Intelligent early warning method based on drone inspection

Commonly used UAV emergency inspection methods are executed by the instructions of the ground command center. The response rate depends on the stability of the communication network and the rapid response ability of the commander. The critical time window is fleeting, which is likely to cause unnecessary loss. Crisis rapid response capability has become the key to measuring system capabilities. In order to improve the system’s rapid response capability, a method of deploying decision-making agents on airborne computers and ground early warning systems is proposed. This early warning method uses key technologies such as multi-network integration, situation assessment, neural network architecture, deep learning, reinforcement learning, and intelligent cognitive reasoning to effectively ensure the effectiveness of crisis warning. The early warning method of the early warning system is as follows: the mission computer uniformly collects the flight control status parameters, the load status parameters and the load real-time data form a composite information flow. The task computer adopts the methods of protocol conversion, data classification, and danger recognition to the compound information flow to identify the crisis information and make a preliminary analysis and judgment of the crisis state. If it is determined that it is necessary to track the target in real time, the initial task assignment and parameter adjustment of the load are carried out, and the continuous tracking of the task target is carried out to realize the rapid response to the crisis on the edge side. At the same time, the composite data are downloaded to the command center. The command center performs the secondary crisis analysis and risk level determination and outputs the crisis plan deduced by the agent to realize the strategy assistance. The accuser refers to the plan strategy and issues instructions to the task computer, and the task computer receives it. Instruction and secondary adjustment and optimization of the load parameters. If there is a flight route adjustment instruction, the adjustment route will be sent to the flight controller, which greatly improves the flexibility and efficiency of handling the crisis in the UAV inspection process. By adopting this set of early warning methods, it can provide users with an updated, faster and more efficient way to realize the early warning requirements in drone inspections, which is a new breakthrough in the field of drone command methods.

Penerapan Na ̈ıve Bayes Classifier, K-Nearest Neighbor (KNN) dan Decision Tree untuk Menganalisis Sentimen pada Interaksi Netizen danPemeritah

Pemerintah Pekanbaru saat ini sudah menerapkan teknologi dalam sistem pemerintahan, penerapannya saat ini masih mendapat keluhan dari masyarakat seperti layanan publik command center yang hanya sebagian masyarakat mengetahuinya dan penerapan cctv yang ada di Alat Pemberi Isyarat Lalu Lintas (APILL) yang belum berfungsi dengan baik. Penerapan teknologi lainnya oleh Pemerintah Pekanbaru dapat kita lihat dari keberadaan portal-portal web situs resmi Pemerintah. Sedangkan untuk melihat beragam komentar netizen dari twitter. Twitter menjadi tempat untuk mendapatkan data yang diungkapkan masyarakat melalui tweets yang diposting ke timeline. Analisa sentimen dilakukan untuk melihat pendapat atau kecenderungan opini netizen terhadap pemerintah Pekanbaru yang mengandung sentimen positif, negatif, dan netral. Data yang digunakan adalah tweet dengan jumlah dataset sebanyak 150 tweets. Data tersebut kemudian di analisa agar menjadi informasi. Analisa dilakukan menggunakan metode data mining yaitu Naïve Bayes Classifier, K-Nearest Neighbor (KNN), dan Decision tree. Penggunaan ketiga pendekatan ini berupaya untuk mengkategorikan hasil komentar netizen terkait penggunaan teknologi yang telah melalui proses analisis sentimen dan membandingkan keakuratan ketiga cara tersebut. Hasil akurasi yang didapatkan cukup beragam yaitu dari metode Naïve Bayes akurasi 100%, metode KKN akurasi 98,25%, dan metode decision tree akurasi 62,28%.

Strengthening communities’ disaster resilience during COVID-19 time: A case of Muhammadiyah in Indonesia

Since the early of March 2020, COVID-19 pandemic which broke out in Indonesia, had a significant impact on various aspects of life. The pandemic not only has pushed the government to take a strategic decision but also has forced the communities to accommodate this condition immediately. Muhammadiyah is one of Indonesia’s largest religious organizations has played its role to overcome COVID-19 pandemic alongside with the government. This study aims to determine the contribution of Muhammadiyah to tackle the pandemic by strengthening the disaster resilience community. The study uses a qualitative approach and a descriptive method. The primary data were obtained by in-depth interviews with Muhammadiyah organization leaders and several working teams handling the pandemic. Literature study was conducted as the secondary data. To tackle the pandemic by strengthening communities’ disaster resilience, Muhammadiyah carried out several programs, including (1) strengthening da’wah networks massively to enhance the community awareness about COVID-19 pandemic, (2) establishing several working teams handling the pandemic to enhance disaster resilience communities, including Muhammadiyah COVID-19 Command Center (MCCC), Muhammadiyah Disaster Management Center (MDMC), and philanthropic body of Muhammadiyah (LazisMu), and (3) Muhammadiyah engagement with stakeholders and development agency, such as the collaboration with the Ministry of Health, BNPB, DFAT and USAID to COVID-19 preventive and curative action.

Ijtihad Kemanusiaan MDMC dalam Menghadapi Pandemi Covid-19 di Indonesia

This study was conducted to determine the sociological impact of MDMC's humanitarian ijtihad in dealing with the Covid-19 pandemic in Indonesia. This research is qualitative by using a phenomenological study of the phenomenon under study, namely by expressing problems, presenting data, analyzing data, and obtaining data through observation either through literature study or directly. The results of this study indicate that MDMC's social care, and solidarity are marked by the establishment of the Muhammadiyah Covid-19 Command Center (MCCC) to fight the Covid-19 pandemic both medically, and outside the medical realm. Muhammadiyah as a religiosity-based community organization takes on a responsible role in responding to the reality of the Covid-19 pandemic with several steps, namely: revitalizing theological rituals, canceling the association's strategic agenda, and engineering learning techniques. These steps are MDMC's humanitarian ijtihad transformed in the face of the Covid-19 pandemic in Indonesia.

UAV-Based Collaborative Electronic Reconnaissance Network for 6G

In unmanned aerial vehicle (UAV) collaborative electronic reconnaissance network, single UAV is always restricted by flyability and sensing capacity; hence, a cooperative network is built to realize the electronic reconnaissance. In this paper, a three-level electronic reconnaissance network is proposed, including the radiation target, UAV-based electronic reconnaissance equipment, and the command center. Each of the UAVs is capable of monitoring several radiation targets at the same time. Since the topology of the UAV network influences the effect of electronic reconnaissance, in this contribution, optimization is achieved based on the improvement of radiation coverage. If there is no radiation target within the sensing scope, the corresponding UAV will remove according to our novel strategy. Iterate operations are carried out for the relative optimum performance. Simulation results show that the UAV network topology optimization is capable of improving the coverage of radiation targets effectively.

Shaking hands is a homeodomain transcription factor that controls axon outgrowth of central complex neurons in the insect model Tribolium

Gene regulatory mechanisms which specify subtype identity of central complex (CX) neurons are the subject of intense investigation. The CX is a compartment within the brain common to all insect species and functions as a “command center” which directs motor actions. It is made up of several thousand neurons with more than 60 morphologically distinct identities. Accordingly, transcriptional programs must effect the specification of at least as many neuronal subtypes. We demonstrate a role for the transcription factor Shaking hands (Skh) in the specification of embryonic CX neurons in Tribolium. The developmental dynamics of Tc-skh expression are characteristic for terminal selectors of subtype identity. In the embryonic brain, Tc-skh expression is restricted to a subset of neurons, many of which survive to adulthood and contribute to the mature CX. Tc-skh expression is maintained throughout the lifetime in at least some CX neurons. Tc-skh knock-down results in axon outgrowth defects thus preventing the formation of an embryonic CX primordium. The as yet unstudied Drosophila skh shows a similar embryonic expression pattern suggesting that subtype specification of CX neurons may be conserved.

Channeling Facts, Crouching Rumours: Taiwan’s Post-Truth Encounter with the Covid Pandemic

This study examines the confrontation between Taiwan and Covid in the period before the virus finally invaded and spread widely on the island in May 2021. While the general approach to Taiwan’s success in keeping the virus out is historical, stating the policy lessons learned from previous anti-pandemic experience, the study focuses on how these coping strategies were able to be made and conducted with little disruption from misinformation and conspiracy theories. Inspired by Sheila Jasanoff’s notion of how science and technology are received through different political and policy systems, and by Bruno Latour’s semiotic reflections on the actor-network theory, the STS take on post-truth politics here is institutional and discursive: instead of focusing on the scientific and the misleading in individual policies, I provide an ethnography of rumour and scientific discourse on Covid, capturing their interactions and net effects in the context of policy discussions. Following closely the daily press conferences held by the Central Epidemic Command Center (CECC), the only official information source for the Covid pandemic, I argue that discursive frames were made upon the limited information given and few confirmed cases found. Through the expert authority and ‘what if?’ scenarios seen at these conferences, Taiwan’s anti-Covid policies came to be presented as a narrative on crises and what the government was doing to get over them, and rumours were either ignored or marginalised. Meanwhile, though disputes and speculations on pandemic control did exist among experts, they only surfaced after the local outbreak, whereupon conspiracy theories flared up, challenging the already exhausted CECC. Together, the excessive information by experts, health professionals, policy analysists and talkshow hosts composes a ‘post-truth normal’ that has started to place Taiwan’s democracy and its trust in expertise on trial.

SELECTION OF POWER LINE COMMUNICATIONS PROTOCOL APPLIED TO A WIND TURBINE UNDER SEVERE CLIMATE CONDITIONS

The main purpose of this paper is to study the preliminary selection of one or more Power Line Communications protocols or standards, to be used in a full duplex communication between a wind turbine and a command center powered by this wind turbine. This situation considers that the wind turbine is located in an isolated area in the Patagonia Austral region, working under severe climate conditions.

MEMBANGUN KREDIBILITAS PEMERINTAH MELALUI DIGITALISASI PEMERINTAHAN DI ERA POST-TRUTH (STUDI PENGEMBANGAN COMMAND CENTER PEMERINTAH PROVINSI SULAWESI UTARA)

Perkembangan teknologi dan informatika sekarang ini telah menyentuh seluruh lapisan baik pemerintah, swasta, dan masyarakat secara umum. Perubahan mendasar yang kemudian menjadi tantangan dalam penyelenggaraan pemerintahan adalah berhubungan dengan pemanfaatan teknologi informatika dan keterbukaan informasi publik. Dimana kedua hal tersebut turut mempengaruhi kredibilitas pemerintah di era digital ini. Sehingga penting bagi Pemerintah Provinsi Sulawesi Utara untuk membangun media yang terpercaya dan akuntabel yang menyediakan layanan informasi yang dapat diakses oleh masyarakat. Penelitian ini bertujuan untuk mengetahui bagaimana membangun kredibilitas pemerintah melalui digitalisasi pemerintahan di era post-truth dengan melakukan studi terhadap pengembangan command center Pemerintah Provinsi Sulawesi Utara berdasarkan dua dimensi kredibilitas dengan melakukan observasi, wawancara dan dokumentasi terhadap sumber data yang telah ditentukan. Hasil yang diperoleh menunjukkan bahwa Pemerintah Provinsi Sulawesi Utara sudah melakukan pengembangan command center untuk membangun kredibilitas pemerintah meskipun terdapat beberapa kekurangan seperti fungsi pengambilan keputusan pimpinan yang belum bisa dilakukan secara optimal melalui command center, terbatasnya informasi yang tersedia pada tampilan menu website, belum semua website perangkat daerah terintegrasi website Pemerintah Provinsi Sulawesi Utara, serta dukungan sumber daya manusia pengelola command center dari unsur ASN yang masih terbatas.