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Anaerobic sequencing batch reactor in pilot scale for treatment of tofu industry wastewater

AIP Conference Proceedings 2015年第1期1699卷

作者： Suparni Setyowati Rahayu Purwanto Budiyono 1Doctoral Program in Environmental Science University of Diponegoro Semarang Indonesia 2Department of Mechanical Engineering State Polytechnic of Semarang Semarang Indonesia 3Department of Chemical Engineering Faculty of Engineering Diponegoro University Semarang Indonesia

The small industry of tofu production process releases the waste water without being processed first, and the wastewater is directly discharged into water. In this study, Anaerobic Sequencing Batch Reactor in Pilot Scale for Treatment of Tofu Industry was developed through an anaerobic process to produce biogas as one kind of environmentally friendly renewable energy which can be developed into the countryside. The purpose of this study was to examine the fundamental characteristics of organic matter elimination of industrial wastewater with small tofu effective method and utilize anaerobic active sludge with Anaerobic Sequencing Bath Reactor (ASBR) to get rural biogas as an energy source. The first factor is the amount of the active sludge concentration which functions as the decomposers of organic matter and controlling selectivity allowance to degrade organic matter. The second factor is that HRT is the average period required substrate to react with the bacteria in the Anaerobic Sequencing Bath Reactor (ASBR).The results of processing the waste of tofu production industry using ASBR reactor with active sludge additions as starter generates cumulative volume of 5814.4 mL at HRT 5 days so that in this study it is obtained the conversion 0.16 L of CH4/g COD and produce biogas containing of CH4: 81.23% and CO2: 16.12%. The wastewater treatment of tofu production using ASBR reactor is able to produce renewable energy that has economic value as well as environmentally friendly by nature.

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An Ethernet sniffer for On-line acquisition of EEG with the BrainNet36® device applied to a BCI

An Ethernet sniffer for On-line acquisition of EEG with the ...

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Biosignals and Biorobotics Conference (BRC), ISSNIP

作者： Alessandro Botti Benevides Anibal Cotrina Atencio Javier Castillo Teodiano Freire Bastos Filho Alessander Botti Benevides Electrical Engineering Post-Graduate Program Federal University of Espirito Santo Vitória Espírito Santo Brazil ICT Doctoral School University of Trento Trento Trentino Italy

This paper presents an Ethernet sniffer programmed in ANSI C to export in an on-line way the electroencephalographic (EEG) data acquired with the device BrainNet36 ® , which is a Brazilian EEG device for clinical and polysomnography purposes. The sniffer proved to be useful for off-line analysis of the EEG and also for on-line applications, as Brain Computer-Interfaces (BCIs). Despite its limitations and packet losses at around 1.7% due to noise, the off-line analysis of the EEG successfully replicated results of the literature regarding the Event-Related (De)Synchronization (ERD/ERS) and Evoked Potentials (EPs) calculated for mental tasks. For on-line applications the sniffer was used to program a single-switch BCI for on-line classification of motor and no motor mental tasks with high success rate. Nowadays, the BrainNet36 ® device is being used for EEG research at many Brazilian universities, therefore, we hope that this article may encourage on-line applications. Finally, as the sniffer operation is explained here with examples, this text may serve as a reference guide for potential user's.

关键词： Electroencephalography Electrodes Educational institutions Noise Scalp Protocols MATLAB

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Comparative study of leaf image recognition with a novel learning-based approach

Comparative study of leaf image recognition with a novel lea...

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Science and Information Conference (SAI)

作者： Jou-Ken Hsiao Li-Wei Kang Ching-Long Chang Chih-Yang Lin Department of Computer Science and Information Engineering National Yunlin University of Science and Technology Yunlin Taiwan Graduate School of Engineering Science and Technology-Doctoral Program National Yunlin University of Science and Technology Yunlin Taiwan Department of Computer Science and Information Engineering Asia University Taichung Taiwan

Automatic plant identification via computer vision techniques has been greatly important for a number of professionals, such as environmental protectors, land managers, and foresters. In this paper, we conduct a comparative study on leaf image recognition and propose a novel learning-based leaf image recognition technique via sparse representation (or sparse coding) for automatic plant identification. In our learning-based method, in order to model leaf images, we learn an overcomplete dictionary for sparsely representing the training images of each leaf species. Each dictionary is learned using a set of descriptors extracted from the training images in such a way that each descriptor is represented by linear combination of a small number of dictionary atoms. Moreover, we also implement a general bag-of-words (BoW) model-based recognition system for leaf images, used for comparison. We experimentally compare the two approaches and show unique characteristics of our sparse coding-based framework. As a result, efficient leaf recognition can be achieved on public leaf image dataset based on the two evaluated methods, where the proposed sparse coding-based framework can perform better.

关键词： Image recognition Dictionaries Training Feature extraction Shape Vectors Image coding

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Learning sparse representation for leaf image recognition

Learning sparse representation for leaf image recognition

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IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)

作者： Jou-Ken Hsiao Li-Wei Kang Ching-Long Chang Chao-Yung Hsu Chia-Yen Chen Department of Computer Science and Information Engineering National Yunlin University of Science and Technology Yunlin Taiwan Graduate School of Engineering Science and Technology-Doctoral Program National Yunlin University of Science and Technology Yunlin Taiwan Institute of Information Science Taipei Taiwan Department of Computer Science and Information Engineering National University of Kaohsiung Taiwan

Automatic plant identification via computer vision techniques has been greatly important for a number of professionals, such as environmental protectors, land managers, and foresters. In this paper, a novel leaf image recognition technique via sparse representation is proposed for automatic plant identification. In order to model leaf images, we learn an overcomplete dictionary for sparsely representing the training images of each leaf species. Each dictionary is learned using a set of descriptors extracted from the training images in such a way that each descriptor is represented by linear combination of a small number of dictionary atoms. For each test leaf image, we calculate the correlation between the image and each learned dictionary of leaf species to achieve the identification of the leaf image. As a result, efficient leaf recognition can be achieved on public leaf dataset based on the proposed framework leading to a more compact and richer representation of leaf images compared to traditional clustering approaches. Moreover, our method is also adapted to newly added leaf species without retraining classifiers and suitable to be highly parallelized as well as integrated with any leaf image descriptors/features.

关键词： Image recognition Dictionaries Training Feature extraction Shape Educational institutions Computer vision

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Disaster Risk and Adaptation of Settlement along the River Brantas in the Context of Sustainable Development, Malang, Indonesia

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Procedia Environmental Sciences 2014年 20卷 602-611页

作者： Sri Utami Soemarno Surjono M. Bisri Student of Doctoral Program on Environment and Development Studies University of Brawijaya Malang East Java Indonesia Department of Architecture Faculty of Engineering University of Brawijaya Malang East Java Indonesia Department of Soil Sciences Faculty of Agriculture University of Brawijaya Malang East Java Indonesia Department of Urban and Regional Planning Faculty of Engineering University of Brawijaya Malang East Java Indonesia Department of Water Resources Faculty of Engineering University of Brawijaya Malang East Java Indonesia

Embong Brantas Area in Malang is one of vulnerable areas to flood. Objectives of the research were to analyze: 1) the disaster risk at Embong Brantas Area, in which vulnerability and hazard are variables of the research, 2) social adaptation that applies variables of land status, length of stay, education, income, numbers of the family member, type of buildings, and experience in disaster. Based on result of the analysis using GIS, it shows that 1.2 ha of Embong Brantas Area has high risk of flood, particularly in the next 100 years. Based on multiple regression analysis, status of land has affected 0.216 on adaptation of settlement by the community at the flood plains.

关键词： Adaptation Embong Brantas Disaster

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Methodology to Improve the Capture of the Subsoil's Heat for Solar Radiation, in the Heating Mode of Geothermal Heat Pump System

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Energy Procedia 2014年 57卷 2686-2695页

作者： Agustín Torres Rodríguez David Morillón Gálvez Daniel Aldama Ávalos Doctoral Program in Architecture UNAM Del Carmen Coyoacán Mexico City 04510 Mexico Institute of Engineering UNAM Del Carmen Coyoacán México City 04510 Mexico Faculty of Higher Studies Aragon National Autonomous University of Mexico 57178 Mexico State Mexico

The document shows the methodology of how to improve the capture of the subsoil's heat due to solar radiation. It was divided in 4 sections: a proper selection of advanced climatic alternating system's capacity, a reduction in diameter and length of geothermal coil, the study of the speed heat gain in the subsoil and the thermal behavior as deposit of heat. The wet sand was suggested as the deposit of heat and a series of steps were set to evaluate 3 physical variables. The results show that 4 sections are closely related to improvement in the capture of the heat subsoil.

关键词： Coil geothermal heat pump system heating methodology solar radiation wet sand

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Complex thermal evaluation for 2,2′-azobis(isobutyronitrile) by non-isothermal and isothermal kinetic analysis methods

Complex thermal evaluation for 2,2′-azobis(isobutyronitrile...

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作者： Liu, Shang-Hao Yu, Yen-Pin Lin, Yu-Chi Weng, Sheng-Yi Hsieh, Tung-Feng Hou, Hung-Yi Doctoral Program Department of Safety Health and Environmental Engineering National Yunlin University of Science and Technology YunTech 123 University Rd. Sec. 3 Douliou Yunlin 64002 Taiwan Department of Safety Health and Environmental Engineering National Yunlin University of Science and Technology YunTech 123 University Rd. Sec. 3 Douliou Yunlin 64002 Taiwan Department of General Education Center Chienkuo Technology University 1 Chiehshou North Rd. Changhua 50046 Changhua Taiwan Department of Occupational Safety and Health Jen-Teh Junior College of Medicine Nursing and Management 1 Jen-Teh Rd. Houlong Miaoli 35665 Taiwan

Azo compounds are widely used in dyes, pigments, blowing agents, and initiators. Unfortunately, these compounds contain the bivalent -N-N- composition which might be cleavaged readily even under high ambient temperature. The self-accelerating decomposition might cause a runaway reaction and lead to a fire or explosion when the cooling system fails or other upsets occur. To investigate the thermal stability parameters of 2,2′- azobis(isobutyronitrile) with thermal hazard and mechanism, differential scanning calorimetry and thermal activity monitor III were applied with non-isothermal method and isothermal method to obtain onset temperature (T 0), maximum temperature (Tmax), and heat of decomposition (ΔHd). Thermal stability parameters play a pivotal role in thermal analysis, leading particularly to complex evaluation of the inherently safer design during preparation, processing, transport, or storage. The results provide sufficient thermokinetic parameters for process safety in terms of proactive loss prevention program. © Akadémiai Kiadó, Budapest, Hungary 2014.

关键词： Differential scanning calorimetry

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Cross-camera vehicle tracking via affine invariant object matching for video forensics applications

Cross-camera vehicle tracking via affine invariant object ma...

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2013 IEEE International Conference on Multimedia and Expo, ICME 2013

作者： Hsu, Chao-Yung Kang, Li-Wei Mark Liao, Hong-Yuan Institute of Information Science Academia Sinica Taipei Taiwan Graduate School of Engineering Science and Technology-Doctoral Program Department of Computer Science and Information Engineering National Yunlin University of Science and Technology Yunlin Taiwan

ISBN: (纸本)9781479900152

The recent deployment of very large-scale camera networks consisting of fixed/moving surveillance cameras and vehicle video recorders, has led to a novel field in object tracking problem. The major goal is to detect and track each vehicle within a large area, which can be applied to video forensics. For example, a suspected vehicle can be automatically identified for mining digital criminal evidences from a large amount of video data. In this paper, we propose an efficient cross-camera vehicle tracking technique via affine invariant object matching. More specifically, we formulate the problem as invariant image feature matching among different viewpoints of cameras. To achieve vehicle matching, we first extract invariant image feature based on ASIFT (affine and scale-invariant feature transform) for each detected vehicle in a camera network. Then, to improve the accuracy of ASIFT feature matching between images from different viewpoints, we propose to efficiently match feature points based on our observed spatially invariant property of ASIFT, as well as the min-hash technique. As a result, cross-camera vehicle tracking can be efficiently and accurately achieved. Experimental results demonstrate the efficacy of the proposed algorithm and the feasibility to video forensics applications. © 2013 IEEE.

关键词： Tracking (position)

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Haze effect removal from image via haze density estimation in optical model

Haze effect removal from image via haze density estimation i...

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作者： Yeh, Chia-Hung Kang, Li-Wei Lee, Ming-Sui Lin, Cheng-Yang Department of Electrical Engineering National Sun Yat-sen University 804 Taiwan Graduate School of Engineering Science and Technology-Doctoral Program Department of Computer Science and Information Engineering National Yunlin University of Science and Technology Yunlin 640 Taiwan Graduate Institute of Networking and Multimedia Department of Computer Science and Information Engineering National Taiwan University Taipei 106 Taiwan

Images/videos captured from optical devices are usually degraded by turbid media such as haze, smoke, fog, rain and snow. Haze is the most common problem in outdoor scenes because of the atmosphere conditions. This paper proposes a novel single image-based dehazing framework to remove haze artifacts from images, where we propose two novel image priors, called the pixel-based dark channel prior and the pixel-based bright channel prior. Based on the two priors with the haze optical model, we propose to estimate atmospheric light via haze density analysis. We can then estimate transmission map, followed by refining it via the bilateral filter. As a result, high-quality haze-free images can be recovered with lower computational complexity compared with the state-of-the-art approach based on patch-based dark channel prior. ©2013 Optical Society of America.

关键词： Pixels

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Towards advanced solutions for achieving sustainability goals in buildings: Lessons learned from case studies

Towards advanced solutions for achieving sustainability goal...

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2nd Annual International Conference Sustainable Design, engineering and Construction, ICSDEC 2012

作者： Halicioglu, Fahriye Hilal Arditi, David Gunhan, Suat Illinois Institute of Technology Department of Civil Architectural and Environmental Engineering Construction Engineering and Management Program 60616Post Doctoral Visiting Research Scholar Chicago IL 60616 United States University of Texas at San Antonio College of Architecture Construction Science and Management Program 501 W. Cesar Chavez Blvd. San Antonio TX 78207 United States

ISBN: (纸本)9780784412688

Sustainable building projects deal with a multitude of technical, environmental, economic, social, organizational, and innovation-related issues, to name but a few. Achieving sustainability goals depends on how well these issues are handled. While some sustainable building projects are quite successful, some are not. It is therefore important to learn lessons from past projects. This research aims to reveal the key lessons concerning sustainability-related issues in building projects. To that end, challenges in the achievement of sustainability goals of building projects are discussed, and lessons learned systems are examined. After that, the events experienced by project managers in a large number of sustainable building projects are obtained from a major public agency's website and are analyzed. The findings show the key lessons that have an important impact on the success/failure of sustainable building projects. The expected contribution of the study is to foster advanced solutions for future sustainable projects. © 2013 American Society of Civil Engineers.

关键词： Sustainable development

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