Attack Type Agnostic Perceptual Enhancement of Adversarial Images

Adversarial images are samples that are intentionally modified to deceive machine learning systems. They are widely used in applications such as CAPTHAs to help distinguish legitimate human users from bots. However, the noise introduced during the adversarial image generation process degrades the perceptual quality and introduces artificial colours; making it also difficult for humans to classify images and recognise objects. In this letter, we propose a method to enhance the perceptual quality of these adversarial images. The proposed method is attack type agnostic and could be used in association with the existing attacks in the literature. Our experiments show that the generated adversarial images have lower Euclidean distance values while maintaining the same adversarial attack performance. Distances are reduced by 5.88% to 41.27% with an average reduction of 22% over the different attack and network types

Military Expenditure and Economic Growth Literature: A Meta-Analysis

This paper surveys the literature on military expenditure and economic growth us- ing a meta-analysis technique. There exists a vast empirical literature that examines the impact of military expenditure on economic growth. The outcomes of these studies have yielded controversial results. Therefore, a meta-analysis is conducted to review 25 empirical studies with 140 estimations. The result indicates that the net combined effect of military expenditure on economic growth is positive but the magnitude is very small.military expenditure, economic growth, meta analysis

Military Expenditure and Economic Growth: A Meta-Analysis

Meta analysis is conducted to review 32 empirical studies with 169 estimates to find the combined overall effect of military expenditure on economic growth. Using a meta fixed and random effects and regression analysis, our results show that there exists a "genuine" net effect of military expenditure on economic growth. The net combined effect is positive, and the magnitude is very small. The main sources of study-to-study variation in the findings of military expenditure and economic growth literature are attributable to the sample, time periods, and functional forms.military expenditure, economic growth, meta analysis

Conflict, Growth and Welfare: Can Increasing Property Rights Really be Counterproductive?

Gonzalez (2007), JET, 137(1), 127-139, sets out a growth model with con- flict in which households allocate their resources across consumption, and investment in both productive and unproductive capital. A striking result is obtained: there are circumstances where increasing property rights in society can actually reduce social welfare and hence incremental changes are not nec- essarily in peoples’ interests. This note reassesses this claim in a generalized form of his model with a CRRA utility function (with a risk aversion param- eter, sigma > 1 rather than his logarithmic form) and we assume a less than full depreciation of capital. Both these generalizations prove to be critical ones that significantly change the result.Conflict, growth, property rights, welfare.

LightChain: A DHT-based Blockchain for Resource Constrained Environments

As an append-only distributed database, blockchain is utilized in a vast variety of applications including the cryptocurrency and Internet-of-Things (IoT). The existing blockchain solutions have downsides in communication and storage efficiency, convergence to centralization, and consistency problems. In this paper, we propose LightChain, which is the first blockchain architecture that operates over a Distributed Hash Table (DHT) of participating peers. LightChain is a permissionless blockchain that provides addressable blocks and transactions within the network, which makes them efficiently accessible by all the peers. Each block and transaction is replicated within the DHT of peers and is retrieved in an on-demand manner. Hence, peers in LightChain are not required to retrieve or keep the entire blockchain. LightChain is fair as all of the participating peers have a uniform chance of being involved in the consensus regardless of their influence such as hashing power or stake. LightChain provides a deterministic fork-resolving strategy as well as a blacklisting mechanism, and it is secure against colluding adversarial peers attacking the availability and integrity of the system. We provide mathematical analysis and experimental results on scenarios involving 10K nodes to demonstrate the security and fairness of LightChain. As we experimentally show in this paper, compared to the mainstream blockchains like Bitcoin and Ethereum, LightChain requires around 66 times less per node storage, and is around 380 times faster on bootstrapping a new node to the system, while each LightChain node is rewarded equally likely for participating in the protocol

The Effects of JPEG and JPEG2000 Compression on Attacks using Adversarial Examples

Adversarial examples are known to have a negative effect on the performance of classifiers which have otherwise good performance on undisturbed images. These examples are generated by adding non-random noise to the testing samples in order to make classifier misclassify the given data. Adversarial attacks use these intentionally generated examples and they pose a security risk to the machine learning based systems. To be immune to such attacks, it is desirable to have a pre-processing mechanism which removes these effects causing misclassification while keeping the content of the image. JPEG and JPEG2000 are well-known image compression techniques which suppress the high-frequency content taking the human visual system into account. JPEG has been also shown to be an effective method for reducing adversarial noise. In this paper, we propose applying JPEG2000 compression as an alternative and systematically compare the classification performance of adversarial images compressed using JPEG and JPEG2000 at different target PSNR values and maximum compression levels. Our experiments show that JPEG2000 is more effective in reducing adversarial noise as it allows higher compression rates with less distortion and it does not introduce blocking artifacts

Samih Rifat, yeni yapıtında Osmanlı öncesi İstanbulu'ndan şiirler sunuyor:Aynı gün batımının ozanları

Taha Toros Arşivi, Dosya No: 135-Oktay Rifat-Samih HorozcuUnutma İstanbul projesi İstanbul Kalkınma Ajansı'nın 2016 yılı "Yenilikçi ve Yaratıcı İstanbul Mali Destek Programı" kapsamında desteklenmiştir. Proje No: TR10/16/YNY/010

Investigation of Bias-assisted photoenhanced electrochemical etching for fabrication of self-alihned gallium nitride based bipolar transistors

Cataloged from PDF version of article.GaN-based bipolar transistors are good candidates for applications in RF power amplifiers. In contrast to more common AlGaN/GaN high electron mobility transistors (HEMTs), GaN based bipolar transistors have not drawn much attention because of the difficulties in good p-type material and ohmic contact. Most of the problems associated with p-type quality and contact come from growth and etch damage during fabrication. In this work, a low damage etching technique with an undercut profile was developed to solve the problems associated with p-type ohmic contact quality and to realize the self-aligned GaN bipolar transistor fabrication. The etching process consists of bias-assisted photoenhanced electrochemical oxidation of GaN in deionized water (BPECO/DI) and its subsequent etching in diluted acid solution. By this technique, we demonstrated good Schottky contacts on samples etched more than 100 nm and p/n doping selective etching was shown. Furthermore the most critical point for self-aligned fabrication is undercut profile and it was also obtained by BPECO/DI etching. Hence this technique is ideal for fabrication of self-aligned bipolar transistors. There are some problems during fabrication of self-aligned bipolar transistor. First, due to the impossibility of activation annealing after emitter etch, activation annealing had to be done at the beginning where emitter layer is on the base and this was a problem for Mg activation. More importantly, there were still uncertainties with BPECO/DI etching like roughening up the etched surface, low etch rate for npn structures and disturbing the material uniformity near the surface. In this work, it was shown that BPECO/DI etching is a very efficient tool that provided low damage etching of GaN and enabled the self aligned RF bipolar transistor structures. It was found that self aligned base-emitter junctions were successfully formed and the BPECO/DI etching was almost stopped at top of the base layer. Self-aligned bipolar transistors were fabricated and their base-emitter and base-collector junctions were measured. The results obtained in this work demonstrated that BPECO/DI etching can bring solutions to the lack of low damage etching and the impossibility of self-aligned base contact in fabrication of today’s GaN based bipolar transistors.Alptekin, EmreM.S

Estimating market share of white goods sector in Turkey with analytic network process

Bu çalışmada, analitik ağ süreci kullanılarak Türkiye’deki beyaz eşya sektöründe yer alan üç büyük firmanın pazar payları tahmin edilmeye çalışılmıştır. Bu firmalar beyaz eşya sektöründe son derece rekabetçi firmalardır. Yeni müşteriler çekmek ve piyasada kendi başlarına tutunmak için, makul fiyatlar belirleyerek, kaliteli ürünler üreterek ve servis ağlarını genişleterek rekabet etmek zorundadırlar. Analitik ağ sürecine uygun olarak ilk önce, pazar payı tahmin problemi yapılandırılmış ve modellenmiştir. Bir sonraki adımda, pazar payını etkileyen faktörlerin önemi belirlenmiş ve Türkiye’deki beyaz eşya firmalarının pazar payları analitik ağ süreci kullanılarak tahmin edilmiştir. Karar modelinin geçerliliği için, tahmin edilen pazar payı değerleri gerçekleşen değerlerle karşılaştırılmıştır.In this paper, it is tried to predict the market shares of the largest three companies in the white goods sector in Turkey through the use of the analytic network process. These companies are highly competitive in the white goods sector. To attract new customers and to retain the current ones, they have to compete by setting reasonable prices, produce high quality products and expand their service networks. In line with the sequence of analytic network process, first of all, an estimation of market share problem has been structured and modeled. Next, it is assessed the importance of the factors affected the market share and it is estimated the market shares of the white goods companies in Turkey using analytic network process. The estimated market share values have been compared with actual ones for the validation of the decision model