Hasil untuk "Modern"

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Edward P. J. Corbett

R. Henley, A. J. Ellis

L. Brodsky

A. Nemirovski

Mark S. Granovetter

J. Petersen

C. Ruff

N. Hemming, G. Hanson

A. Gray

Oded Galor, D. Weil

Hans-Peter Lehmann, Thomas Mueller, Rasmus Pagh et al.

Given a set $S$ of $n$ keys, a perfect hash function for $S$ maps the keys in $S$ to the first $m \geq n$ integers without collisions. It may return an arbitrary result for any key not in $S$ and is called minimal if $m = n$. The most important parameters are its space consumption, construction time, and query time. Years of research now enable modern perfect hash functions to be extremely fast to query, very space-efficient, and scale to billions of keys. Different approaches give different trade-offs between these aspects. For example, the smallest constructions get within 0.1% of the space lower bound of $\log_2(e)$ bits per key. Others are particularly fast to query, requiring only one memory access. Perfect hashing has many applications, for example to avoid collision resolution in static hash tables, and is used in databases, bioinformatics, and stringology. Since the last comprehensive survey in 1997, significant progress has been made. This survey covers the latest developments and provides a starting point for getting familiar with the topic. Additionally, our extensive experimental evaluation can serve as a guide to select a perfect hash function for use in applications.

Kaleb Bacztub, Braden Vester, Matteo Hodge et al.

Wireless networks act as the backbone of modern digital connectivity, making them a primary target for cyber adversaries. Rogue Access Point attacks, specifically the Evil Twin variant, enable attackers to clone legitimate wireless network identifiers to deceive users into connecting. Once a connection is established, the adversary can intercept traffic and harvest sensitive credentials. While modern defensive architectures often employ Network Intrusion Detection Systems (NIDS) to identify malicious activity, the effectiveness of these systems against Layer 2 wireless threats remains a subject of critical inquiry. This project aimed to design a stealth-capable Rogue AP and evaluate its detectability against Suricata, an open-source NIDS/IPS. The methodology initially focused on a hardware-based deployment using Raspberry Pi platforms but transitioned to a virtualized environment due to severe system compatibility issues. Using Wifipumpkin3, the research team successfully deployed a captive portal that harvested user credentials from connected devices. However, the Suricata NIDS failed to flag the attack, highlighting a significant blind spot in traditional intrusion detection regarding wireless management frame attacks. This paper details the construction of the attack, the evasion techniques employed, and the limitations of current NIDS solutions in detecting localized wireless threats

Hannes Waclawek, Stefan Huber

This work explores an extension of machine learning-optimized piecewise polynomial approximation by incorporating energy optimization as an additional objective. Traditional closed-form solutions enable continuity and approximation targets but lack flexibility in accommodating complex optimization goals. By leveraging modern gradient descent optimizers within TensorFlow, we introduce a framework that minimizes elastic strain energy in cam profiles, leading to smoother motion. Experimental results confirm the effectiveness of this approach, demonstrating its potential to Pareto-efficiently trade approximation quality against energy consumption.

Faisol Mahmoud Adam Ibrahim, Moh Aziz Arifin

This study aims to examine the relationship between the Qur'an as a source of Islamic law and positive Indonesian law from a philosophical perspective. Specifically, this study aims to understand the position of legal values ​​in the Qur'an towards the formation of positive law, as well as to examine the philosophical implications of the differences in the normative basis of the two. This title is important to study because in the practice of the national legal system, there is often a tug-of-war between legal values ​​derived from religion and the modern legal system rooted in the secular Western tradition. Given that Indonesia is a country with a Muslim majority population, the relevance of the Qur'an in the formation of law cannot be ignored, both in terms of legal ethics, justice values, and the formation of written legal norms. This study is formulated through two main questions: (1) What is the position of the Qur'an as a source of legal values ​​in the construction of positive law in Indonesia? and (2) What are the philosophical implications of the differences in the normative basis between the Qur'an and positive law towards the formation of legislation? To answer these questions, the method used is the normative legal research method with a legal philosophy approach and a legislative approach. The main data sources consist of primary legal materials in the form of laws and regulations and interpretations of legal verses in the Qur'an, as well as secondary legal materials such as Islamic legal literature and legal philosophy theories. The results of the study indicate that the Qur'an contains universal justice values ​​that are in line with the basic principles of positive law, such as justice, welfare, and legal certainty. Although there are differences in the form and structure of law, philosophically, both can complement each other within the framework of developing a just national law. This study recommends an integrative approach in formulating positive law that is not only based on legal-formal rationality, but also considers transcendental values ​​that originate from revelation.

Danijela Nikolić, Saša Jovanović, Nebojša Jurišević et al.

In modern agriculture today, the cultivation of agricultural products cannot be imagined without greenhouses. This paper presents an energy optimization of a solar greenhouse with a photovoltaic system (PV) and a ground-source heat pump (GSHP). The PV system generates electricity, while the GSHP is used for heating and cooling. A greenhouse is designed with an Open Studio plug-in in the Google SketchUp environment, the EnergyPlus software (8.7.1 version) was used for energy simulation, and the GenOpt software (2.0.0 version) was used for optimization of the azimuth angle and PV cell efficiency. Results for different solar greenhouse orientations and different photovoltaic module efficiency are presented in the paper. The obtained optimal azimuth angle of the solar greenhouse was −8°. With the installation of a PV array with higher module efficiency (20–24%), it is possible to achieve annual energy savings of 6.87–101.77%. Also, with the PV module efficiency of 23.94%, a concept of zero-net-energy solar greenhouses (ZNEG) is achieved at optimal azimuth and slope angle. Through the environmental analysis of different greenhouses, CO₂ emissions of PV and GSHP are calculated and compared with electricity usage. Saved CO₂ emission for a zero-net-energy greenhouse is 6626 kg CO₂/year. An economic analysis of installed renewable energy systems was carried out: with the total investment of 19,326 € for ZNEG, the payback period is 8.63 years.

Olga S. Matorina, Nadezhda M. Illarionova, Svetlana V. Nesterova

The article considers the formation features of cumulative stress and psychological burnout among employees of fire divisions of EMERCOM of Russia. The analysis of risk factors affecting the mental state of personnel, including occupational loads, working conditions and socio-psychological characteristics, is presented. Statistical data reflecting the prevalence of stress disorders among firefighters are presented. There are outlined the following modern approaches to the prevention of cumulative stress: organizational, psychological and medical measures. There is a need to introduce systemic programs of psycho-prophylaxis and psycho-rehabilitation in the activities of fire and rescue units.

Hao-Hsiang Ku, Shih-Cheng Yang, Huai-An Hsiao et al.

In recent years, due to the rapid pace of urbanization and increasingly hectic modern lifestyles that leave little time for home cooking, more and more people prefer to dine at food stands, restaurants, or supermarkets due to convenience. This type of people are often called the eating-out population. The general public may have a concept that most of the food items consumed by people eating out are first prepared for storage by vendors and are likely to contain more food preservatives. Excessive exposure to benzoic acid (BA), sorbic acid (SA), and dehydroacetic acid (DHA), which account for the highest number of violations of the amount of preservatives permitted in food, may cause potential human health risk. The purpose of this study was to investigate the human health risks of consuming preservatives used in food among for Taiwanese people who eat out. We applied the total diet study (TDS) method to analyze the concentrations of BA, SA, and DHA in the food items frequently consumed when people dine outside. The hazard index in percent acceptable daily intake (%ADI) of BA and SA for four exposure groups classified by age were calculated. In high-intake consumers, the highest hazard index of BA was 2.5%ADI for the 6–9 years old age group of the eating-out population, which still fell within the acceptable risk range. In addition, the risk appeared to be decreasing year-on-year, which may be related to year-on-year improvements of the way food products are processed in the food industry.

L. Bromham, D. Penny

Korbinian Pöppel, Maximilian Beck, Sepp Hochreiter

While Transformers and other sequence-parallelizable neural network architectures seem like the current state of the art in sequence modeling, they specifically lack state-tracking capabilities. These are important for time-series tasks and logical reasoning. Traditional RNNs like LSTMs and GRUs, as well as modern variants like sLSTM do have these capabilities at the cost of strictly sequential processing. While this is often seen as a strong limitation, we show how fast these networks can get with our hardware-optimization FlashRNN in Triton and CUDA, optimizing kernels to the register level on modern GPUs. We extend traditional RNNs with a parallelization variant that processes multiple RNNs of smaller hidden state in parallel, similar to the head-wise processing in Transformers. To enable flexibility on different GPU variants, we introduce a new optimization framework for hardware-internal cache sizes, memory and compute handling. It models the hardware in a setting using polyhedral-like constraints, including the notion of divisibility. This speeds up the solution process in our ConstrINT library for general integer constraint satisfaction problems (integer CSPs). We show that our kernels can achieve 50x speed-ups over a vanilla PyTorch implementation and allow 40x larger hidden sizes compared to our Triton implementation. Our open-source kernels and the optimization library are released here to boost research in the direction of state-tracking enabled RNNs and sequence modeling: https://github.com/NX-AI/flashrnn