To provide social network data (SN) data to researchers for data analysis, protecting user privacy via anonymization is necessary. One anonymization metric for SN data called k-neighbor focuses on the neighborhood sub...
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information security, including integrity and privacy, is an important concern among today's computer users due to increased connectivity. Despite a number of secure algorithms that have been proposed, the trade-o...
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information security, including integrity and privacy, is an important concern among today's computer users due to increased connectivity. Despite a number of secure algorithms that have been proposed, the trade-offs made between security and performance demands further research toward improvement. In bulk data transfer, especially in large messages, the secured processing time takes much longer than non-secured processes. This is due to crypto operations, which include symmetric encryption operations and hashing functions. In the current bulk data transfer phase in secure socket layer (SSL), the server or the client firstly calculates the message authentication code (MAC) of the data using keyed-hash message authentication code (HMAC) operation, and then performs the symmetric encryption on the data together with the MAC. This paper proposes a new algorithm which provides a significant performance gain in bulk data transfer without compromising the security. The proposed algorithm performs the encryption of the data and the calculation of the MAC in parallel. The server calculates the MAC of the data at the same time as the encryption process of the data. Once the calculation of the MAC is completed, only then the MAC will be encrypted. The algorithm was simulated in two processors with one processor performing the MAC calculation and the other on encrypting the data, simultaneously. The communication between the two processors was done via message passing interface (MPI). Based on the performance simulations, the new parallel algorithm gained speedup of 1.74 with 85% efficiency over the current (sequential) algorithm.
Studies on information system success and evaluation have been done for several decades. However, an evaluation should be followed by system improvement to give practical contribution to organization. This study propo...
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ISBN:
(纸本)9781509016495
Studies on information system success and evaluation have been done for several decades. However, an evaluation should be followed by system improvement to give practical contribution to organization. This study proposes an integrated step to evaluate an IS success and analyze its improvement opportunities based on user requirements. To aim this objective, DeLone & McLean success model, KANO model and QFD concept are utilized. A case study of Electronic Disposition and Mailing System (EDMS) in Ministry of State Secretariat Indonesia is presented to illustrate the use of proposed method. The results indicate that priorities of needs are different before and after the integration of Kano's Model in QFD.
Part-of-speech tagging in real-world applications is performed on text in domains which are different from the publicly available large training data sets. The two most successful part-of-speech taggers are trained on...
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Part-of-speech tagging in real-world applications is performed on text in domains which are different from the publicly available large training data sets. The two most successful part-of-speech taggers are trained on the Wall Street Journal corpus, a corpus of millions of words. We compare their performance on a test set from a different domain-astronomy-from documents that are available on the World Wide Web. The Maximum Entropy Part of Speech Tagger (MXPOST) and the Transformation-Based Learning Tagger are well-known and widely used in language research and development systems. The two taggers were tested in several modes: (1) after training on the Wall Street Journal corpus only, (2) after training on only a small body of text from our astronomy domain, (3) with and without an auxiliary lexicon derived from many astronomy-related Web documents, and (4) after incremental training-that is, having been trained on the Wall Street Journal, with additional training from the specific domain. One conclusion from the experiment is that different taggers exhibit different biases when trained on the same data.
Natural language processing (NLP) is a branch of artificial intelligence (AI) that enables computers to comprehend, generate, and manipulate human language. Natural language processing can interrogate the data with na...
Natural language processing (NLP) is a branch of artificial intelligence (AI) that enables computers to comprehend, generate, and manipulate human language. Natural language processing can interrogate the data with natural language text or voice. Abstractive Text Summarization is based on the Natural Language Processing technique that tries to provide new and more concise textual summaries for huge texts. Artificial intelligence and deep learning techniques are used in abstractive summarization to examine the text's essential information and create a new summary that conveys the content more concisely and accurately. This type of summary differs from normal extractive summarizing in that it can generate new summaries beyond simply extracting key lines from the source text. This study presents an abstractive Arabic summarization based on the Multilingual T5 (MT5) model AASMT5 to address these concerns. This technique is based on deep neural networks and models like transformers, which have changed the ability to summarize text. This research has explored the various types of summarizations and highlighted the significance of two prominent techniques: abstractive and extractive summarization. This research describes a complete process for developing an Arabic abstractive summarization model using the MT5 architecture. Experiments on different datasets show that this model achieves state-of-the-art results across MT5.
The pervasive utilization of smartphones, while augmenting personal and professional communications, also elicits mental stress and disrupts the work-life balance. Users necessitate staying connected to critical updat...
The pervasive utilization of smartphones, while augmenting personal and professional communications, also elicits mental stress and disrupts the work-life balance. Users necessitate staying connected to critical updates without undue disruption, necessitating an optimized, user-friendly smartphone interface. However, current "Do Not Disturb (DND)" features fall short of providing the desired customization options, thereby contributing to heightened anxiety and diminished productivity. Consequently, this study proposes a design modification to the DND mode by incorporating an "Exceptional Apps Notification", feature thereby aiding in alleviating stress and enhancing focus by permitting essential alerts from selected apps or contacts. In other words, the users only need to turn off notifications for specific applications, not every application. This approach addresses the problem of users fearing they will miss some important notifications. Therefore, the design process employed principles of selective attention and color theory, and user experience was assessed through questionnaires and psycho-physiological feedback. Early findings suggest the potential for stress reduction, albeit with opportunities for further optimization, such as including a memory feature for user preferences and allowing selective access for specific contacts.
Acquisition of pervasive sensor data can be often unsuccessful due to power outage at nodes, time synchronization issues, interference, network transmission failures or sensor hardware issues. Such failures can lead t...
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The fracture property of amorphous metal was studied by a large scale molecular dynamics (MD) simulation. The Finnis-Sinclair potential for α-iron was used as an inter-atomic potential. At first, we made a model amor...
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ISBN:
(纸本)9781617820632
The fracture property of amorphous metal was studied by a large scale molecular dynamics (MD) simulation. The Finnis-Sinclair potential for α-iron was used as an inter-atomic potential. At first, we made a model amorphous metal by melting-rapid quenching simulation. And then a crystal growth simulation in the amorphous was performed. We used circular model, and the cracktip is assumed to be at the center. In order to analyze the crack growth characteristics in an infinite domain, the linear elastic solution of Mode I crack was used as a boundary condition. The periodic boundary condition was used to the thickness direction. The crack opens in similar fashion and it has smooth surfaces during the amorphous state. As it deformed, some clusters of bcc-crystal nucleate around the cracktip and they grow rapidly. The distribution of deformation zones and deformation mechanism are significantly altered. The grains are not deformed while they are relatively small. The emission of dislocations from the cracktip is observed, after the crystal phase covered the crack-tip surfaces. The grain size appeared small in the vicinity of the crack-tip, and becomes gradually large as it separates form the crack-tip.
Recent trends in computational research show the significance of computation-based biological research, for example, bioinformatics and system biology, and biologically inspired computational research, which includes ...
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Recent trends in computational research show the significance of computation-based biological research, for example, bioinformatics and system biology, and biologically inspired computational research, which includes genetic algorithms, artificial neural networks, and evolutionary programming. Artificial immune systems (AIS) is a novel computing paradigm inspired from the human immune system (HIS). The dramatic features of HIS like distributability, uniqueness, adaptability, mobility, imperfect-detection, and anomaly-detection, have grabbed the attention of computational researchers for adopting HIS principles to design AIS that are robust, scalable, highly flexible, resilient to sub-versioning, and degrade gracefully. Designers of AIS make use of their creative abilities for designing computational systems by extracting corresponding metaphors from HIS. AIS is growing as a core paradigm for a wide application area including: intrusion detection, data analysis, pattern recognition, optimization, robotics, distributed control, and bioinformatics etc. The field of AIS, being in its infancy, bears enormous research potential. This work aims to throw light on some prospective research issues in the field. The effort is based on (1) latest research references and (2) our experience for pioneering AIS based research infrastructure in the Universiti Teknologi Malaysia (UTM). It may help new researchers to jump start AIS research and save their precious time.
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