There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

[신간의 별자리x] 우리/미술, 그리고 ‘슬픔의 박물관’

“Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks”の学習報告

The distributed nature and dynamic topology of Wireless Sensor Networks (WSNs) introduces very special requirements in routing protocols that should be met. The most important feature of a routing protocol, in order to be efficient for WSNs, is the energy consumption and the extension of the network's lifetime. During the recent years, many energy efficient routing protocols have been proposed for WSNs. In this paper, energy efficient routing protocols are classified into four main schemes: Network Structure, Communication Model, Topology Based and Reliable Routing. The routing protocols belonging to the first category can be further classified as flat or hierarchical. The routing protocols belonging to the second category can be further classified as Query-based or Coherent and non-coherent-based or Negotiation-based. The routing protocols belonging to the third category can be further classified as Location-based or Mobile Agent-based. The routing protocols belonging to the fourth category can be further classified as QoS-based or Multipath-based. Then, an analytical survey on energy efficient routing protocols for WSNs is provided. In this paper, the classification initially proposed by Al-Karaki, is expanded, in order to enhance all the proposed papers since 2004 and to better describe which issues/operations in each protocol illustrate/enhance the energy-efficiency issues.

Energy-Efficient Routing Protocols in Wireless Sensor Networks: A Survey

https://hal.archives-ouvertes.fr/hal-01009386/document

Energy efficiency in wireless sensor networks: A top-down survey

Climatologists attribute the warming of the Earth over the last 50 years to the increased greenhouse gases that are being expelled in the atmosphere in large part due to power production. This paper analyzes the various methods used in fossil fuel and renewable power production discussing their respective emission and efficiency rates. A closer look on solar power, specifically concentrated photovoltaic (CPV) systems, is presented. Photovoltaic efficiencies have been shown to increase from the standard 12% to 30% by using concentrators and tracking systems. A concept for sun tracking and Fresnel lens concentrator components using liquid crystal material is proposed. Using inexpensive liquid crystal material, these concepts have potential to improve PV efficiencies while maintaining a low overall system cost.

Reducing Climate Change through CPV Development

Since the introduction of the first flash memory in 1984, flash memory has been a very important member of the non-volatile semiconductor memory family due to its advantages, such as high density, low-cost, shock resistance, fast access time, low-power consumption and reliability. Despite the advantages, flash memory is still facing many technical limitations that need to be further studied. Various solutions have been developed to improve the performance of flash memory by overcoming the technical limitations; however, flash translation layer has a great impact on the overall performance improvement due to its cost-efficiency and usefulness. In this paper, three main aspects of flash memory are discussed from a perspective of flash translation layer. First, we discuss and classify flash translation layer based on the mapping method. Second, we discuss the current technical limitations that flash memory is facing and how these can be overcome by adopting flash translation layer. Third, we investigate the latest flash translation layer schemes that have been recently studied and proposed, and analyse their advantages and drawbacks.

Modern flash technologies: a flash translation layer perspective

Suppose there are n applications and n processors. A pair cover is a set S of one-to-one mappings (assignments) of the applications to the processors such that, for every pair (Ai,Aj) of applications and every pair (p,q) of processors, there is an assignment f in S that maps (Ai,Aj) to (p,q). More generally, we consider, for all k/spl ges/1, minimum size k-tuple covers. We improve bounds given earlier in by Latifi, where the application for k-tuple covers was fault tolerance of the multidimensional star network. Let F(n,k) denote the minimum cardinality k-tuple cover for n applications and processors. We give bounds for F(n,k) that are within a small multiplicative factor of optimum.

Bounding the Size of k-Tuple Covers

/pdf/machine-learning-approach-to-dissolved-gas-analysis-of-power-1u04pa0isb.pdf

Machine Learning Approach to Dissolved Gas Analysis of Power Transformers

Recent threats to public safety, such as terror attacks, mass shootings, and suicide bombings have made it very clear that law enforcement needs better tools for the protection of innocent people. The ability to identify and neutralize a target before it becomes a threat is a widely sought-after tool by law enforcement and military agencies. This paper proposes using a combination of existing technologies to identify threats prior to an incident, giving law enforcement time to deescalate or remove a threat before harm is done. Threat detection is accomplished by imaging the target area and using gait analysis to determine the emotional state of all people in the area. The gait analysis is enhanced using gait energy images in order to complete data acquisition from subjects with items that normally interfere with data acquisition. Data complexity can be reduced using techniques such as PCA, MDA, ACDA, or another reduction method. Each target is assigned a membership or classification rating in a given emotional class from collected data. The emotional classification values are then input to a neural network to determine whether the current subject matches the emotional characteristics of a perpetrator preparing to attack. Subjects who match sufficiently are flagged for further review by a human operator. This tool will help law enforcement or military agencies do more to protect the public without large additions in training or manpower.

Shahram Latifi

Papers

Reducing Climate Change through CPV Development

Modern flash technologies: a flash translation layer perspective

Bounding the Size of k-Tuple Covers

Machine Learning Approach to Dissolved Gas Analysis of Power Transformers

Threat Recognition from Gait Analysis