The development of Software Defined Networking (SDN) has altered the landscape of computer networking in recent years. Its scalable architecture has become a blueprint for the design of several advanced future networks. To achieve improve and efficient monitoring, control and management capabilities of the network, software defined networks differentiate or decouple the control logic from the data forwarding plane. As a result of this, logical control is solely centralized in the controller. Due to the centralized nature, SDNs are exposed to several vulnerabilities such as Spoofing, Flooding, and primarily Denial of Service (DoS) and Distributed Denial of Service (DDoS) among other attacks. In effect, the performance of SDN degrades based on these attacks. This paper presents a comprehensive review of several DoS and DDoS defense/mitigation strategies and classifies them into distinct classes with regards to the methodologies employed. Furthermore, based on the discussions raised, suggestions have been made to enhance current mitigation strategies accordingly.

Limestone mining for cement plants uses a blasting method to break the material. Blasting production is considered successful when it can achieve production targets based on tonnage of uncovered rock, efficient use of explosives, grain size or rock fragmentation, and environmental impact. This research aims to analyze the blasting geometry on the production results at the research location by knowing the initial design, the actual blasting geometry, and the geometry recommendation using the C.J. Konya method. In addition, researchers also know the explosives used, the production results in the form of material fractionation using the Kuz-Ram method, and the tonnage of uncovered rocks. The initial design with a burden of 3.4 m, spacing of 3.4 m, hole depth of 5.9 m, and ANFO explosives per hole of 33 kg produced 147.31 tonnages. The actual geometry with a burden of 1.7 m, spacing of 3.5 m, hole depth of 6.0 m, and ANFO explosives per hole of 26.73 kg produced a 77.11 tonnage. The actual geometry resulted in a blasting production of 6,941 tonnes per day, which did not meet the company's production target of 10,639. The fragmentation calculation results obtained an average size in the field of 15.29 cm, which meets the required screening or sieve criteria of 0.80 - 1.00 m. The size of the fragments also follows the sieve calculation using the Kuz-Ram method, with a 100 cm sieve passing only 0.01 %. Based on this, the company is recommended to make geometry changes to achieve the production tonnage target that has been set.

Indonesia is a country with diverse cultures. Indonesia comprises numerous tribes, including Batak Toba. The Batak Toba people actively practice their traditional rituals, including wedding ceremonies. Their traditional wedding ceremony involves several rituals, symbols, and attributes with different meanings. Today, learning resources for traditional rituals, attributes, and others can be accessed through experts’ knowledge, video tutorials, and scientific journal. However, all sources have failed to attract attention. Thus, only a few generations are concerned and interested in studying culture. And threatens the dissappear of cultural experts. The research objective is to develop a system based on a multimedia approach that provides learning materials about the traditional rituals of the Batak Toba wedding ceremony. The multimedia development life cycle method is used for system development. Based on the research result show that 90% responded easier to understand the content.

This article outlines the creation and application of a technologically improved robot designed to amplify the precision and effectiveness of ring retrieval and projection tasks in the ABU Robocon Indonesia Robot Challenge. The ABU Robocon competition is an annual event that tasks teams with crafting robots capable of accomplishing specific assignments under a predetermined time limit. The ring retrieval and projection task, historically known for its precision requirements, has proven to be quite demanding. Our strategy entailed the incorporation of cutting-edge technologies into the robot's design, encompassing computer vision and machine learning algorithms, to augment its accuracy and performance. We equipped the robot with cameras and sensors for the detection and analysis of ring positions and orientations. Real-time decisions regarding the optimal approach for retrieving and accurately projecting the rings were made using machine learning models that had undergone training. The outcomes of our experiments reveal a marked enhancement in the robot's performance when compared to conventional methods. The tech-enhanced robot consistently exhibited a heightened success rate when performing ring retrieval and projection tasks. This development not only boosts the competitiveness of our robot in the ABU Robocon competition but also underscores the potential of advanced technologies in enhancing the performance of robotics systems when confronted with intricate tasks.

The pendulum-spring system studied using Hamilton equations consists of three generalized coordinates. The coordinates are the swing angle of the rod, the swing angle of the spring, and the length extension. In this case, the total Hamiltonian is complicated because of the complicated mechanical system. Six equations of motion are obtained from the Hamilton equations. The visualization of the generalized coordinates with respect to time is illustrated. In the visualization, the spring constant and the initial swing angle of the rod were varied. These variations obtained the harmonic and non-harmonic motion. The motion of such a complex system was usually sensitive to the initial values. Solving the mechanical problems with Hamiltonian formalism could familiarize students with a branch of physics with numerous indispensable applications to other branches.

Bio-briquettes from a mixture of coconut leaves charcoal and cassava peel charcoal have been produced and characterized in this study. The analysis carried out included density, burning rate, water content, ash content, and calorific value. Bio-briquette samples were produced with composition variations between coconut leaves charcoal and cassava peel charcoal with mass percentage ratios of 100:0, 75:25, 50:50, 25:75 and 0:100. The mixture used to produce briquettes with a ratio of tapioca flour, water and charcoal as raw materials is 1.5:1.5:2. The results of the study show that the density and calorific value of bio-briquettes increases with the increase in the amount of cassava peel in the briquette content. The optimum bio-briquette product from this research was found in variations of coconut leaves and cassava peel with a ratio of 75:25. The density is 0.96 g/ml, the burning rate is 0.190 g/min, the water content is 3%, the ash content is 18.81%, and the calorific value is 3521.47 Cal/g.

The national flags are among the symbolic representations of a country. They make us understand the country of interest in a particular issue. Therefore, they are commonly used in both private and government organizations. It has been discovered in recent times that the younger generation mostly and idly spend its time online; hence, knowing little about national flags. Additionally, some national flags (particularly in West Africa) are identical in nature. The likeness is in terms of layout, colours, shapes and objects on the national flags. Hence, there is a need to have a model for flag recognition. In this paper, national flag images of some West African countries were gathered to form a dataset. After this, the images were preprocessed by cropping out the irrelevant parts of the images. VGG-16 was used to extract necessary features and to develop the deep learning model. This contrasted with the existing handcrafted feature extraction and traditional machine learning techniques used on this subject matter. It was observed from this study that the proposed approach performed excellently well in predicting national flags; with an Accuracy of 98.20%, and an F1 score of 98.16%. In the future, it would be interesting to incorporate the national flag recognition into Human-Computer Interaction System. For instance, it could be used as flag recognition in some mobile and web applications for individuals with colour blindness. This research work presents a robust model because of nature of the dataset used in this work compared to previous works.

Agriculture is a vital sector for a nation's livelihood. However, in the near future, the agricultural sector faces various challenges, particularly related to environmental and cultural issues. In this era of digital transformation, technology plays a crucial role in the agricultural field. Research is conducted to control the quality of nutrition and water intake for hydroponic plants to ensure their healthy and high-quality growth. The controlled parameters for nutrition include pH and nutrient solution availability, while water intake involves temperature, acidity (pH), electrical conductivity, and nutrient dosage. These parameters are detected by pH sensors, temperature sensors, EC (electric conductivity) sensors, and controlled by microcontrollers. The sensor detection results control the pump operation, ensuring a continuous and quality water intake rate. The growth of Brazilian spinach plants under study is observed with water pH controlled at 6.5 – 7 and nutrient electrical conductivity at 2 – 2.1 ms/cm. Test results demonstrate that the growth of plants in the research growth medium and the comparison growth medium significantly improves, even though the growth is not uniform across all plants. Plants in the research growth medium exhibit significantly better growth compared to those in the comparison growth medium.

An earthquake is a sudden disaster that is not possible to predict. This impulsive behavior makes it very dangerous for humankind. Precautionary measures are immense for reducing damage. The first step of preventive measures for an earthquake is raising awareness. Dhaka City has a high earthquake risk due to its large population and urbanization. Researchers have said that an earthquake in this zone can be fatal, resulting in heavy casualties with structural damage. For this reason, proper awareness is essential for the residents of this area. The aim of this study is to find out the current knowledge level of the residents of Dhaka City about Earthquake risk of this city. Online questionnaire was used to collect data from random residents of Dhaka. Survey data indicates that many people lack Knowledge of what to do before and during an earthquake. Especially school and college-going students are unaware of the essential things to do during an earthquake incident. Many people still don’t know the importance of a seismic-resistant building system and are unprepared for a seismic event. This study brings these aspects together to learn about the knowledge level, which can help policymakers raise awareness among this city's residents.

Resources have economic value, form, quality, quantity, grade, geological characteristics, and certain sustainability to be extracted economically. Mineral resources decrease based on the level of geological confidence in the Inferred, Indicated, and Measured categories. This study uses the Ordinary Kriging geostatistical method to assess the potential of nickel laterite resources and the distribution of nickel mineralization levels in the study area. The research methodology was inspired by statistical and geostatistical analysis, starting with univariant statistical analysis, spatial statistics, bivariant statistics, and resource estimation. For later use in determining the distribution of mineralization grades and classifying nickel laterite resources using the Relative Kriging Standard Deviation (RKSD) calculation. This method estimates nickel content in a block whose grade value is unknown. The results of statistical calculations using Ordinary kriging obtained an average grade value of 2.90% Ni. Mineralization data for nickel content in limonite layers with Ni content of 0.5 – 1.3% and saprolite layers with Cut of Grade (COG) Ni, > 1.4 – 3.1% Ni in limonite and saprolite layers are projected in the block model. The estimated tonnage of nickel resources using the OK method is 670,837.83 tonnes. Laterite nickel resource classification results RKSD calculation are classified into measured resources (Measured).