Motion Switching with Sensory and Instruction Signals by designing Dynamical Systems using Deep Neural Network

To ensure that a robot is able to accomplish an extensive range of tasks, it is necessary to achieve a flexible combination of multiple behaviors. This is because the design of task motions suited to each situation would become increasingly difficult as the number of situations and the types of tasks performed by them increase. To handle the switching and combination of multiple behaviors, we propose a method to design dynamical systems based on point attractors that accept (i) "instruction signals" for instruction-driven switching. We incorporate the (ii) "instruction phase" to form a point attractor and divide the target task into multiple subtasks. By forming an instruction phase that consists of point attractors, the model embeds a subtask in the form of trajectory dynamics that can be manipulated using sensory and instruction signals. Our model comprises two deep neural networks: a convolutional autoencoder and a multiple time-scale recurrent neural network. In this study, we apply the proposed method to manipulate soft materials. To evaluate our model, we design a cloth-folding task that consists of four subtasks and three patterns of instruction signals, which indicate the direction of motion. The results depict that the robot can perform the required task by combining subtasks based on sensory and instruction signals. And, our model determined the relations among these signals using its internal dynamics.Comment: 8 pages, 6 figures, accepted for publication in RA-L. An accompanied video is available at this https://youtu.be/a73KFtOOB5

Man-Machine Control of Space Robots under Uncertainty

Control problem of space robots is characterized by several challenges. The first one is that the area is full of uncertainties due to lack of information. Another difficulty is tasksharing between an operator and a partly autonomous robot. Moreover, there are several constrains on the robot operations, including communication delay and an appropriate temperature at which robot can work. Design of the robots navigation should be based on consideration of trade-offs between several conflicting criteria, such as maximization of the robot safety, minimization of the energy consumption, maximization of the value of information collected by the robot during its movement. Our research objective is to design man-machine interactive system, dealing with navigation problem of space robots. This paper focuses on the problem of path planning for small robot exploring a small asteroid. This problem is solved by an operator controlling the robot from Earth

JAPANESE MENTAL HEALTH CARE IN HISTORICAL CONTEXT: WHY DID JAPAN BECOME A COUNTRY WITH SO MANY PSYCHIATRIC CARE BEDS?

Mental health care has been shifting from psychiatric institutions towards community-based settings for the last 40 years in most countries. However, Japan still has a very high ratio of psychiatric care beds per capita, and the average length of stay in psychiatric institutions is nearly 300 days. By examining the history of Japanese mental health care, this paper analyses the reasons why it has been heavily dependent on hospital-based care, and why Japan still relies on it to this day. The roles of psychiatric social workers, who promote the rehabilitation of people with mental disorders, is also presented in the conclusio

Pembangkitan Ekonomis pada Unit Pembangkit Listrik Tenaga Diesel Telaga Gorontalo Menggunakan Algoritma Genetika

The increasing daily need towards electrical energy demands for generation companies to conduct operational cost-saving strategy including the generation fuel. One of the strategies that can be done is through economical generation optimization. The genetics algorithm of the heuristics method is known for its ability to overcome the problems characterized as non-linear, non convex, integer/ discrete, not continuous, and a system with a lot of variables. The evaluation technique employing the evolution theory has been applied to the case of IEEE 26 buses power system and diesel power generation in a unit in Telaga, Gorontalo. The result shows that the proposed method is believed to be able to minimize the generation cost better than the previous method. The method is tested by applying for its real system in Telaga, Gorontalo and it is found that the total cost at Rp 20.201.000,00 per hour with total load at 5.000 kW

Analisis Kebutuhan Guru dan Siswa MAN I Kota Malang Terhadap Pembelajaran Daring Pada Mata Pelajaran Bahasa Indonesia

Abstrak: Penelitian ini bertujuan untuk mengumpulkan informasi tentang kemajuan belajar siswa, dengan pembelajaran dalam jaringan (daring) guru bisa mengumpulkan informasi tentang kebutuhan nyata peserta didik MAN 1 Kota Malang dalam pembelajaran bahasa Indonesia, khususnya pada pembelajaran teks eksposisi kelas X dan XI. Dengan menggunakan metode analisis kebutuhan kemudian dari hasil penelitian ini dapat digunakan sebagai bahan evaluasi untuk memperoleh informasi yang berguna bagi pengambilan kebijakan pendidikan dalam rangka meningkatkan mutu pendidikan pada masa pandemi seperti sekarang ini. Ada dua cakupan aspek yang menjadi fokus penelitian tentang analisis kebutuhan guru dan siswa MAN I Kota Malang dalam pembelajaran daring pada mata pelajaran bahasa Indonesia, yaitu: 1) bagaimanakah kebutuhan guru MAN I Kota Malang terhadap pembelajaran bahasa Indonesia dalam jaringan (2) Bagaimanakah kebutuhan peserta didik MAN I Kota Malang terhadap pembelajaran bahasa Indonesia dalam jaringan. Penelitian ini menggunakan pendekatan kualitatif dengan jenis penelitian deskriptif. . Penelitian ini, diajukan untuk menganalisis kebutuhan guru dan peserta didik terhadap pembelajaran bahasa Indonesia dalam jaringan. Penelitian ini menggunakan pendekatan deskriptif dengan tujuan untuk mendeskripsikan objek penelitian atupun hasil penelitian. Data yang diperoleh berasal dari angket, penelitian ini dilaksanakan untuk mengetahui kebutuhan guru dan peserta didik MAN 1 Kota Malang terhadap pembelajaran bahasa Indonesia dalam jaringa (daring). Sampel yang digunakan adalah dari perwakilan semua tingkatan kelas. Data dalam penelitian ini berupa data kualitatif yang menjelaskan tentang suatu fenomena yang berupa deskriptif, yang meneliti tentang kebutuhan (Needs), yang difokuskan pada guru dan peserta didik MAN I Kota Malang dalam melaksakan pembelajaran bahasa Indonesia dalam jaringan.Kata Kunci: analisis kebutuhan, guru dan siswa MAN I Kota Malang, pembelajaran daring, mata pelajaran bahasa Indonesia

Kajian Ekonomis Pembangkit Hybrid Renewable Energi Menuju Desa Mandiri Energi Di Kabupaten Bone-Bolango

Energy crisis due to extensive uses of fossil fuel and environmental issues caused by unsustainable uses of energy driving the world and Indonesian government to accelerate the USAge of renewable energy such as hydro, wind and solar. One of the government approaches is to implement a program called Independent Energy Village (IEV). Hybrid Optimization Model for Electric Renewables (HOMER) serves to design a micropower systems and to facilitate the comparison between some of power generation technologies. Researcher models the power system based on the physical behavior and overall cost, which are the total cost of installation and operation of the system during operation of the system. HOMER allows researcher to compare various forms of system designs technically and economically. This research was conducted in the village of Lombongo, District Suwawa, in Bone-Bolango Gorontalo. Some of the modeling results showed that the combination of micro-hydro and solar power have the most favorable economic value if operated over 25 years with a Net Present Cost (NPC) is US$-369,087.00 and a Level Cost of Energy (LCOE) of -0.106 US$/kWh below the level energy costs of PLN at 0.116 US$/kWh in whch made this hybrid plant is very competitive. The hybrid plant has micro-hydro generating capacity of 58,9 kW with annual production of 657,384 kW, while solar power plant with a production capacity of 15,7 kW per year 20.091 kW

Stable deep reinforcement learning method by predicting uncertainty in rewards as a subtask

In recent years, a variety of tasks have been accomplished by deep reinforcement learning (DRL). However, when applying DRL to tasks in a real-world environment, designing an appropriate reward is difficult. Rewards obtained via actual hardware sensors may include noise, misinterpretation, or failed observations. The learning instability caused by these unstable signals is a problem that remains to be solved in DRL. In this work, we propose an approach that extends existing DRL models by adding a subtask to directly estimate the variance contained in the reward signal. The model then takes the feature map learned by the subtask in a critic network and sends it to the actor network. This enables stable learning that is robust to the effects of potential noise. The results of experiments in the Atari game domain with unstable reward signals show that our method stabilizes training convergence. We also discuss the extensibility of the model by visualizing feature maps. This approach has the potential to make DRL more practical for use in noisy, real-world scenarios.Comment: Published as a conference paper at ICONIP 202

Teaching Research Methodology Using A Project-Based Three Course Sequence Critical Reflections On Practice

This article presents a reflective analysis of teaching research methodology through a three course sequence using a project-based approach.  The authors reflect critically on their experiences in teaching research methods courses in an undergraduate business management program.  The introduction of a range of specific techniques including student developed research projects, student-centered learning experiences, and public presentation of research projects are reflected upon.  In 2001, the Department of Management reviewed the curriculum and established a research sequence linking major management course offerings.  Three courses: Statistics, Research Methodology and Organizational Behavior were selected to be taught in sequence and designed to build research expertise.  This article addresses the processes, procedures and practices for implementing and sustaining an undergraduate research sequence.  Techniques are included for course design, development, and facilitation that emphasize product based learning strategies and interactive elements.  Techniques for garnering student engagement and excitement for research projects will be presented

Interactively Robot Action Planning with Uncertainty Analysis and Active Questioning by Large Language Model

The application of the Large Language Model (LLM) to robot action planning has been actively studied. The instructions given to the LLM by natural language may include ambiguity and lack of information depending on the task context. It is possible to adjust the output of LLM by making the instruction input more detailed; however, the design cost is high. In this paper, we propose the interactive robot action planning method that allows the LLM to analyze and gather missing information by asking questions to humans. The method can minimize the design cost of generating precise robot instructions. We demonstrated the effectiveness of our method through concrete examples in cooking tasks. However, our experiments also revealed challenges in robot action planning with LLM, such as asking unimportant questions and assuming crucial information without asking. Shedding light on these issues provides valuable insights for future research on utilizing LLM for robotics.Comment: 7 pages, 6 figures, accepted at SII 202