A Feature-Independent Hyper-Heuristic Approach for Solving the Knapsack Problem

Recent years have witnessed a growing interest in automatic learning mechanisms and applications. The concept of hyper-heuristics, algorithms that either select among existing algorithms or generate new ones, holds high relevance in this matter. Current research suggests that, under certain circumstances, hyper-heuristics outperform single heuristics when evaluated in isolation. When hyper-heuristics are selected among existing algorithms, they map problem states into suitable solvers. Unfortunately, identifying the features that accurately describe the problem state—and thus allow for a proper mapping—requires plenty of domain-specific knowledge, which is not always available. This work proposes a simple yet effective hyper-heuristic model that does not rely on problem features to produce such a mapping. The model defines a fixed sequence of heuristics that improves the solving process of knapsack problems. This research comprises an analysis of feature-independent hyper-heuristic performance under different learning conditions and different problem sets.

Deep neural networks for quantum circuit mapping

Quantum computers have become reality thanks to the effort of some majors in developing innovative technologies that enable the usage of quantum effects in computation, so as to pave the way towards the design of efficient quantum algorithms to use in different applications domains, from finance and chemistry to artificial and computational intelligence. However, there are still some technological limitations that do not allow a correct design of quantum algorithms, compromising the achievement of the so-called quantum advantage. Specifically, a major limitation in the design of a quantum algorithm is related to its proper mapping to a specific quantum processor so that the underlying physical constraints are satisfied. This hard problem, known as circuit mapping, is a critical task to face in quantum world, and it needs to be efficiently addressed to allow quantum computers to work correctly and productively. In order to bridge above gap, this paper introduces a very first circuit mapping approach based on deep neural networks, which opens a completely new scenario in which the correct execution of quantum algorithms is supported by classical machine learning techniques. As shown in experimental section, the proposed approach speeds up current state-of-the-art mapping algorithms when used on 5-qubits IBM Q processors, maintaining suitable mapping accuracy.

The Mimic Man in Kiran Desai’s The Inheritance of Loss

Spread over continents, countries and cultures, Kiran Desai’s The Inheritance of Loss (2006) takes us on a tour de force into the realms of multiculturalism and hybridity in Indian culture. It focuses on the changing face of India, amidst East - West encounter, globalization and glocalization. The novel as a postcolonial text puts forth, the authority politics of cultural imperialism, even after the independence of India. This paper appraises the novel using Homi. K. Bhabha’s theory of mimicry, hybridity and ambivalence. It concentrates on the mimic man of the novel Judge Jemubhai Patel. This paper focuses on the hybridization of culture along with the making of reformed hybrids who are in a constant conflict with their identity, language and culture on account of the praxis between the culture of the colonized and the colonizer during and after colonization of the colonized. This paper recommends proper mapping of mimicry and hybridity with indigenous culture, values and ethics. It advocates sowing and stringing in cultural amalgamation and westernization in indigenous Indian culture and ethos for a better life and better Indian society.

A QoS provisioning architecture of fiber wireless network based on XGPON and IEEE 802.11ac

The integration of the XGPON network with the 5G WLAN network is a suitable solution for next-generation high-speed access Internet service. We demonstrated the integration of two different standards via the QoS concept. Further, this work also presents a proper mapping scheme of QoS traffic between XG-PON and fifth-generation Wi-Fi standards known as IEEE 802.11ac. The analysis assessment compares the behavior of different IEEE 802.11ac standards with XGPON with-respect-to multimedia traffic in the FiWi network. To assess the performance of the FiWi network, the OMNET++ and INET framework are used to carrying out a comparative analysis in terms of upstream (US) delay and fairness index. The study concludes that the EDCA Wi-Fi module has better performance than the DCF Wi-Fi module with the integrated XGPON system for the FiWi access network.

A Compressed Sensing Approach for Multiple Obstacle Localisation Using Sonar Sensors in Air

Methods for autonomous navigation systems using sonars in air traditionally use the time-of-flight technique for obstacle detection and environment mapping. However, this technique suffers from constructive and destructive interference of ultrasonic reflections from multiple obstacles in the environment, requiring several acquisitions for proper mapping. This paper presents a novel approach for obstacle detection and localisation using inverse problems and compressed sensing concepts. Experiments were conducted with multiple obstacles present in a controlled environment using a hardware platform with four transducers, which was specially designed for sending, receiving and acquiring raw ultrasonic signals. A comparison between the performance of compressed sensing using Orthogonal Matching Pursuit and two traditional image reconstruction methods was conducted. The reconstructed 2D images representing the cross-section of the sensed environment were quantitatively assessed, showing promising results for robotic mapping tasks using compressed sensing.

Application of Remote Sensing in Identifying and Mapping of Exposed Rock Massifs, Potential Quarry Sites in Yaounde-Cameroon

Since 2018, Cameroon opted for an aggressive mineral exploration in order to attain the status of an emerging country by 2035. Thus, any surface and sub-surface resources found important has to be valorised. This study therefore seeks to contribute towards the drive to an emerging nation initiative through the identification and mapping of exposed rock massifs in the city of Yaounde using Remote sensing techniques. The fieldwork constituted of locating the geographic coordinates of some rock outcrops with the GPS, projecting the samples on the a geo-referenced satellite image using GIS software (ArcGIS) and simulating the spectral behaviour of those spots to those of similar reflectance in order to conclude as the targets. This was then treated in GIS software for proper mapping to be done. The study revealed that Yaounde is actually endowed with enormous exposed rock massifs which can actually be valorised for construction works. Some of the exposed rocks are surrounded by vegetation especially at the outskirts of the city, others are actually engulfed within built-up areas with difficult accessibility while others could only be exposed on excavated areas for construction. Some are already under exploitation while others are not. Some of the rock outcrops were spotted of shallow extensions while others are small in surface areas but project deep down the soil. These results are of importance for use by quarry companies and the government of Cameroon through its Ministry of mines for onward allocation of exploitation permits.

Divide and Compact — Stochastic Space Compaction for Faster-than-at-Speed Test

With shrinking feature sizes detecting small delay faults is getting more and more important. But not all small delay faults are detectable during at-speed test. By overclocking the circuit with several different test frequencies faster-than-at-speed test (FAST) is able to detect these hidden delay faults. If the clock frequency is increased, some outputs of the circuit may not have stabilized yet, and these outputs have to be considered as unknown ([Formula: see text]-values). These [Formula: see text]-values impede the test response compaction. In addition, the number and distribution of the [Formula: see text]-values vary with the clock frequency, and thus a very flexible [Formula: see text]-handling is needed for FAST. Most of the state-of-the-art solutions are not designed for these varying [Formula: see text]-profiles. Yet, the stochastic compactor by Mitra et al. can be adjusted to changing environments. It is easily programmable because it is controlled by weighted pseudo-random signals. But an optimal setup cannot be guaranteed in a FAST scenario. By partitioning the compactor into several smaller ones and a proper mapping of the scan outputs to the compactor inputs, the compactor can be better adapted to the varying [Formula: see text]-profiles. Finding the best setup can be formulated as a set partitioning problem. To solve this problem, several algorithms are presented. Experimental results show that independent from the scan chain configuration, the number of [Formula: see text]-values can be reduced significantly while the fault efficiency can be maintained. Additionally, it is shown that [Formula: see text]-reduction and fault efficiency can be adapted to user-defined goals.

An approach to building energy clusters using particle swarm optimization algorithm for allocating the tasks in computational grid

<span>The proper mapping in case of allocation of available tasks among particles is a challenging job to accomplish. It requires proper procedural approach and effectual algorithm or strategy. The deterministic polynomial time for task allocation problem is relative. The existence of proper and exact approach for allocation problem is void. However, for the survival of the grid and executing the assigned tasks, the reserved tasks need to be allocated equally among the particles of the grid space. At the same time, the applied model for task allocation must not consume unnecessary time and memory. We applied Particle Swarm Optimization (PSO) for allocating the task. Additionally, the particles will be divided into three clusters based on their energy level. Each cluster will have its own cluster header. Cluster headers will be used to search the task into space. In a single cluster, particles member will be of same energy level status such as full energy, half energy, and no energy level. As a result, the system will use the limited time for searching task for the remaining tasks in it if a particular task requires allocating half task to a particle.</span>