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190 results on '"Naeem, M. Asif"'

1. A Web Smart Space Framework for Intelligent Search Engines

Author

Naeem, M. Asif and Asif, Noreen

Subjects
JOURNALS
Abstract

A web smart space is an intelligent environment which has additional capability of searching the information smartly and efficiently. New advancements like dynamic web contents generation has increased the size of web repositories. Among so many modern software analysis requirements, one is to search information from the given repository. But useful information extraction is a troublesome hitch due to the multi-lingual; base of the web data collection. The issue of semantic based information searching has become a standoff due to the inconsistencies and variations in the characteristics of the data. In the accomplished research, a web smart space framework has been proposed which introduces front end processing for a search engine to make the information retrieval process more intelligent and accurate. In orthodox searching anatomies, searching is performed only by using pattern matching technique and consequently a large number of irrelevant results are generated. The projected framework has insightful ability to improve this drawback and returns efficient outcomes. Designed framework gets text input from the user in the form complete question, understands the input and generates the meanings. Search engine searches on the basis of the information provided.

Published
2011

2. Co-Designing a Medication Notification Application with Multi-Channel Reminders

Author

Chanane, Nawal, Mirza, Farhaan, and Naeem, M. Asif

Subjects
Computer Science - Human-Computer Interaction
Abstract

Evidence suggests that medication adherence applications (apps) are one of the most effective methods to remind patients to take medication on time. Reminders via apps are overwhelming today, consumers discard using them after a brief period of initial usage, eventually becoming unfavourable towards them and not using them at all. This study aims to qualitatively determine the key features and design of medication reminder apps that facilitate or disrupt usage from the users perceptive. Three focus groups were conducted with participants aged between 15 and 65+ (N= 12). The participants evaluated a smart medication reminder prototype, then sketched and discussed their thoughts and perceptions within the group. Participants identified, 1) Multi-channel reminders, 2) Medication intake acknowledgement for reporting and 3) Seamless addition of medications and associated reminders as important elements. Understanding consumers needs and concerns will inform the future development of medication reminder apps that are acceptable and valuable to consumers.

Published
2023

3. BlindEye: Blind Assistance Using Deep Learning

Author

Shabbir, Bilal, Salman, Ali, Akhtar, Sohaib, Naeem, M. Asif, Kacprzyk, Janusz, Series Editor, García Márquez, Fausto Pedro, editor, Jamil, Akhtar, editor, Ramirez, Isaac Segovia, editor, Eken, Süleyman, editor, and Hameed, Alaa Ali, editor

Published
2024
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6. Predicting Peak Demand Days for Asthma-Related Emergency Hospitalisations: A Machine Learning Approach

Author

Bhalla, Rashi, Mirza, Farhaan, Naeem, M. Asif, Chan, Amy Hai Yan, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Wu, Shiqing, editor, Yang, Wenli, editor, Amin, Muhammad Bilal, editor, Kang, Byeong-Ho, editor, and Xu, Guandong, editor

Published
2023
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7. Optimizing Semi-Stream CACHEJOIN for Near-Real-Time Data Warehousing

Author

Naeem, M. Asif, Mehmood, Erum, Abbas, M G, and Jamil, Noreen

Subjects
Computer Science - Databases
Abstract

Streaming data join is a critical process in the field of near-real-time data warehousing. For this purpose, an adaptive semi-stream join algorithm called CACHEJOIN (Cache Join) focusing non-uniform stream data is provided in the literature. However, this algorithm cannot exploit the memory and CPU resources optimally and consequently it leaves its service rate suboptimal due to sequential execution of both of its phases, called stream-probing (SP) phase and disk-probing (DP) phase. By integrating the advantages of CACHEJOIN, in this paper we present two modifications in it. First is called P-CACHEJOIN (Parallel Cache Join) that enables the parallel processing of two phases in CACHEJOIN. This increases number of joined stream records and therefore improves throughput considerably. Second is called OP-CACHEJOIN (Optimized Parallel Cache Join) that implements a parallel loading of stored data into memory while the DP phase is executing. We present the performance analysis of both of our approaches with existing CACHEJOIN empirically using synthetic skewed dataset.

Published
2019

12. Multi-interest User Profiling in Short Text Microblogs

Author

Wandabwa, Herman, Naeem, M. Asif, Mirza, Farhaan, Pears, Russel, Nguyen, Andy, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Hofmann, Sara, editor, Müller, Oliver, editor, and Rossi, Matti, editor

Published
2020
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15. Improving a Credit Scoring Model by Incorporating Bank Statement Derived Features

Author

Bunker, Rory P., Zhang, Wenjun, and Naeem, M. Asif

Subjects
Computer Science - Learning
Abstract

In this paper, we investigate the extent to which features derived from bank statements provided by loan applicants, and which are not declared on an application form, can enhance a credit scoring model for a New Zealand lending company. Exploring the potential of such information to improve credit scoring models in this manner has not been studied previously. We construct a baseline model based solely on the existing scoring features obtained from the loan application form, and a second baseline model based solely on the new bank statement-derived features. A combined feature model is then created by augmenting the application form features with the new bank statement derived features. Our experimental results using ROC analysis show that a combined feature model performs better than both of the two baseline models, and show that a number of the bank statement-derived features have value in improving the credit scoring model. The target data set used for modelling was highly imbalanced, and Naive Bayes was found to be the best performing model, and outperformed a number of other classifiers commonly used in credit scoring, suggesting its potential for future use on highly imbalanced data sets.

Published
2016

17. Long-Term Trends in Public Sentiment in Indian Demonetisation Policy

Author

Darliansyah, Adi, Wandabwa, Herman Masindano, Naeem, M. Asif, Mirza, Farhaan, Pears, Russel, Barbosa, Simone Diniz Junqueira, Editorial Board Member, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Kotenko, Igor, Editorial Board Member, Washio, Takashi, Editorial Board Member, Yuan, Junsong, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Bajwa, Imran Sarwar, editor, Kamareddine, Fairouz, editor, and Costa, Anna, editor

Published
2019
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18. E-BRACE: A Secure Electronic Health Record Access Method in Medical Emergency

Author

Nayak, Shraddha, Hossain, Md. Akbar, Mirza, Farhaan, Naeem, M. Asif, Jamil, Noreen, Barbosa, Simone Diniz Junqueira, Editorial Board Member, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Kotenko, Igor, Editorial Board Member, Washio, Takashi, Editorial Board Member, Yuan, Junsong, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Bajwa, Imran Sarwar, editor, Kamareddine, Fairouz, editor, and Costa, Anna, editor

Published
2019
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24. Acceptance of Technology-Driven Interventions for Improving Medication Adherence

Author

Chanane, Nawal, Mirza, Farhaan, Naeem, M. Asif, Mirza, Asfahaan, Diniz Junqueira Barbosa, Simone, Series editor, Chen, Phoebe, Series editor, Du, Xiaoyong, Series editor, Filipe, Joaquim, Series editor, Kotenko, Igor, Series editor, Liu, Ting, Series editor, Sivalingam, Krishna M., Series editor, Washio, Takashi, Series editor, Doss, Robin, editor, Piramuthu, Selwyn, editor, and Zhou, Wei, editor

Published
2017
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25. A Multi-way Semi-stream Join for a Near-Real-Time Data Warehouse

Author

Naeem, M. Asif, Nguyen, Kim Tung, Weber, Gerald, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Huang, Zi, editor, Xiao, Xiaokui, editor, and Cao, Xin, editor

Published
2017
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28. Optimising Queue-Based Semi-stream Joins by Introducing a Queue of Frequent Pages

Author

Naeem, M. Asif, Weber, Gerald, Lutteroth, Christof, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Cheema, Muhammad Aamir, editor, Zhang, Wenjie, editor, and Chang, Lijun, editor

Published
2016
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30. A Cache-Based Semi-Stream Join to deal with Unmatched Stream Data

Author

Naeem, M. Asif, Bajwa, Imran Sarwar, Jamil, Noreen, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Sharaf, Mohamed A., editor, Cheema, Muhammad Aamir, editor, and Qi, Jianzhong, editor

Published
2015
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32. SSCJ: A Semi-Stream Cache Join Using a Front-Stage Cache Module

Author

Naeem, M. Asif, Weber, Gerald, Dobbie, Gillian, Lutteroth, Christof, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Bellatreche, Ladjel, editor, and Mohania, Mukesh K., editor

Published
2013
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33. Tuned X-HYBRIDJOIN for Near-Real-Time Data Warehousing

Author

Naeem, M. Asif, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Ishikawa, Yoshiharu, editor, Li, Jianzhong, editor, Wang, Wei, editor, Zhang, Rui, editor, and Zhang, Wenjie, editor

Published
2013
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34. A Lightweight Stream-Based Join with Limited Resource Consumption

Author

Naeem, M. Asif, Dobbie, Gillian, Weber, Gerald, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Cuzzocrea, Alfredo, editor, and Dayal, Umeshwar, editor

Published
2012
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35. Interacting with Data Warehouse by Using a Natural Language Interface

Author

Naeem, M. Asif, Ullah, Saif, Bajwa, Imran Sarwar, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Bouma, Gosse, editor, Ittoo, Ashwin, editor, Métais, Elisabeth, editor, and Wortmann, Hans, editor

Published
2012
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42. Witan

Author

Denham, Benjamin, primary, Lai, Edmund M-K., additional, Sinha, Roopak, additional, and Naeem, M. Asif, additional

Published
2022
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48. Evaluating Encryption Algorithms for Sensitive Data Using Different Storage Devices

Author

Sassani, Alkorbi, Mohammed, Jamil, Noreen, Naeem, M. Asif, and Mirza, Farhaan

Subjects
Hardware_MEMORYSTRUCTURES, Article Subject
Abstract

Sensitive data need to be protected from being stolen and read by unauthorized persons regardless of whether the data are stored in hard drives, flash memory, laptops, desktops, and other storage devices. In an enterprise environment where sensitive data is stored on storage devices, such as financial or military data, encryption is used in the storage device to ensure data confidentiality. Nowadays, the SSD-based NAND storage devices are favored over HDD and SSHD to store data because they offer increased performance and reduced access latency to the client. In this paper, the performance of different symmetric encryption algorithms is evaluated on HDD, SSHD, and SSD-based NAND MLC flash memory using two different storage encryption software. Based on the experiments we carried out, Advanced Encryption Standard (AES) algorithm on HDD outperforms Serpent and Twofish algorithms in terms of random read speed and write speed (both sequentially and randomly), whereas Twofish algorithm is slightly faster than AES in sequential reading on SSHD and SSD-based NAND MLC flash memory. By conducting full range of evaluative tests across HDD, SSHD, and SSD, our experimental results can give better idea for the storage consumers to determine which kind of storage device and encryption algorithm is suitable for their purposes. This will give them an opportunity to continuously achieve the best performance of the storage device and secure their sensitive data.

Published
2020
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49. Data Analytics in Mental Healthcare

Author

Kamran Ul haq, Ayesha, Khattak, Amira, Jamil, Noreen, Naeem, M. Asif, and Mirza, Farhaan

Subjects
Article Subject
Abstract

Worldwide, about 700 million people are estimated to suffer from mental illnesses. In recent years, due to the extensive growth rate in mental disorders, it is essential to better understand the inadequate outcomes from mental health problems. Mental health research is challenging given the perceived limitations of ethical principles such as the protection of autonomy, consent, threat, and damage. In this survey, we aimed to investigate studies where big data approaches were used in mental illness and treatment. Firstly, different types of mental illness, for instance, bipolar disorder, depression, and personality disorders, are discussed. The effects of mental health on user’s behavior such as suicide and drug addiction are highlighted. A description of the methodologies and tools is presented to predict the mental condition of the patient under the supervision of artificial intelligence and machine learning.

Published
2020
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