Metals from the ritual site of Shaitanskoye Ozero II (Sverdlovsk Oblast, Russia) [Metales del yacimiento ritual de Shaitanskoye Ozero II (provincia de Sverdlovsk Oblast, Rusia)]

The present article describes materials from the ritual site of Shaitanskoye Ozero II, Sverdlovsk Oblast. Few excavations carried out at the site measuring less than 240 sq. m in size, yielded more than 160 bronze artifacts: utensils, weapons, rolled copper ornaments, and abundant smelting and casting waste. Apart from Seima-Turbino (celts and laminar knives) and Eurasian types (daggers with cast hilts, truncated knives with guards, fluted bracelets and rings), several metal artifacts were revealed manufactured in the style of the Samus-Kizhirovo tradition. Bronze artifacts, stone knives and scrapers, and numerous arrowheads are accompanied by ceramics of the Koptyaki type. Metals use mainly a copper-tin alloy. This assemblage is shown to be relevant to the local tradition of metalworking, which, in this particular region, was comparatively ancient having been left uninterrupted by the rapid migrations of the Seima-Turbino people. In addition, the assemblage indicates the sources from which post-Seima artifacts reached the Alakul people. These artifacts may also have been linked with a large metalworking center located in the Middle Urals

Encryption Algorithms in IoT: Security vs Lifetime

IoT devices are inherently limited by their processing capabilities and power capacity. While aiming to maximise their lifespan, one of the biggest challenges they face is to reduce the computational burden, especially for tasks such as encryption, data transmission, or compression. This paper investigates the lifespan of an IoT device transmitting encrypted data as a function of the encryption algorithm used and the packet length. We focus the analysis particularly on lightweight algorithms popular in IoT ecosystems, such as AES, XTEA, HIGHT, KLEIN, ECC, PRESENT, Serpent, Piccolo, Blowfish, and Twofish. The results of the study indicate that the type of data encryption used for transmission has a significant impact on the IoT device lifetime, together with the data length and the input parameters used. To summarise, the Piccolo algorithm is the most energy-efficient, leading to maximum lifetime and low power consumption, followed by AES, XTEA, and KLEIN. At the other end of the spectrum, ECC, Blowfish, Twofish, PRESENT, and Serpent have high power consumption, hence they should be less preferred for the device-to-device or device-to-gateway IoT communication. Aside from the acknowledged energy efficiency of ciphers based on substitution-permutation operations versus Feistel ones, the results show that algorithms of first group, such as Serpent and PRESENT, require significant encryption and decryption times, while Feistel ciphers such as Piccolo, XTEA and HEIGHT are notably fast

Brainwave-based authentication using features fusion

This article investigates the use of human brainwaves for user authentication. We used data collected from 50 volunteers and leveraged the Support Vector Machine (SVM) as a classification algorithm for the case study. User recognition patterns are taken from a combination of blinking, attention concentration, and picture recognition emotion sequences. These actions impact alpha, beta, gamma, and theta brain waves, which are measured using several electrodes. Ten different electrode placement patterns are explored, with varied positioning on the head. For each placement position, four features are examined, for a total of 40 extracts in the learning model. Features are: 1) spectral information, 2) coherence, 3) mutual correlation coefficient, and 4) mutual information. Each feature type is trained by the SVM algorithm, and the 40 weak classifier candidates. Adaptive Boosting (AdaBoost), a type of machine learning, is then used to generate a robust classifier, which is subsequently used to create a model, and select features, used to accurately identify individuals for authentication purposes. Upon verifying the proposed method using 32 legitimate users and 18 intruders, we obtained an authentication error rate (ERR) of 0.52%, and a classification rate of 99.06%

Wireless Sensors for Brain Activity — A Survey

Over the last decade, the area of electroencephalography (EEG) witnessed a progressive move from high-end large measurement devices, relying on accurate construction and providing high sensitivity, to miniature hardware, more specifically wireless wearable EEG devices. While accurate, traditional EEG systems need a complex structure and long periods of application time, unwittingly causing discomfort and distress on the users. Given their size and price, aside from their lower sensitivity and narrower spectrum band(s), wearable EEG devices may be used regularly by individuals for continuous collection of user data from non-medical environments. This allows their usage for diverse, nontraditional, non-medical applications, including cognition, BCI, education, and gaming. Given the reduced need for standardization or accuracy, the area remains a rather incipient one, mostly driven by the emergence of new devices that represent the critical link of the innovation chain. In this context, the aim of this study is to provide a holistic assessment of the consumer-grade EEG devices for cognition, BCI, education, and gaming, based on the existing products, the success of their underlying technologies, as benchmarked by the undertaken studies, and their integration with current applications across the four areas. Beyond establishing a reference point, this review also provides the critical and necessary systematic guidance for non-medical EEG research and development efforts at the start of their investigation

Epitaxial lithium niobate thin films grown by chemical beam epitaxy on sapphire

Lithium Niobate (LiNbO3) is a versatile material with a number of remarkable qualities. It finds application in optical modulators because of its electro-optic properties. Nonlinearity opens its use in bio-physical applications where particles or wires of LiNbO3 can be used as highly localized optical probes. Optical frequency conversion is another possible use, as well. One of the current commercial applications of the material is in optical modulators in telecomunication devices. Nowadays bulk crystals of the material are used. However, in order to make devices more compact and affordable it is necessary to be able to produce LiNbO3 films on suitable substrates with sufficient crystalline and optical quality

Status of NSLS-II booster

The National Synchrotron Light Source II is a third generation light source under construction at Brookhaven National Laboratory. The project includes a highly optimized 3 GeV electron storage ring, linac pre-injector and full-energy booster-synchrotron. Budker Institute of Nuclear Physics builds booster for NSLS-II. The booster should accelerate the electron beam continuously and reliably from minimal 170 MeV injection energy to maximal energy of 3.15 GeV and average beam current of 20 mA. The booster shall be capable of multi-bunch and single bunch operation. This paper summarizes the status of NSLS-II booster.Национальный источник синхротронного излучения II является синхротроном третьего поколения, созданным в Брукхевенской национальной лаборатории. Проект включает: высокооптимизированное накопительное кольцо на 3 ГэВ, линейный ускоритель и бустерный синхротрон на полную энергию. Институт ядерной физики им. Г.И. Будкера создает бустер для NSLS-II. Бустер должен надежно и непрерывно ускорять пучок электронов от минимальной энергии инжекции 170 МэВ до максимальной энергии 3,15 ГэВ с током пучка 20 мА. Бустер должен быть способен работать в односгустковом и многосгустковом режимах. Эта статья суммирует состояние дел по бустеру для NSLS-II.Національне джерело синхротронного випромінювання II є синхротроном третього покоління, створеним у Брукхевенській національній лабораторії. Проект включає: високооптимізоване накопичувальне кільце на 3 ГеВ, лінійний прискорювач і бустерний синхротрон на повну енергію. Інститут ядерної фізики ім. Г.І. Будкера створює бустер для NSLS-II. Бустер повинен надійно і безперервно прискорювати пучок електронів від мінімальної енергії інжекції 170 МеВ до максимальної енергії 3,15 ГеВ зі струмом пучка 20 мА. Бустер повинен бути здатний працювати в односгустковому і багатосгустковому режимах. Ця стаття підсумовує стан справ по бустеру для NSLS-II