthquakes, a type of inevitable natural disaster, is responsible for the highest average death toll per year compared to other types of a natural disaster. Even though it is inevitable, but it can be anticipated to minimize damage and casualties, such as predicting the earthquake‘s magnitude using a neural network. In this study, a backpropagation algorithm is used to train the multilayer neural network to weekly predict the average magnitude of earthquakes in grid-based locations in Indonesia. Based on the findings in this research, the neural network is able to predict the magnitude of earthquakes in grid-based locations across Indonesia …
Parallelization Of Partitioning Around Medoids (Pam) In K-Medoids Clustering On Gpu, Adhi Prahara, Dewi Pramudi Ismi, Ahmad Azhari
Parallelization Of Partitioning Around Medoids (Pam) In K-Medoids Clustering On Gpu, Adhi Prahara, Dewi Pramudi Ismi, Ahmad Azhari
Knowledge Engineering and Data Science
K-medoids clustering is categorized as partitional clustering. K-medoids offers better result when dealing with outliers and arbitrary distance metric also in the situation when the mean or median does not exist within data. However, k-medoids suffers a high computational complexity. Partitioning Around Medoids (PAM) has been developed to improve k-medoids clustering, consists of build and swap steps and uses the entire dataset to find the best potential medoids. Thus, PAM produces better medoids than other algorithms. This research proposes the parallelization of PAM in k-medoids clustering on GPU to reduce computational time at the swap step of PAM. The parallelization …
Opinion Analysis For Emotional Classification On Emoji Tweets Using The Naïve Bayes Algorithm, Siti Sendari, Ilham Ari Elbaith Zaeni, Dian Candra Lestari, Hanny Prasetya Hariyadi
Opinion Analysis For Emotional Classification On Emoji Tweets Using The Naïve Bayes Algorithm, Siti Sendari, Ilham Ari Elbaith Zaeni, Dian Candra Lestari, Hanny Prasetya Hariyadi
Knowledge Engineering and Data Science
Opinion Analysis is a research study needed to social media, since the content could become a trending topic and has a significant impact on social life. One of the social media that have a big contribution to cyberspace and information development is Twitter. In the Twitter application, users can insert images that represent emotions, facial expressions, or icons. Emoji is a graphic symbol in the form of an image to express a thing, with the Emoji, a text can be read and understood according to its meaning because the image represents it. Of the several things that have been mentioned …
Vehicle Operator Attention Monitor, Matthew Krispinsky, Matt Marsek, Matthew Mayfield, Brian Call
Vehicle Operator Attention Monitor, Matthew Krispinsky, Matt Marsek, Matthew Mayfield, Brian Call
Williams Honors College, Honors Research Projects
Motor vehicle operators’ attention levels can be monitored to improve driver safety. By recording and analyzing the drivers eye gaze, hand position, vehicle speed and engine rpm the driver’s attention can be determined. A Raspberry Pi will be the main processing unit. Data will be pulled and analyzed from the OBD-II port on vehicle speed and engine rpm. The system will be powered from a 12V, 4A pin on the OBD-II port connected to the car battery. A webcam will be used to track the pupil location and determine when the driver is looking at the road. A battery powered …
Tabletop Mechanical Tester, Jamie Dombroski, Brian English, Richard Leffler, Andrew Shirk
Tabletop Mechanical Tester, Jamie Dombroski, Brian English, Richard Leffler, Andrew Shirk
Williams Honors College, Honors Research Projects
The need for hands-on and face-to-face experiences in the engineering classroom is very great. The equations, principles, and concepts can all be learned, but without the visual and tactile application, these don’t always sink in or become concrete. A small-scale tensile test machine was designed, sourced, manufactured, and tested for the purpose of being applied in classroom settings to provide this experience to engineering students. Extensive research was performed concerning tensile machines on the market, the essential elements of which are the load cell, grips, crosshead, extensometer, motor, and frame. The raw materials for the frame were purchased and drawings …
Neural Network Classification Of Brainwave Alpha Signalsin Cognitive Activities, Ahmad Azhari, Adhi Susanto, Andri Pranolo, Yingchi Mao
Neural Network Classification Of Brainwave Alpha Signalsin Cognitive Activities, Ahmad Azhari, Adhi Susanto, Andri Pranolo, Yingchi Mao
Knowledge Engineering and Data Science
The signal produced by human brain waves is one unique feature. Signals carry information and are represented in electrical signals generated from the brain in a typical waveform. Human brain wave activity will always be active even when sleeping. Brain waves will produce different characteristics in different individuals. Physical and behavioral characteristics can be identified from patterns of brain wave activity. This study aims to distinguish signals from each individual based on the characteristics of alpha signals from brain waves produced. Brain wave signals are generated by giving several mental perception tasks measured using an Electroencephalogram (EEG). To get different …
Optimisation Of Rice Fertiliser Composition Using Genetic Algorithms, Retno Dewi Anissa, Wayan Firdaus Mahmudy, Agus Wahyu Widodo
Optimisation Of Rice Fertiliser Composition Using Genetic Algorithms, Retno Dewi Anissa, Wayan Firdaus Mahmudy, Agus Wahyu Widodo
Knowledge Engineering and Data Science
There are so many problems with food scarcity. One of them is not too good rice quality. So, an enhancement in rice production through an optimal fertiliser composition. Genetic algorithm is used to optimise the composition for a more affordable price. The process of genetic algorithm is done by using a representation of a real code chromosome. The reproduction process using a one-cut point crossover and random mutation, while for the selection using binary tournament selection process for each chromosome. The test results showed the optimum results are obtained on the size of the population of 10, the crossover rate …
Handwriting Character Recognition Usingvector Quantization Technique, Haviluddin Haviluddin, Rayner Alfred, Ni’Mah Moham, Herman Santoso Pakpahan, Islamiyah Islamiyah, Hario Jati Setyadi
Handwriting Character Recognition Usingvector Quantization Technique, Haviluddin Haviluddin, Rayner Alfred, Ni’Mah Moham, Herman Santoso Pakpahan, Islamiyah Islamiyah, Hario Jati Setyadi
Knowledge Engineering and Data Science
This paper seeks to explore Learning Vector Quantization (LVQ) processing stage to recognize The Buginese Lontara script from Makassar as well as explaining its accuracy. The testing results of LVQ obtained an accuracy degree of 66.66 %. The most optimal variant of network architecture in the recognition process is a variation of learning rate of 0.02, a maximum epoch of 5000 and a hidden layer of 90 neurons which was the result of recognition based on feature 8. Based on these variations, the obtained performance with a mean square error (MSE) of 0.0306 and the time required during the learning …
Comparison Of Indonesian Imports Forecastingby Limited Period Using Sarima Method, Harits Ar Rosyid, Mutyara Whening Aniendya, Heru Wahyu Herwanto
Comparison Of Indonesian Imports Forecastingby Limited Period Using Sarima Method, Harits Ar Rosyid, Mutyara Whening Aniendya, Heru Wahyu Herwanto
Knowledge Engineering and Data Science
The development of Indonesia's imports fluctuate over years. Inability to anticipate such rapid changes can cause economic slump due to inappropriate policy. For instance, recent years imports in rice led to the extermination of rice reserves. The reason is to maintain the market price of rice in Indonesia. To overcome these changes, forecasting the amount of imports should assist the Government in determining the optimum policy. This can be done by utilizing an algorithm to forecast time series data, in this case the amount of imports in the next few months with a high degree of accuracy. This study uses …
Comparison Of Naïve Bayes Algorithm And Decision Tree C4.5for Hospital Readmission Diabetes Patientsusing Hba1c Measurement, Utomo Pujianto, Asa Luki Setiawan, Harits Ar Rosyid, Ali M. Mohammad Salah
Comparison Of Naïve Bayes Algorithm And Decision Tree C4.5for Hospital Readmission Diabetes Patientsusing Hba1c Measurement, Utomo Pujianto, Asa Luki Setiawan, Harits Ar Rosyid, Ali M. Mohammad Salah
Knowledge Engineering and Data Science
Diabetes is a metabolic disorder disease in which the pancreas does not produce enough insulin or the body cannot use insulin produced effectively. The HbA1c examination, which measures the average glucose level of patients during the last 2-3 months, has become an important step to determine the condition of diabetic patients. Knowledge of the patient's condition can help medical staff to predict the possibility of patient readmissions, namely the occurrence of a patient requiring hospitalization services back at the hospital. The ability to predict patient readmissions will ultimately help the hospital to calculate and manage the quality of patient care. …
Crude Palm Oil Prediction Based On Back Propagation Neutral Network Approach, Hijratul Aini, Haviluddin Haviluddin
Crude Palm Oil Prediction Based On Back Propagation Neutral Network Approach, Hijratul Aini, Haviluddin Haviluddin
Knowledge Engineering and Data Science
Crude palm oil (CPO) production at PT. Perkebunan Nusantara (PTPN) XIII from January 2015 to January 2018 have been treated. This paper aims to predict CPO production using intelligent algorithms called Backpropagation Neural Network (BPNN). The accuracy of prediction algorithms have been measured by mean square error (MSE). The experiment showed that the best hidden layer architecture (HLA) is 5-10-11-12-13-1 with learning function (LF) of trainlm, activation function (AF) of logsig and purelin, and learning rate (LR) of 0.5. This architecture has a good accuracy with MSE of 0.0643. The results showed that this model can predict CPO production in …
The Diffusion Of Ict For Corruption Detectionin Open Government Data, Darusalam Darusalam, Jamaliah Said, Normah Omar, Marijn Janssen, Kazi Sohag
The Diffusion Of Ict For Corruption Detectionin Open Government Data, Darusalam Darusalam, Jamaliah Said, Normah Omar, Marijn Janssen, Kazi Sohag
Knowledge Engineering and Data Science
Corruption occurs in many places within the government. To tackle the issue, open data can be used as one of the tools in creating more insight into the government. The premise of this paper is to support the notion that data opening can bring up new ways of fighting corruption. The current paper aimed at investigating how open data can be employed to detect corruption. This open data is trivial due to challenges like information asymmetry among stakeholders, data might only be opened partly, different sources of data need to be combined, and data might not be easy to use, …
Adam Optimization Algorithmfor Wide And Deep Neural Network, Imran Khan Mohd Jais, Amelia Ritahani Ismail
Adam Optimization Algorithmfor Wide And Deep Neural Network, Imran Khan Mohd Jais, Amelia Ritahani Ismail
Knowledge Engineering and Data Science
The objective of this research is to evaluate the effects of Adam when used together with a wide and deep neural network. The dataset used was a diagnostic breast cancer dataset taken from UCI Machine Learning. Then, the dataset was fed into a conventional neural network for a benchmark test. Afterwards, the dataset was fed into the wide and deep neural network with and without Adam. It was found that there were improvements in the result of the wide and deep network with Adam. In conclusion, Adam is able to improve the performance of a wide and deep neural network.
Selection Of Marine Security Policyusing Fuzzy-Ahp Topsis Hybrid Approach, Hozairi Hozairi, Buhari Buhari, Heru Lumaksono, Marcus Tukan
Selection Of Marine Security Policyusing Fuzzy-Ahp Topsis Hybrid Approach, Hozairi Hozairi, Buhari Buhari, Heru Lumaksono, Marcus Tukan
Knowledge Engineering and Data Science
The research was focused on the integration of Fuzzy set theory with Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to choose the optimum maritime security policy to achieve Indonesia recognition as the world's maritime axis. The method used is AHP with fuzzy based enhancement. Here, the weight of each criterion is calculated to overcome the criticism of the scale of unbalanced rating, uncertainty, and inaccuracy in the pairwise of comparison process. The best recommendation for Indonesian maritime policies is multi task single agency which is greatly infuenced by several factors such as …
High Dimensional Data Clustering Using Self-Organized Map, Ruth Ema Febrita, Wayan Firdaus Mahmudy, Aji Prasetya Wibawa
High Dimensional Data Clustering Using Self-Organized Map, Ruth Ema Febrita, Wayan Firdaus Mahmudy, Aji Prasetya Wibawa
Knowledge Engineering and Data Science
As the population grows and e economic development, houses could be one of basic needs of every family. Therefore, housing investment has promising value in the future. This research implements the Self-Organized Map (SOM) algorithm to cluster house data for providing several house groups based on the various features. K-means is used as the baseline of the proposed approach. SOM has higher silhouette coefficient (0.4367) compared to its comparison (0.236). Thus, this method outperforms k-means in terms of visualizing high-dimensional data cluster. It is also better in the cluster formation and regulating the data distribution.
Exploring Critical Success Factors For Data Integration And Decision-Making In Law Enforcement, Marquay Edmondson, Walter R. Mccollum, Mary-Margaret Chantre, Gregory Campbell
Exploring Critical Success Factors For Data Integration And Decision-Making In Law Enforcement, Marquay Edmondson, Walter R. Mccollum, Mary-Margaret Chantre, Gregory Campbell
International Journal of Applied Management and Technology
Agencies from various disciplines supporting law enforcement functions and processes have integrated, shared, and communicated data through ad hoc methods to address crime, terrorism, and many other threats in the United States. Data integration in law enforcement plays a critical role in the technical, business, and intelligence processes created by users to combine data from various sources and domains to transform them into valuable information. The purpose of this qualitative phenomenological study was to explore the current conditions of data integration frameworks through user and system interactions among law enforcement organizational processes. Further exploration of critical success factors used to …
Profiling And Identifying Individual Usersby Their Command Line Usage And Writing Style, Darusalam Darusalam, Helen Ashman
Profiling And Identifying Individual Usersby Their Command Line Usage And Writing Style, Darusalam Darusalam, Helen Ashman
Knowledge Engineering and Data Science
Profiling and identifying individual users is an approach for intrusion detection in a computer system. User profiles are important in many applications since they record highly user-specific information - profiles are basically built to record information about users or for users to share experiences with each other. This research extends previous research on re-authenticating users with their user profiles. This research focuses on the potential to add psychometric user characteristics into the user model so as to be able to detect unauthorized users who may be masquerading as a genuine user. There are five participants involved in the investigation for …
Energy Efficiency Metrics Of University Data Centers, Leonel Hernandez, Genett Jimenez, Piedad Marchena
Energy Efficiency Metrics Of University Data Centers, Leonel Hernandez, Genett Jimenez, Piedad Marchena
Knowledge Engineering and Data Science
The data centers are fundamental pieces in the network and computing infrastructure,and evidently today more than ever they are relevant. Since they support the processing, analysis, assurance of the data generated in the network and by the applications in the cloud, which every day increases its volume thanks to technologies such as Internet of Things, Virtualization, and cloud computing, among others. Precisely the management of this large volume of information makes the data centers consume a lot of energy, generating great concern to owners and administrators. Green Data Centers offer a solution to this problem, reducing the impact produced by …