Sirindhorn International Institute of Technology

About: Sirindhorn International Institute of Technology is a based out in . It is known for research contribution in the topics: Supply chain & Combustion. The organization has 1048 authors who have published 1678 publications receiving 30067 citations.

Magnetic-responsive polysaccharide-inorganic composite materials for cancer therapeutics

Abstract: Each year a large number of people lose their lives because of well-studied diseases such as diabetes mellitus, cancer, and neurodegenerative and cardiovascular diseases. Cancer is one of these diseases and drugs used for its treatment have a high toxicity. The nonspecific delivery of these toxic drugs to different parts of the body through dosage forms is an immense challenge within the treatment of numerous diseases. However, there are several opportunities that have been created through biomedical nanotechnology for diagnosis of, and therapies for, health problems. In fact, advanced drug delivery development has attracted a special attention to deliver drugs to the suitable organ and tissue. Indeed, nanotechnology can be taken into account as one of the useful approaches for the diagnosis, treatment, and prevention of cancer disease. Thanks to the imaging characteristics and therapeutic properties of magnetic metal oxide nanoparticles as Fe3O4 and γ-Fe2O3 maghemite, they took an outstanding place for biomedical applications among other different nanoparticles. Through the application of a magnetic field, magnetic nanoparticles (MNPs) can easily enter into the lesion area due to their small size and large specific area. Furthermore, magnetic nanoparticle properties are appealing, including surface charge nature and density, shape, chemical composition, size, degradation, internal morphology, and responsiveness to stimuli of pH, light, and temperature. At the present time, a new subfield named theranostics came out due to MNPs’ double function in diagnosis and therapy. Thus MNPs attract significant attention in the treatment of diseases, especially for cancer. This chapter is focused on some of the newest developments concerning MNPs.

Towards a BSN-based gesture interface for intelligent home applications

Abstract: This paper presents an attempt towards the development of a hand gesture-based interface for intelligent home applications using Body Sensor Networks (BSNs). The system being developed consists of four main components namely BSN sensor gloves as the input devices, a software prototype for facilitating mappings of sensory signals onto different commands, a model for automatic gesture recognition and a relay-board for demonstrating device control output. Our current results include the first version of software prototype and real-time recognition of simple gesture commands from signals acquired using the BSN-based flex-sensor glove.

Singular-Spectrum Analysis for Digital Audio Watermarking with Automatic Parameterization and Parameter Estimation

Abstract: This paper proposes a blind, inaudible, robust digitalaudio watermarking scheme based on singular-spectrum analysis, which relates to watermarking techniques based on singular value decomposition. We decompose a host signal into its oscillatory components and modify amplitudes of some of those components with respect to a watermark bit and embedding rule. To improve the sound quality of a watermarked signal and still maintain robustness, differential evolution is introduced to find optimal parameters of the proposed scheme. Test results show that, although a trade-off between inaudibility and robustness still persists, the difference in sound quality between the original and the watermarked one is considerably smaller. This improved scheme is robust against many attacks, such as MP3 and MP4 compression, and band-pass filtering. However, there is a drawback, i.e., some music-dependent parameters need to be shared between embedding and extraction processes. To overcome this drawback, we propose a method for automatic parameter estimation. By incorporating the estimation method into the framework, those parameters need not to be shared, and the test results show that it can blindly decode watermark bits with an accuracy of 99.99%. This paper not only proposes a new technique and scheme but also discusses the singular value and its physical interpretation. key words: singular-spectrum analysis, singular value decomposition, singular value, differential evolution, automatic parameter estimation, concavity density function

Optimization of Indonesian Geothermal Energy Resources for Future Clean Electricity Supply: A Case of Java-Madura-Bali System

Abstract: Total of geothermal potential for power generation in Indonesia is estimated to be around 28 GW, equal to 40% of world’s potential. Around 36% of Indonesian geothermal potential is located in Java and Bali Islands. In 2006, total installed capacity of geothermal power plants was only 852 MW or 3% of total potential in the country. The Philippines, in comparison, has higher geothermal utilization for electricity generation. It is around 12.7% of the national capacity. Meanwhile, Indonesian government’s current policy concerning the power sector is to promote coal utilization. However, coal power generation faces environmental emission issue. This study examined utilization of geothermal energy for future electricity supply expansion in Java-Madura-Bali (Jamali) system, the largest electricity consumer in Indonesia, by using Long-range Energy Alternatives Planning (LEAP) model from 2006 to 2025. This study uses three scenarios of geothermal utilization to maintain reserve margin of 30%, according to the government plan, in 2025. In the first scenario, it was added with 50 MW of geothermal power plant, in the second scenario 100 MW of geothermal power plant was added, and in the last scenario 124 MW was added to the existing capacity. It was found that in the end of the period, by implementing the first scenario, the geothermal capacity increases by 5.7 GW. In the second and the third scenarios, the estimated increase is 8.2 GW and about 10 GW respectively. It was also found that in 2025 CO2 emission reduction in each scenario were 12.9%, 21.5%, and 25% respectively, compared to the BAU scenario. Additionally, in the end of projection, the costs of each scenario were 6.6 Billion USD, 6.8 Billion USD and 7.1 Billion USD respectively, compared to 6.3 Billion USD in the BAU scenario. By considering externality from power generation, the first, second and third scenarios reduce external costs by 46.3, 71.6 and 80.8 million USD respectively, when compared with the BAU scenario. However, by including the external costs in the total cost, it does not make all geothermal scenarios cheaper than the BAU scenario.