This study delves into the concept of the “cultural bomb” within the framework of non-military defense empowerment strategies in Indonesia. This approach can potentially change society’s views and attitudes towards various security threats as a realization of strengthening the defense and security system of the universal people (Sishankamrata) per article 30 paragraph (2) of the 1945 constitution. By leveraging media, education, and information technology, the cultural bomb acts as a social weapon that operates powerfully in the “space of mind,” shaping behavior and actions nonviolently. The issue of cultural threats pertains to the infiltration and imposition of foreign cultural values and practices that undermine local traditions and national identity, leading to social fragmentation and weakness. This study proposes the concept of a “cultural bomb” as a policy framework to address and mitigate these cultural threats. The research employs a qualitative approach using the Delphi technique, engaging experts from cultural studies and defense strategies to reach a consensus on the strategic application of the cultural bomb. The results indicate that the cultural bomb can effectively strengthen national identity and awareness of national defense by promoting local values and cultural resilience, thus enhancing societal cohesion and mitigating the impact of foreign cultural influences. The paper outlines the components of a cultural bomb, analyzes its application in international contexts, and discusses its implications in efforts to strengthen national identity and foster a sense of national defense awareness. Focusing on the “war over space of mind” ideology, it introduces “cultural hacking” as a strategic initiative to address cultural power imbalances in the post-truth era.

Breast cancer was a prevalent form of cancer worldwide. Thermography, a method for diagnosing breast cancer, involves recording the thermal patterns of the breast. This article explores the use of a convolutional neural network (CNN) algorithm to extract features from a dataset of thermographic images. Initially, the CNN network was used to extract a feature vector from the images. Subsequently, machine learning techniques can be used for image classification. This study utilizes four classification methods, namely Fully connected neural network (FCnet), support vector machine (SVM), classification linear model (CLINEAR), and KNN, to classify breast cancer from thermographic images. The accuracy rates achieved by the FCnet, SVM, CLINEAR, and k-nearest neighbors (KNN) algorithms were 94.2%, 95.0%, 95.0%, and 94.1%, respectively. Furthermore, the reliability parameters for these classifiers were computed as 92.1%, 97.5%, 96.5%, and 91.2%, while their respective sensitivities were calculated as 95.5%, 94.1%, 90.4%, and 93.2%. These findings can assist experts in developing an expert system for breast cancer diagnosis.

Carbon based materials are really an integral component of our lives and widespread research regarding their properties was conducted along this process. The addition of dopants to carbon materials, either during the production process or later on, has been actively investigated by researchers all over the world who are looking into how doping can enhance the performance of materials and how to overcome the current difficulties. This study explores synthesis methods for nitrogen-doped carbon materials, focusing on advancements in adsorption of different pollutants like CO₂ from air and organic, inorganic and ions pollutants from water, energy conversion, and storage, offering novel solutions to environmental and energy challenges. It addresses current issues with nitrogen-doped carbon materials, aiming to contribute to sustainable solutions in environmental and energy sciences. Alongside precursor types and synthesis methods, a significant relationship exists between nitrogen content percentage and adsorption capacity in nitrogen-doped activated carbon. Nitrogen content ranges from 0.64% to 11.23%, correlating with adsorption capacities from 0.05 mmol/g to 7.9 mmol/g. Moreover, an electrochemical correlation is observed between nitrogen atom increase and specific capacity in nitrogen-doped activated carbon electrodes. Higher nitrogen percentage corresponds to increased specific capacity and capacity retention. This comprehensive analysis sheds light on the potential of nitrogen-doped carbon materials and highlights their significance in addressing critical environmental and energy challenges.