Optimized Resource Allocation in IoT using Fuzzy Logic and Bio-Inspired Algorithms

IoT smart devices are a confluence of microprocessors, sensors, power source and transceiver modules to effectively sense, communicate and transfer data. Energy efficiency is a key governing value of the network performance of smart devices in distributed IoT networks.Low and discrete power and limited amount of memory and finite amount of resources form some major bottlenecks in the workflow.Dynamic load balancing, reliability and flexibility are heavily relied upon by cloud computing for its accessibility.Resources are dynamically provided to the end client in an as-come on-demand fashion with the global network that is the Internet. Proportionally the need for services is increasing at a rate that is astonishing compared to any other forms of development. Load balancing seems a major challenge faced due to the architecture and the modular nature of our cloud environment. Loads need to be distributed dynamically to all the nodes. In this paper, we have introduced a technique that combines fuzzy logic with various nature inspired algorithms - grey wolf algorithm and firefly algorithm in order to effectively balance the load in a network of IoT devices. The performances of various nature inspired algorithms are compared with a brute force approach on the basis of energy efficiency, network lifetime maximization, node failure rate and packet delivery ratio.

Feature partitioning for robust tree ensembles and their certification in adversarial scenarios

Machine learning algorithms, however effective, are known to be vulnerable in adversarial scenarios where a malicious user may inject manipulated instances. In this work, we focus on evasion attacks, where a model is trained in a safe environment and exposed to attacks at inference time. The attacker aims at finding a perturbation of an instance that changes the model outcome.We propose a model-agnostic strategy that builds a robust ensemble by training its basic models on feature-based partitions of the given dataset. Our algorithm guarantees that the majority of the models in the ensemble cannot be affected by the attacker. We apply the proposed strategy to decision tree ensembles, and we also propose an approximate certification method for tree ensembles that efficiently provides a lower bound of the accuracy of a forest in the presence of attacks on a given dataset avoiding the costly computation of evasion attacks.Experimental evaluation on publicly available datasets shows that the proposed feature partitioning strategy provides a significant accuracy improvement with respect to competitor algorithms and that the proposed certification method allows ones to accurately estimate the effectiveness of a classifier where the brute-force approach would be unfeasible.

Exact Nearest Neighbour Search within Constrained Neighbourhood Using the Forest of Vp-Tree-Like Structures

In this paper, we address the problem of fast nearest neighbour search. Unfortunately, well-known indexing data structures, such as vp-trees perform poorly on some datasets and do not provide significant acceleration compared to the brute force approach. In the paper, we consider an alternative solution, which can be applied if we are not interested in some fraction of distant nearest neighbours. This solution is based on building the forest of vp-tree-like structures and guarantees the exact nearest neighbour search in the epsilon-neighbourhood of the query point.

An Algorithm to Solve the Zeckendorf Game

Zeckendorf proved that every positive integer N can be written uniquely as the sum of non-adjacent Fibonacci numbers. This property can be used to create a two-player Zeckendorf game. A recent paper proved that player 2 has the winning strategy for all N>2. However, the proof was non-constructive. In fact, the paper only provided computer code of the winning strategy of player 2 by brute force. In this paper, we present an algorithm to efficiently solve the Zeckendorf game. Specifically, we convert the game to a directed graph, prove that the graph has no cycles and only one terminal node, and construct an iterative algorithm to find all the winning strategies of player 2. We provide an example to show that the proposed algorithm works much more efficiently than a brute force approach.

Method and Verification for Material Calibration of the Chaboche Plasticity Model for Multiple Material Directions

The Chaboche model is a well-validated non-linear kinematic hardening material model. This material model, like many models, depends on a set of material constants that must be calibrated for it to match the experimental data. Due to the challenge of calibrating these constants, the Chaboche model is often disregarded. The challenge with calibrating the Chaboche constants is that the most reliable method for doing the calibration is a brute force approach, which tests thousands of combinations of constants. Different sampling techniques and optimization schemes can be used to select different combinations of these constants, but ultimately, they all rely on iteratively selecting values and running simulations for each selected set. In the experience of the authors, such brute force methods require roughly 2,500 combinations to be evaluated in order to have confidence that a reasonable solution is found. This process is not efficient. It is time-intensive and labor-intensive. It requires long simulation times, and it requires significant effort to develop the accompanying scripts and algorithms that are used to iterate through combinations of constants and to calculate agreement. A better, more automated method exists for calibrating the Chaboche material constants. In this paper, the authors describe a more efficient, automated method for calibrating Chaboche constants. The method is validated by using it to calibrate Chaboche constants for an IN792 single-crystal material and a CM247 directionally-solidified material. The calibration results using the automated approach were compared to calibration results obtained using a brute force approach. It was determined that the automated method achieves agreeable results that are equivalent to, or supersede, results obtained using the conventional brute force method. After validating the method for cases that only consider a single material orientation, the automated method was extended to multiple off-axis calibrations. The Chaboche model that is available in commercial software, such as ANSYS, will only accept a single set of Chaboche constants for a given temperature. There is no published method for calibrating Chaboche constants that considers multiple material orientations. Therefore, the approach outlined in this paper was extended to include multiple material orientations in a single calibration scheme. The authors concluded that the automated approach can be used to successfully, accurately, and efficiently calibrate multiple material directions. The approach is especially well-suited when off-axis calibration must be considered concomitantly with longitudinal calibration. Overall, the automated Chaboche calibration method yielded results that agreed well with experimental data. Thus, the method can be used with confidence to efficiently and accurately calibrate the Chaboche non-linear kinematic hardening material model.

Resilietn Coupling: The Systems Of Coastally Dependent Communities

As climate change becomes a more prevalent reality, rising sea levels are increasingly a threat to cities and communities in coastal regions. In light of this it is important to consider architecture’s role in the strategizing of defences and resilience. The major issue with traditionally implemented coastal defence programs, such as those considered by the US Army Corp of Engineers, is their brute force approach is repressively one dimensional, undermining the diverse, and complex realities of any community. Orienting itself in the diverse and complex communities of Atlantic Canada, this thesis operates in the face of these challenges and shortfalls. Instead a coupling of systems, activities and events in these coastal communities can make possible an architecture that accommodates, and makes visible, the realities of its changing environs at a multitude of scales, allowing the continued success of human settlement.

Resilietn Coupling: The Systems Of Coastally Dependent Communities

As climate change becomes a more prevalent reality, rising sea levels are increasingly a threat to cities and communities in coastal regions. In light of this it is important to consider architecture’s role in the strategizing of defences and resilience. The major issue with traditionally implemented coastal defence programs, such as those considered by the US Army Corp of Engineers, is their brute force approach is repressively one dimensional, undermining the diverse, and complex realities of any community. Orienting itself in the diverse and complex communities of Atlantic Canada, this thesis operates in the face of these challenges and shortfalls. Instead a coupling of systems, activities and events in these coastal communities can make possible an architecture that accommodates, and makes visible, the realities of its changing environs at a multitude of scales, allowing the continued success of human settlement.

Computation of the Available Force Set of a 3-RPRR Kinematically-Redundant Planar Parallel Manipulator

An algorithm is developed to determine the Available Force Set (AFS) of the 3-RPRR kinematically-redundant planar parallel manipulator. The results of the algorithm are verified against a brute force approach and are found to yield exact results with significantly less computational time. The use of the AFS in a robot design context is illustrated through the analysis of two performance indices: the maximum pure force capable of being applied in any direction and the maximum pure force capable of being applied in a given direction. The algorithm is used to compute the AFS and the performance indices throughout the 3-RPRR robot's workspace. The proposed methodology is a useful tool for the design and analysis of the 3-RPRR robot and could be adapted to other kinematically-redundant planar parallel manipulators.

Aplikasi Stemming Kata Bahasa Lampung Dialek Api Menggunakan Pendekatan Brute-Force dan Pemograman C#

Lampung is one of the areas on the island of Sumatra that has the regional language and script of Lampung. In this province there are two main regional dialects, namely the dialect of fapi and the dialect of nyo. Research efforts for the preservation of the Lampung language digitally have been conducted by researchers from various Universities. The research stemming from Lampung dialects of api is based on the findings of the fact that the dictionary-based Lampung dialects of the Lampung language dialect cannot translate the affix words. Stemming of Lampung language dialects of api is worked with a Brute-force approach. In the Lampung language there are inflexional verbs and derivational verbs. Inflexional verbs are verbs formed from bases that are also categorized verbs while derivational verbs are verbs formed from bases that are categorized in addition to verbs such as nouns, adjectives, adverbs, pronouns and numerals. The purpose of this research is to (1) conduct word stemming with a Brute-force approach, (2) produce an application as a Lampung language word Stemmer dialect of api using C # programming language and online database using Firebase. The methods used in this study consisted of (1) Researchers are looking for, identifying, recording, manually typing 2000 words following the basic words of the Lampung dialect of api, (2) creating a stemming algorithm with a Brute-force approach (3) testing applications that have made. As for the result obtained is the application is able to do word stemming for words that have been identified in 2000 words and if stemming can not be done then the facility is provided to update the database used in the application to be used for stemming because the stemming application is very supportive of the application dictionary-based translation engine. The urgency of Stemming application research is to address the affix word in the Lampung language machine translation machine translation application for further research

CRISPR-SE: a brute force search engine for CRISPR design

CRISPR is a revolutionary genome-editing tool that has been broadly used and integrated within novel biotechnologies. A major component of existing CRISPR design tools is the search engines that find the off-targets up to a predefined number of mismatches. Many CRISPR design tools adapted sequence alignment tools as the search engines to speed up the process. These commonly used alignment tools include BLAST, BLAT, Bowtie, Bowtie2 and BWA. Alignment tools use heuristic algorithm to align large amount of sequences with high performance. However, due to the seed-and-extend algorithms implemented in the sequence alignment tools, these methods are likely to provide incomplete off-targets information for ultra-short sequences, such as 20-bp guide RNAs (gRNA). An incomplete list of off-targets sites may lead to erroneous CRISPR design. To address this problem, we derived four sets of gRNAs to evaluate the accuracy of existing search engines; further, we introduce a search engine, namely CRISPR-SE. CRISPR-SE is an accurate and fast search engine using a brute force approach. In CRISPR-SE, all gRNAs are virtually compared with query gRNA, therefore, the accuracies are guaranteed. We performed the accuracy benchmark with multiple search engines. The results show that as expected, alignment tools reported an incomplete and varied list of off-target sites. CRISPR-SE performs well in both accuracy and speed. CRISPR-SE will improve the quality of CRISPR design as an accurate high-performance search engine.