We explore the effect of dimensionality on the nearest neighbor problem. We show that under a broad set of conditions (much broader than independent and identically distributed dimensions), as dimensionality increases, the distance to the nearest data point approaches the distance to the farthest data point. To provide a practical perspective, we present empirical results on both real and synthetic data sets that demonstrate that this effect can occur for as few as 10-15 dimensions. These results should not be interpreted to mean that high-dimensional indexing is never meaningful; we illustrate this point by identifying some high-dimensional workloads for which this effect does not occur. However, our results do emphasize that the methodology used almost universally in the database literature to evaluate high-dimensional indexing techniques is flawed, and should be modified. In particular, most such techniques proposed in the literature are not evaluated versus simple linear scan, and are evaluated over workloads for which nearest neighbor is not meaningful. Often, even the reported experiments, when analyzed carefully, show that linear scan would outperform the techniques being proposed on the workloads studied in high (10-15) dimensionality!.

When is nearest neighbor meaningful

저작근 근전도에 관한 정상교합자와 ii급 부정교합자의 비교 연구

In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LITS) organized in conjunction with the IEEE International Symposium on Biomedical Imaging (ISBI) 2016 and International Conference On Medical Image Computing Computer Assisted Intervention (MICCAI) 2017. Twenty four valid state-of-the-art liver and liver tumor segmentation algorithms were applied to a set of 131 computed tomography (CT) volumes with different types of tumor contrast levels (hyper-/hypo-intense), abnormalities in tissues (metastasectomie) size and varying amount of lesions. The submitted algorithms have been tested on 70 undisclosed volumes. The dataset is created in collaboration with seven hospitals and research institutions and manually reviewed by independent three radiologists. We found that not a single algorithm performed best for liver and tumors. The best liver segmentation algorithm achieved a Dice score of 0.96(MICCAI) whereas for tumor segmentation the best algorithm evaluated at 0.67(ISBI) and 0.70(MICCAI). The LITS image data and manual annotations continue to be publicly available through an online evaluation system as an ongoing benchmarking resource.

The Liver Tumor Segmentation Benchmark (LiTS)

Infrared and visible image fusion based on visual saliency map and weighted least square optimization

Near Field Communication (NFC) as a promising short range wireless communication technology facilitates mobile phone usage of billions of people throughout the world that offers diverse services ranging from payment and loyalty applications to access keys for offices and houses. Eventually NFC technology integrates all such services into one single mobile phone. NFC technology has emerged lately, and consequently not much academic source is available yet. On the contrary, due to its promising business case options, there will be an increasing amount of work to be studied in the very close future. This paper presents the concept of NFC technology in a holistic approach with different perspectives, including communication essentials with standards, ecosystem and business issues, applications, and security issues. Open research areas and further recommended studies in terms of academic and business point of view are also explored and discussed at the end of each major subject's subsection. This comprehensive survey will be a valuable guide for researchers and academicians as well as for business world interested in NFC technology.

A Survey on Near Field Communication (NFC) Technology

A two-dimensional least-mean-square (TDLMS) adaptive algorithm based on the method of steepest decent is proposed and applied to noise reduction in images. The adaptive property of the TDLMS algorithm enables the filter to have an improved tracking performance in nonstationary images. The results presented show that the TDLMS algorithm can be used successfully to reduce noise in images. The algorithm complexity is 2(N*N) multiplications and the same number of additions per image sample, where N is the parameter-matrix dimension. Analysis and convergence properties of the LMS algorithm in the one-dimensional case presented by other authors is shown to be applicable to this algorithm. The algorithm can be used in a number of two-dimensional applications such as image enhancement and image data processing. >

The two-dimensional adaptive LMS (TDLMS) algorithm

Internet and networks applications are growing very fast, so the needs to protect such applications are increased. Encryption algorithms play a main role in information security systems. On the other side, those algorithms consume a significant amount of computing resources such as CPU time, memory, and battery power. This paper provides evaluation of six of the most common encryption algorithms namely: AES (Rijndael), DES, 3DES, RC2, Blowfish, and RC6. A comparison has been conducted for those encryption algorithms at different settings for each algorithm such as different sizes of data blocks, different data types, battery power consumption, different key size and finally encryption/decryption speed. Experimental results are given to demonstrate the effectiveness of each algorithm.

/pdf/evaluating-the-performance-of-symmetric-encryption-4bhgguzky5.pdf

Evaluating the Performance of Symmetric Encryption Algorithms

Trust management and reputation systems in mobile participatory sensing applications

As the importance and the value of exchanged data over the Internet or other media types are increasing, the search for the best solution to offer the necessary protection against the data thieves’ attacks. Encryption algorithms play a main role in information security systems. On the other side, those algorithms consume a significant amount of computing resources such as CPU time, memory, and battery power. But Resources in the wireless environment are limited. There is limited battery power available. Technologies such as CPU and memory are increasing and so is their need for power, but battery technology is increasing at a much slower rate, forming a “battery gap”. Because of this, battery capacity plays a major role in the usability of the devices. The increasing demand for services on wireless devices has pushed technical research into finding ways to overcome these limitations. This paper provides evaluation of six of the most common encryption algorithms namely: AES (Rijndael), DES, 3DES, RC2, Blowfish, and RC6. We examine a method for analyzing trade-offs between energy and security. We suggest approach to reduce the energy consumption of security protocols. A comparison has been conducted for those encryption algorithms at different settings for each algorithm such as different sizes of data blocks, different data types, battery power consumption, different key size and finally encryption/decryption speed.

/pdf/evaluating-the-effects-of-symmetric-cryptography-algorithms-1mp25quuqh.pdf

Evaluating the Effects of Symmetric Cryptography Algorithms on Power Consumption for Different Data Types.

This paper presents a block based digital image watermarking that is dependent on the mathematical technique of singular value decomposition (SVD). Traditional SVD watermarking already exists for watermark embedding on the image as a whole. In the proposed approach, the original image is divided into blocks, and then the watermark is embedded in the singular values (SVs) of each block separately. This segmentation process and watermarking on a block-by-block basis makes the watermark more robust to the attacks such as noise, compression, cropping and other attacks as the results reveal. Watermark detection is implemented by extracting the watermark from the SVs of the watermarked blocks. Extracting the watermark from one block at least is enough to ensure the existence of the watermark.

/pdf/an-efficient-block-by-block-svd-based-image-watermarking-1zy2fevii7.pdf

Mohiy M. Hadhoud

Papers

The two-dimensional adaptive LMS (TDLMS) algorithm

Evaluating the Performance of Symmetric Encryption Algorithms

Trust management and reputation systems in mobile participatory sensing applications

Evaluating the Effects of Symmetric Cryptography Algorithms on Power Consumption for Different Data Types.

An Efficient Block-by-Block SVD-Based Image Watermarking Scheme