Modified Firefly Optimization with Deep Learning based Multimodal Biometric Verification Model

Biometric security has become a main concern in the data security field. Over the years, initiatives in the biometrics field had an increasing growth rate. The multimodal biometric method with greater recognition and precision rate for smart cities remains to be a challenge. By comparison, made with the single biometric recognition, we considered the multimodal biometric recognition related to finger vein and fingerprint since it has high security, accurate recognition, and convenient sample collection. This article presents a Modified Firefly Optimization with Deep Learning based Multimodal Biometric Verification (MFFODL-MBV) model. The presented MFFODL-MBV technique performs biometric verification using multiple biometrics such as fingerprint, DNA, and microarray. In the presented MFFODL-MBV technique, EfficientNet model is employed for feature extraction. For biometric recognition, MFFO algorithm with long short-term memory (LSTM) model is applied with MFFO algorithm as hyperparameter optimizer. To ensure the improved outcomes of the MFFODL-MBV approach, a widespread experimental analysis was performed. The wide-ranging experimental analysis reported improvements in the MFFODL-MBV technique over other models

Smart Health Predicting System Using Data Mining

An overview of the data mining techniques with its applications, medical, and educational aspects of Clinical Predictions. In medical and health care areas, due to regulations and due to the availability of computers, a large amount of data is becoming available. Such a large amount of data cannot be processed by humans in a short time to make diagnosis, and treatment schedules. A major objective is to evaluate datamining techniques in clinical and health care applications to develop accurate decisions. It also gives a detailed discussion of medical data mining techniques which can improve various aspects of Clinical Predictions. It is a new powerful technology which is of high interest incomputer world. It is a sub field of computer science that uses already existing data in different databases to transform it into new researches and results. It makes use of machine learning and database management to extract new patterns from large datasets and the knowledge associated with these patterns. The actual task is to extract data by automatic orsemi- automatic means. The different parameters included in data mining include clustering, forecasting, path analysis and predictive analysis. It might have happened so many times that you or someone yours need doctors help immediately, but they are not available due to some reason. The Health Prediction system is an end user support and online consultation project. Here we propose a system that allows users to get instant guidance on their health issues through an intelligent health care system online. The system is fed with various symptoms and the disease/illness associated with those systems. The system allows user to share their symptoms and issues. It then processes userssymptoms to check for various illness that could be associated with it. Here we use some intelligent data mining techniques to guess the most accurate illness that could be associated with patient’s symptoms. If the system is not able to provide suitable results, it informs the user about the type of disease or disorder it feels user’s symptoms are associated with. If users symptoms do not exactly match any disease in our database

Measuring cognitive load and cognition: metrics for technology-enhanced learning

This critical and reflective literature review examines international research published over the last decade to summarise the different kinds of measures that have been used to explore cognitive load and critiques the strengths and limitations of those focussed on the development of direct empirical approaches. Over the last 40 years, cognitive load theory has become established as one of the most successful and influential theoretical explanations of cognitive processing during learning. Despite this success, attempts to obtain direct objective measures of the theory's central theoretical construct – cognitive load – have proved elusive. This obstacle represents the most significant outstanding challenge for successfully embedding the theoretical and experimental work on cognitive load in empirical data from authentic learning situations. Progress to date on the theoretical and practical approaches to cognitive load are discussed along with the influences of individual differences on cognitive load in order to assess the prospects for the development and application of direct empirical measures of cognitive load especially in technology-rich contexts

6G Enabled Smart Infrastructure for Sustainable Society: Opportunities, Challenges, and Research Roadmap

The 5G wireless communication network is currently faced with the challenge of limited data speed exacerbated by the proliferation of billions of data-intensive applications. To address this problem, researchers are developing cutting-edge technologies for the envisioned 6G wireless communication standards to satisfy the escalating wireless services demands. Though some of the candidate technologies in the 5G standards will apply to 6G wireless networks, key disruptive technologies that will guarantee the desired quality of physical experience to achieve ubiquitous wireless connectivity are expected in 6G. This article first provides a foundational background on the evolution of different wireless communication standards to have a proper insight into the vision and requirements of 6G. Second, we provide a panoramic view of the enabling technologies proposed to facilitate 6G and introduce emerging 6G applications such as multi-sensory–extended reality, digital replica, and more. Next, the technology-driven challenges, social, psychological, health and commercialization issues posed to actualizing 6G, and the probable solutions to tackle these challenges are discussed extensively. Additionally, we present new use cases of the 6G technology in agriculture, education, media and entertainment, logistics and transportation, and tourism. Furthermore, we discuss the multi-faceted communication capabilities of 6G that will contribute significantly to global sustainability and how 6G will bring about a dramatic change in the business arena. Finally, we highlight the research trends, open research issues, and key take-away lessons for future research exploration in 6G wireless communicatio

The Origins of Bagan: The archaeological landscape of Upper Burma to AD 1300.

The archaeological landscape of Upper Burma from the middle of the first millennium BC to the Bagan period in the 13th-14th century AD is a landscape of continuity. Finds of polished stone and bronze artifacts suggest the existence of early metal-using cultures in the Chindwin and Samon River Valleys, and along parts of the Ayeyarwady plain. Increasing technological and settlement complexity in the Samon Valley suggests that a distinctive culture whose agricultural and trade success can be read in the archaeological record of the Late Prehistoric period developed there. The appearance of the early urban "Pyu" system of walled central places during the early first millennium AD seems to have involved a spread of agricultural and management skills and population from the Samon. The leaders of the urban centres adopted Indic symbols and Sanskrit modes of kingship to enhance and extend their authority. The early urban system was subject over time to a range of stresses including siltation of water systems, external disruption and social changes as Buddhist notions of leadership eclipsed Brahmanical ones. The archaeological evidence indicates that a settlement was forming at Bagan during the last centuries of the first millennium AD. By the mid 11th century Bagan began to dominate Upper Burma, and the region began a transition from a system of largely autonomous city states to a centralised kingdom. Inscriptions of the 11th to 13th centuries indicate that as the Bagan Empire expanded it subsumed the agricultural lands that had been developed by the Pyu

The Origins of Bagan: The archaeological landscape of Upper Burma to AD 1300.

The archaeological landscape of Upper Burma from the middle of the first millennium BC to the Bagan period in the 13th-14th century AD is a landscape of continuity. Finds of polished stone and bronze artifacts suggest the existence of early metal-using cultures in the Chindwin and Samon River Valleys, and along parts of the Ayeyarwady plain. Increasing technological and settlement complexity in the Samon Valley suggests that a distinctive culture whose agricultural and trade success can be read in the archaeological record of the Late Prehistoric period developed there. The appearance of the early urban "Pyu" system of walled central places during the early first millennium AD seems to have involved a spread of agricultural and management skills and population from the Samon. The leaders of the urban centres adopted Indic symbols and Sanskrit modes of kingship to enhance and extend their authority. The early urban system was subject over time to a range of stresses including siltation of water systems, external disruption and social changes as Buddhist notions of leadership eclipsed Brahmanical ones. The archaeological evidence indicates that a settlement was forming at Bagan during the last centuries of the first millennium AD. By the mid 11th century Bagan began to dominate Upper Burma, and the region began a transition from a system of largely autonomous city states to a centralised kingdom. Inscriptions of the 11th to 13th centuries indicate that as the Bagan Empire expanded it subsumed the agricultural lands that had been developed by the Pyu

The study of Wai Phra Kao Wat in Bangkok, Thailand

The study presents a new form of pilgrimage introduced by Thai authorities and involving visiting to nine temples (Wai Phra Kao Wat) in Bangkok. I will focus on four main aspects of this phenomenon. Firstly, the study will describe the dynamic application of the practice (Wai Phra Kao Wat) including the forms of devotion, the designation of temples by authorities, the pilgrims’ experience, and the role played by local ‘communities’ (chumchon). Secondly, the study will consider this pilgrimage as a case study with which to explore how Thai cultural phenomena provide multiple avenues for Thai people to reflect on their perception of the relation between Buddhism (Theravada Buddhism in particular) and the state. Thirdly, the study explores the contribution of ‘new’ performances of religiosity in popular Buddhism into shaping modern economy and rhetorical politics. Lastly, the study will provide the significance of Wai Phra Kao Wat that could shed light on important contemporary Thai cultural phenomena such as the emergence of ‘pilgrimage tourism’ on socio-cultural and economic changes and the relationship between ritual practice and Thai citizenship. The ethnographic methods including participant observation and interviewing are mainly employed throughout the fieldwork. I conclude that Buddhism in contemporary Thailand becomes an instrument to negotiate identities and meanings at the level of governance. Wai Phra Kao Wat, a state-oriented campaign, has been then utilised to enhance Thai capital’s venture into the global economy as well as to establish regime legitimacy with the inculcation of nation, religion, and monarchy

Toward practical argument systems for verifiable computation

textHow can a client extract useful work from a server without trusting it to compute correctly? A modern motivation for this classic question is third party computing models in which customers outsource their computations to service providers (as in cloud computing). In principle, deep results in complexity theory and cryptography imply that it is possible to verify that an untrusted entity executed a computation correctly. For instance, the server can employ probabilistically checkable proofs (PCPs) in conjunction with cryptographic commitments to generate a succinct proof of correct execution, which the client can efficiently check. However, these theoretical solutions are impractical: they require thousands of CPU years to verifiably execute even simple computations. This dissertation describes the design, implementation, and experimental evaluation viiiof a system, called Pepper, that brings this theory into the realm of plausibility. Pepper incorporates a series of algorithmic improvements and systems engineering techniques to improve performance by over 20 orders of magnitude, relative to an implementation of the theory without our refinements. These include a new probabilistically checkable proof encoding with nearly optimal asymptotics, a concise representation for computations, a more efficient cryptographic commitment primitive, and a distributed implementation of the server with GPU acceleration to reduce latency. Additionally, Pepper extends the verification machinery to handle realistic applications of third party computing: those that interact with remote storage or state (e.g., MapReduce jobs, database queries). To do so, Pepper composes techniques from untrusted storage with the aforementioned technical machinery to verifiably offload both computations and state. Furthermore, to make it easy to use this technology, Pepper includes a compiler to automatically transform programs in a subset of C into executables that run verifiably. One of the chief limitations of Pepper is that verifiable execution is still orders of magnitude slower than an unverifiable native execution. Nonetheless, Pepper takes powerful results from complexity theory and verifiable computation a few steps closer to practicalityComputer Science

A Systematic Literature Review on Blockchain Enabled Federated Learning Framework for Internet of Vehicles

While the convergence of Artificial Intelligence (AI) techniques with improved information technology systems ensured enormous benefits to the Internet of Vehicles (IoVs) systems, it also introduced an increased amount of security and privacy threats. To ensure the security of IoVs data, privacy preservation methodologies have gained significant attention in the literature. However, these strategies also need specific adjustments and modifications to cope with the advances in IoVs design. In the interim, Federated Learning (FL) has been proven as an emerging idea to protect IoVs data privacy and security. On the other hand, Blockchain technology is showing prominent possibilities with secured, dispersed, and auditable data recording and sharing schemes. In this paper, we present a comprehensive survey on the application and implementation of Blockchain-Enabled Federated Learning frameworks for IoVs. Besides, probable issues, challenges, solutions, and future research directions for BC-Enabled FL frameworks for IoVs are also presented. This survey can further be used as the basis for developing modern BC-Enabled FL solutions to resolve different data privacy issues and scenarios of IoVs

Fault tolerance of MPI applications in exascale systems: The ULFM solution

[Abstract] The growth in the number of computational resources used by high-performance computing (HPC) systems leads to an increase in failure rates. Fault-tolerant techniques will become essential for long-running applications executing in future exascale systems, not only to ensure the completion of their execution in these systems but also to improve their energy consumption. Although the Message Passing Interface (MPI) is the most popular programming model for distributed-memory HPC systems, as of now, it does not provide any fault-tolerant construct for users to handle failures. Thus, the recovery procedure is postponed until the application is aborted and re-spawned. The proposal of the User Level Failure Mitigation (ULFM) interface in the MPI forum provides new opportunities in this field, enabling the implementation of resilient MPI applications, system runtimes, and programming language constructs able to detect and react to failures without aborting their execution. This paper presents a global overview of the resilience interfaces provided by the ULFM specification, covers archetypal usage patterns and building blocks, and surveys the wide variety of application-driven solutions that have exploited them in recent years. The large and varied number of approaches in the literature proves that ULFM provides the necessary flexibility to implement efficient fault-tolerant MPI applications. All the proposed solutions are based on application-driven recovery mechanisms, which allows reducing the overhead and obtaining the required level of efficiency needed in the future exascale platforms.Ministerio de Economía y Competitividad and FEDER; TIN2016-75845-PXunta de Galicia; ED431C 2017/04National Science Foundation of the United States; NSF-SI2 #1664142Exascale Computing Project; 17-SC-20-SCHoneywell International, Inc.; DE-NA000352