Volume 29, Issue 4

Internet was designed to provide source to destination communication and it had shown good resilience over the time. In today’s world, evolution of content-centric applications has led to failure of internet as it was designed to interact over a pre-established communication channel. Named Data Networking (NDN) came up as a solution to this which works with content specific requests and returns the contents to its requester regardless of its location. It uses different data structures where it stores information about various content and perform a search among these when a request encounters. As the requests and content size increases it leads to increase in complexity of query as well as memory consumption. So main challenge is to find the solution to efficiently store, query and retrieve large number of entries related to content names in real time interactions, Probabilistic Data Structures (PDS) came up as the solution for this as they are suitable for large data processing, approximate predications, fast retrieval and storing unstructured data, thus improving space and search complexity in Big data processing. Bloom filter is a PDS which is used for approximate membership query. Many variants of BF have been already successfully employed in various domains in NDN like, scalable forwarding and routing, caching and security. In this paper, we try to discuss the study of applications of BF in different NDN domains in depth. We conclude our survey by identifying a set of open challenges in NDN which should be addressed by using PDS.

In this day and age there are mechanisms or mediums to pass messages for advertisers and this include traditional print media, online advertisement campaign, electronic media such as television and radio etc. However, a very critical feature a whether an advertisement is successful or not depends on the realms of understanding between the source and the receiver. This paper has examined the importance of realm of understanding in a communication model by analyzing Dove’s phenomenally successful online advertisement campaign titled Dove Real Beauty Sketches.

Corruption is a cankerworm that has eaten deep into almost every system in Nigeria. It is a crime with such a despicable viral effect and disastrous tendency like a terror bomb. Though it is more of an executive crime but no well-meaning government handles corruption with levity because the extremity of its ugly tentacles is capable of obstructing good governance. Therefore, the system has to be sanitized to make the process hitch free for strategic developmental adventure. One of the major challenges in the fight against corruption is detecting and exposing corruption. The whistle blowing therefore becomes a veritable means to fight this cancerous crime. Against this backdrop, this paper seeks to examine where is the whistle blowing policy in Nigeria? An anti-corruption strategy Based on the gaps in literature, this paper recommends among others a performance review system that is tied to rewarding whistle blowing; ways to protect whistle-blowers and the need to strengthen organizational support structures for whistleblowing.

A honey pot is a technique of cloud computing that is proposed for capturing hackers or tracking unusual methods of attack. This technique will seize, recognize and duplicate the hacker behavior. It works in a Cloud environment where anything like technology, tool, and the result can be offered as a service. Purveyors offer and deliver such services to their customers via the network. This paper presents the concept of a high-interaction honeypot, Kerberos authentication system as a service in a cloud environment to implement the benefits of, such service to ably distinguish between hackers and users and to provide overall security to the data/network.

To assess the potential impacts on seabirds, turtles and marine mammals from oil and gas production from the oceanic Pre-Salt province at Brazil’s Santos Basin, the Brazilian environmental agency (IBAMA) required PETROBRAS, the main oil company in the basin, to implement the “Programa de Monitoramento de Praias da Bacia de Santos” (Santos Basin Beach Monitoring Program – PMP-BS). Since 2015 PMP-BS has been operating along the states of Santa Catarina, Paraná, São Paulo and Rio de Janeiro, to collect biological data from live and dead stranded animals. This dataset comprises the first three years of monitoring (September 2015 to August 2018) along the southern Santa Catarina state coastline, from 28°8’37.558” S 48°38’42.367” W and 28°29’48.831” S 48°45’41.561” W. During this period, 3291 animals of 46 species were recorded, 88.61% of which were dead and 11.39% alive when first observed. This dataset represents the first high-intensity monitoring effort in the area and is essential to establish baselines for future work that seek to better understand the impacts of human activities on marine ecosystems.

In a recent article the authors describe the origin of gamma radiation or low energy gamma rays up to 10 MeV (Millions of electron Volt). A type of high frequency electromagnetic radiation usually produced by radioactive elements and electrical discharges present in the environment where we live. The intensity of this radiation may vary with each location on the planet. Measurements of gamma radiation from 200 keV to 10.0 MeV were taken at the campus of the Technological Institute of Aeronautics – ITA – in São José dos Campos, SP, Brazil. The detector set plus the associated electronics was previously calibrated in the laboratory using the radioactive sources of Cesium – (Cs-137), Polonium- (Po-210) and Strontium- (Sr-90). These sources provide gamma ray energies at (0.662 keV, 1.17 MeV), alpha particles at 5.4 MeV and electrons at 0.90 keV, respectively. The detector consists of a height-by diameter (3x 3) inches, Thallium Activated Sodium Iodide [NaI (Tl)] scintillator, associated with a photomultiplier (PM) and associated electronics and data acquisition. Measurements were taken within 10 minutes, in the environment, with each radioactive source and with all radioactive sources placed on the scintillator. The generation of the spectra as a function of energy is always studied at the same time interval. It was thus possible to determine for this location the presence of natural gamma radiation present at the ground-air interface for this energy range using a minimum measurement time interval of 10 minutes.

Traffic accidents are a global problem, therefore an approach method is needed to reduce accident rates by identifying and analyzing the causes. This research was conducted on the urban road in Paringin City through a media questionnaire by asking the opinion of the community as road users to participate in providing input on the factors that cause traffic accidents. There are four causative factors and twenty nine indicators are used as research variables and the data is processed by Partial Least Square (PLS) analysis. The results of the study are derived from the human factor (the driver) who are fatigue is the dominant cause of traffic accidents, other causes are lack of concentration, lack of discipline, lack of anticipation, and high speed. In vehicle factors, it was found that tire damage was the dominant cause of traffic accidents, other causes were over dimension and over load (ODOL), damage to the steering system, slippage, untreated vehicle spare parts, damage to the light system and the age of the vehicle is too old. On the road factor, it was found that the road / slope geometry was the dominant cause of traffic accidents, other causes were road damage, lack of road facilities, misuse of road functions and road pavement conditions. In environmental factors it was found that flooding was the dominant cause of traffic accidents, other causes were side obstacles and densely populated.

Well-designed artificial miRNAs (amiRNAs) are as effective as short hairpin RNAs (shRNAs) but produce 10–80 times less siRNA. They enable long-term silencing and are safer than other RNAi triggers. They are suitable instruments for gene therapy techniques, especially for incurable monogenic diseases. In clinical studies, stereotactic injection of AAV5 directly into the striatum is the most effective approach. Intravenous injections would not only make patients more comfortable, but would also reduce the cost of complex brain surgery.In terms of structure, biogenesis, and expression levels, Ami RNAs are more “natural” than other gene therapy methods. They also utilise the cell’s native protein machinery and do not produce irreversible alterations, unlike genome editing technologies. The amount of time spent on a technology determines its level of progression. ASOs have an edge in this regard, as seen by the number of authorized medicines. Perhaps RNAi is just around the corne

Deep learning has become a cornerstone of artificial intelligence (AI), driving advances in areas like computer vision, natural language processing, and autonomous systems. However, as these models become more powerful, the need for safety and security becomes paramount. This paper explores the architectural innovations in deep learning aimed at ensuring the safe and secure deployment of AI systems. It reviews the latest developments in adversarial training, robust optimization, and model interpretability to counteract vulnerabilities such as adversarial attacks and data poisoning. Adversarial training techniques, which involve training models to withstand crafted input manipulations, play a crucial role in improving the resilience of deep learning models. Additionally, the paper delves into privacy-preserving techniques such as federated learning and differential privacy, which allow models to learn from distributed data sources without compromising sensitive information. It also evaluates the role of explainable AI (XAI) methods in making deep learning models more transparent, thereby enhancing trust among users and stakeholders. This study is based on a systematic review of recent research findings and real-world applications, offering insights into how deep learning architectures can be optimized for both safety and security. The aim is to provide a roadmap for researchers and practitioners looking to build more robust AI systems. Ultimately, the paper underscores the importance of balancing performance with safety and security in the design of future deep learning models, ensuring they can be deployed reliably in critical environments.