bluuebunny/crossref_metadata_2025 huggingface dataset:
POLITIK HUKUM PERSAINGAN USAHA DI INDONESIA
Authors: Hidayat Muhammad Fajar
Published: March 2019

Sebagai reaksi terhadap maraknya kegiatan konglomerasi, sejak tahun1980’an di Indonesia, masyarakat selanjutnya menuntut dikeluarkannyaUndang-Undang Anti Monopoli atau Antitrust Law. Selain itu tuntutandibuatnya perangkat hukum Anti Monopoli karena terdapat penguasaanbisnis pada sentralisme kekuasaan yang disinyalir kuat mengandung praktikkorupsi, kolusi, dan nepotisme (KKN). Adapun yang menjadi tujuan dalampenelitian ini yaitu untuk mengetahui politik hukum persaingan usaha diIndonesia dan yang menyebabkan Undang-Undang Nomor 5 Tahun 1999tentang Larangan Praktek Monopoli dan Persaingan Usaha Tidak Sehatbelum cukup efektif dalam menciptakan persaingan usaha yang sehat diIndonesia. Penulis menggunakan metode penelitian hukum normatif dalampenelitian ini. Hasil penelitian ini menunjukkan bahwa Undang-UndangNomor 5 Tahun 1999 tentang Larangan Praktek Monopoli dan PersainganUsaha Tidak Sehat merupakan implementasi dari politik hukum persainganusaha di Indonesia. Politik hukum persaingan usaha di Indonesia padaprinsipnya tergantung political will dari anggota Dewan Perwakilan Rakyat(DPR) selaku legislatif bersama dengan Pemerintah selaku eksekutif dalammembuat Undang-Undang. Sebab Undang-Undang Nomor 5 Tahun 1999tentang Larangan Praktek Monopoli dan Persaingan Usaha Tidak Sehatbelum cukup efektif dalam menciptakan persaingan usaha yang sehat diIndonesia dikarenakan dalam substansi UU tersebut masih terdapatkelemahan dalam beberapa pasal yang membuat kinerja Komisi PengawasPersaingan Usaha (KPPU) menjadi tidak maksimal.
MEMBANGUN BUDAYA HUKUM INDONESIA DI ERA GLOBALISASI
Authors: - Riski Febria Nurita Laga Sugiarto
Published: March 2019

Jika hari ini kita berbicara tentang sebuah negara yang disebut Republik Indonesia maka kita akan banyak bicara tentang korupsi, penyuapan, konflik baik konflik internal dalam tiga lembaga tertinggi di Indonesia maupun konflik eksternal di luar lembaga-lembaga negara, pertempuran antara siswa serta perkelahian antar warga di Indonesia sendiri, penganiayaan, pembunuhan, pemerkosaan dan banyak lainnya yang kita miliki sendiri telah merasa malu untuk membicarakannya karena hal-hal ini tidak akan ada akhirnya. Apalagi jika kita berbicara tentang hukum di era globalisasi ,kita akan berbicara tentang hukum di Indonesia dengan nama ketidakadilan, keberpihakan, keberpihakan, bukan otonomi dan lain-lain. Hal-hal ini ketika kita melihat kembali dengan hati-hati, kita akan menemukan sesuatu yang disebut "budaya hukum", karena budaya hukum adalah penentu di mana sistem hukum ditempatkan di tempat yang sah dengan nilai-nilai di dalamnya yang nilai sosial sebagai hukum yang dibuat ditujukan untuk orang-orang di suatu negara sendiri untuk mengatur semua perilaku orang-orang di negara yang mengeluarkan hukum. Budaya hukum di Indonesia sendiri telah tergusur oleh budaya hukum baru yang disebabkan oleh banyak hal misalnya pesatnya kemajuan teknologi seolah-olah kita dapat melintasi batas antar negara, perkembangan perdagangan bebas di Indonesia, informasi yang semakin banyak dan masih banyak penyebab lainnya. Penyebabnya adalah meninggalkan dampak yang baik pada negara kita misalnya, hanya di bidang hukum, dengan kemajuan teknologi informasi kita dapat menentukan bagaimana penerapan hukum di negara-negara yang lain sehingga kita dapat meningkatkan sistem hukum di negara kita sendiri jika dinilai kurang baik maka kita dapat mengambil contoh penerapan hukum di negara lain. Selain dampak positif yang dibuat oleh banyak kemajuan di era globalisasi, dampak negatif juga turut serta mewarnai segala sesuatunya di negara kita. Misalnya, hanya dengan munculnya budaya pemikiran barat kita menjadi barat. Demikian pula kita dapat melihat awal negara kita adalah negara demokratis dari rakyat dan untuk orang-orang serba sosial dan kepentingan sosial tetap jadi kali ini secara tidak langsung kami negara bergeser ke negara liberal yaitu masyarakat yang paling memiliki semangat individualisme, ekonomi bergeser yang semula menyombongkan diri tentang ekonomi yang demokratis di negara ini menjadi ekonomi kapitalisme telah terbukti di negara kita yang berkuasa pada titik mana pun pulsa ekonomi adalah modal tinggi dan bahwa tidak ada modal masih marginal klan di negara mereka sendiri tanpa ada perubahan dari tahun ke tahun. Pergeseran yang merupakan subyek penulis penelitian yang akan dijelaskan satu per satu dimulai dari keadaan awal budaya hukum di Indonesia, penetrasi barat masuk di Indonesia, budaya hukum negara di Indonesia setelah penetrasi barat masuk, hingga Bagaimana mengembalikan budaya hukum Indonesia yang telah mengungsi dalam arti pergeseran arah negatif.
ANALISIS YURIDIS TENTANG SENGKETA DALAM PROSPEKTIF KAJIAN HUKUM INTERNASIONAL
Authors: - UKAS
Published: March 2019

Sengketa dan atau konflik baik ia secara privat maupun publik akan berujung padaketidak/kesepahaman para pihak atau subjek hukum lainnya. Dalam hubungan Internasionalantar negara diperlukan keharmonisan diberbagai kegiatan, dan ini tidak akan tercapai jika parapihak tidak memiliki itikad baik dalam menyelesaikan sengketanya. Penyelesaian sengketakarenanya merupakan satu tahap penting dan menentukan. Dalam hal terjadinya sengketa,hukum internasional memainkan peranan yang juga esensial. Ia memberikan pedoman, aturan,dan cara atau metode bagaimana suatu sengketa dapat diselesaikan oleh para pihak secaradamai. Upaya penyelesaian sengketa telah menjadi perhatian bagi masyarakat internasional,utamanya apabila menghdapi sengketa yang sifatnya bisnis yang melampaui batas-batas wilayahkedaulatan suatu negara. Penyelesaian sengketa secara damai merupakan cara yang telah diakuidan dipraktikkan sejak lama sampai saat ini. Suatu negara meskipun tunduk pada kewajibanpenyesaian sengketa secara damai, ia tetap memiliki kewenangan menentukan caraa atau metodepenyelesaian sengketanya. Kewajibannya tetap tunduk pada kesepakatan negara yangbersangkutan.
Liver Injury Induced by Carbon Tetrachloride in Mice Is Prevented by the Antioxidant Capacity of Anji White Tea Polyphenols
Authors: Wang Ranran , Yang Zhiqing , Zhang Jing , Mu Jianfei , Zhou Xianrong , Zhao Xin
Published: March 2019

Anji white tea is a unique variety of green tea that is rich in polyphenols. In this study, the effect of Anji white tea polyphenols (AJWTP) on the prevention of carbon tetrachloride (CCl4)-induced liver injury through its antioxidant properties was studied. Biochemical and molecular biology methods were used to analyze the serum and liver tissue of mice. The antioxidant capacity and liver injury preventive effect of AJWTP were determined, and the mechanism was elaborated. The results showed that AJWTP decreased the serum levels of aspartate aminotransferase (AST), alanine aminotransferase (ALT), triglyceride (TG), and total cholesterol (TC) in mice with liver injury, it increased the activities of superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) in the serum and liver tissue of mice with liver injury, and it also decreased the amount of malondialdehyde (MDA). Further quantitative polymerase chain reaction (qPCR) results showed that AJWTP upregulated the mRNA expression of Cu/Zn-SOD, Mn-SOD, catalase (CAT), and nuclear factor of kappa light polypeptide gene enhancer in B-cell inhibitor alpha (IκB-α) and downregulated the expression of nuclear factor κ-light-chain-enhancer of activated B-cells (NF-κB), cyclooxygenase-2 (COX-2), inducible nitric oxide synthase (iNOS), interleukin-1 beta (IL-1β), and tumor necrosis factor alpha (TNF-α) in the liver tissue of mice with liver injury. Therefore, AJWTP produces sufficient antioxidant action to prevent liver injury, and the effect increases with the increase in AJWTP concentration. The effect of 200 mg/kg AJWTP was similar to that of the same concentration of the drug (silymarin) used for the treatment of liver injury. This indicates excellent potential for the development and utilization of AJWTP because it is an active substance with excellent antioxidant effects and can prevent liver injury.
Adaptive Polling Medium Access Control Protocol for Optic Wireless Networks
Authors: Msongaleli Dawson Ladislaus , Kucuk Kerem , Kavak Adnan
Published: March 2019

The emergence of optical wireless networks (OWNs) is a potential solution to the quest for the increasing bandwidth demand. Existing bandwidth assignment strategies are not suitable for OWNs, considering factors such as differences between the physical properties of radio networks and OWNs. In order to eliminate collision, minimize delay and enhance system utilization and fairness, we propose the non-contention bandwidth assignment protocol called adaptive polling medium access control (APMAC) protocol for OWNs. The APMAC protocol involves association, data transmission and dissociation phases. Moreover, the APMAC protocol exploits features of the IEEE 802.15.7 visible light communication (VLC) standard. While assigning bandwidth to the visible light nodes (VLNs), the visible light access point (VLAP) establishes a polling table that contains the identity, buffer size and round-trip time of each VLN that issued bandwidth request. The contents of the polling table enable the computation of the maximum transmission unit and time-slot for each VLN that requests bandwidth assignment. In order to achieve convincing results, we simulate the protocol under varying network sizes ranging from 1 to 10 VLNs per access point, then we compare the results against the medium transparent medium access control (MT–MAC) protocol that is a non-contention MAC protocol. We demonstrate numerical results of our study considering average waiting time, packet collision, system utilization and fairness. Numerical results reveal that the APMAC protocol outperforms the MT–MAC protocol.
Application of a DC Distribution System in Korea: A Case Study of the LVDC Project
Authors: Kim Juyong , Kim Hyunmin , Cho Youngpyo , Kim Hongjoo , Cho Jintae
Published: March 2019

With the rapid expansion of renewable energy and digital devices, there is a need for direct current (DC) distribution technology that can increase energy efficiency. As a result, DC distribution research is actively underway to cope with the sudden digitization and decentralization of load environment and power supply. To verify the possibility of DC distribution, Korea Electric Power Corporation (KEPCO) Research Institute made a DC distribution system connected with a real power system in Gwangju. The construction of the demonstration area mainly includes design of protection and grounding systems, operating procedures of insulation monitoring device (IMD), and construction of power converters. Furthermore, this paper goes beyond the simulation and the lab testing to apply DC distribution to a real system operation in advance. It is designed as a long-distance low-loaded customer for rural areas and operated by the DC distribution. In addition, safety and reliability are confirmed through field tests of DC distribution elements such as power conversion devices, protection and grounding systems. In particular, to improve the reliability of non-grounding system, the insulation monitoring device was installed and the algorithms of its operational procedures are proposed. Finally, this paper analyzes the problems caused by operating the actual DC distribution and suggests solutions accordingly.
Numerical Analysis of a Catenary Mooring System Attached by Clump Masses for Improving the Wave-Resistance Ability of a Spar Buoy-Type Floating Offshore Wind Turbine
Authors: Liu Zhenqing , Tu Yuangang , Wang Wei , Qian Guowei
Published: March 2019

The International Energy Agency (IEA), under the auspices of their Offshore Code Comparison Collaboration (OC3) initiative, has completed high-level design OC-3 Hywind system. In this system the wind turbine is supported by a spar buoy platform, showing good wave-resistance performance. However, there are still large values in the motion of surge degree of freedom (DOF). Addition of clump masses on the mooring lines is an effective way of reducing the surge motion. However, the optimization of the locations where the clump masses are added is still not clear. In this study, therefore, an in-house developed code is verified by comparing the results of the original OC3 model with those by FAST. The improvement of the performance of this modified platform as a function of the location of the clump masses has been examined under three regular waves and three irregular waves. In the findings of these examination, it was apparent that attaching clump masses with only one-tenth of the mass of the total mooring-line effectively reduces the wave-induced response. Moreover, there is an obvious improvement as the depth of the location where the clump masses mounted is increased.
Generation of High Quality Biogenic Silica by Combustion of Rice Husk and Rice Straw Combined with Pre- and Post-Treatment Strategies—A Review
Authors: Beidaghy Dizaji Hossein , Zeng Thomas , Hartmann Ingo , Enke Dirk , Schliermann Thomas , Lenz Volker , Bidabadi Mehdi
Published: March 2019

Utilization of biomass either as a renewable energy source or for the generation of biogenic materials has received considerable interest during the past years. In the case of rice husk (RH) and rice straw (RS) with high silica contents in the fuel ash, these approaches can be combined to produce high-grade biogenic silica with purities >98 wt % from combustion residues. The overall process can be considered nearly neutral in terms of CO2 emission and global warming, but it can also address disposal challenges of rice husk and rice straw. For the resulting biogenic silica, several advanced application opportunities exist, e.g., as adsorbents, catalysts, drug delivery systems, etc. This article provides a comprehensive literature review on rice husk and rice straw combustion as well as applied strategies for raw material pre-treatment and/or post-treatment of resulting ashes to obtain high quality biogenic silica. Purity of up to 97.2 wt % SiO2 can be reached by combustion of untreated material. With appropriate fuel pre-treatment and ash post-treatment, biogenic silica with purity up to 99.7 wt % can be achieved. Studies were performed almost exclusively at a laboratory scale.
Volumetric Tooth Wear Measurement of Scraper Conveyor Sprocket Using Shape from Focus-Based Method
Authors: Ding Hua , Liu Yinchuan , Liu Jiancheng
Published: March 2019

Volumetric tooth wear measurement is important to assess the life of scraper conveyor sprocket. A shape from focus-based method is used to measure scraper conveyor sprocket tooth wear. This method reduces the complexity of the process and improves the accuracy and efficiency of existing methods. A prototype set of sequence images taken by the camera facing the sprocket teeth is collected by controlling the fabricated track movement. In this method, a normal distribution operator image filtering is employed to improve the accuracy of an evaluation function value calculation. In order to detect noisy pixels, a normal operator is used, which involves with using a median filter to retain as much of the original image information as possible. In addition, an adaptive evaluation window selection method is proposed to address the difficulty associated with identifying an appropriate evaluation window to calculate the focused evaluation value. The shape and size of the evaluation window are autonomously determined using the correlation value of the grey scale co-occurrence matrix generated from the measured pixels’ neighbourhood pixels. A reverse engineering technique is used to quantitatively verify the shape volume recovery accuracy of different evaluation windows. The test results demonstrate that the proposed method can effectively measure sprocket teeth wear volume with an accuracy up to 97.23%.
Prediction of the Dynamic Stiffness of Resilient Materials using Artificial Neural Network (ANN) Technique
Authors: Kim Changhyuk , Lee Jung-Yoon , Kim Moonhyun
Published: March 2019

High-rise residential buildings are constructed in countries with high population density in response to the need to utilize small development areas. As many high-rise buildings are being constructed, issues of floor impact sound tend to occur in buildings. In general, resilient materials are implemented between the slab and the finishing mortar to control the floor impact sound. Various mechanical properties of resilient materials can affect the floor impact sound. To investigate the impact sound reduction capacity, various experimental tests were conducted. The test results show that the floor impact sound reduction capacity has a close relationship with the dynamic stiffness of resilient materials. A total of six different kinds of resilient materials were loaded under four loading conditions. The test results show that loading time, loading, and material properties influence the change in dynamic stiffness. Artificial neural network (ANN) technique was implemented to obtain the responses between the deflection and dynamic stiffness. Three different algorithms were considered in the ANN models and the trained results were analyzed based on the root mean square error. The feasibility of using the ANN technique was verified with a high and consistent level of accuracy.
Changes in Means and Extreme Events of Sea Surface Temperature in the East China Seas Based on Satellite Data from 1982 to 2017
Authors: Wang Qingyuan , Li Yan , Li Qingquan , Liu Yiwei , Wang Ya-nan
Published: March 2019

Marginal seas are fundamental to humans for their importance in mariculture resources and commerce. Based on the NOAA 0.25 degree daily Optimum Interpolation (OI) sea surface temperature (SST) data set, spatiotemporal changes in mean and extreme SST in the East China Seas (ECSs) were examined for from 1982 to 2017. As a regional average, the annual mean SST has notably increased at a rate of 0.21 ± 0.08 °C per decade. The warming SST during 1982–2017 is probably related to the influence from a recent strengthening and westward extension of the WPSH. There are also notable warming trends in annual minimum and maximum SST. Spatially, the rapid warming of annual mean SSTs are located in the vicinity of the Yangtze Estuary, exceeding 0.2 °C per decade and part of the ECS-Kuroshio. This pattern may be largely affected by the spatial changes of minimum SST. Rapid warming of maximum SST can be found across the region, from the northern East China Sea (ECS) to the Bohai Sea. Since 1982, extreme hot days (EHDs) have undergone an obvious increasing trend, at a rate of 15.2 days per decade. Conversely, extreme cold days (ECDs) have been decreasing. Notably, the largest increase of EHDs appears in the western ECS and the Bohai Sea, which both have rich marine ecosystems. The trend of EHDs has a significant relationship to mean SST, suggesting that there will be a further increase in EHDs under continued warming in the ECSs. These findings emphasize the importance and urgency of strategies which should be planned for the adaptation and mitigation of specific types of extreme hot events in this region.
Functional Boundedness of Balleans: Coarse Versions of Compactness
Authors: Banakh Taras , Protasov Igor
Published: March 2019

We survey some results and pose some open problems related to boundedness of real-valued functions on balleans and coarse spaces. Special attention is paid to balleans on groups. The boundedness of functions that respect the coarse structure of a ballean could be considered as a coarse counterpart of pseudo-compactness.
Analysis of Flavonoids Bioactivity for Cholestatic Liver Disease: Systematic Literature Search and Experimental Approaches
Authors: Sánchez-Salgado Juan Carlos , Estrada-Soto Samuel , García-Jiménez Sara , Montes Sergio , Gómez-Zamudio Jaime , Villalobos-Molina Rafael
Published: March 2019

Flavonoids are naturally occurring compounds that show health benefits on the liver. However, there is little investigation about identification and evaluation of new flavonoid-containing drugs for cholestatic liver disease, one of the most common liver illnesses. We aimed to a systematic search regarding efficacy of flavonoids for treatment of cholestatic liver disease, and then evaluate naringenin (NG) as representative flavonoid in an obstructive cholestasis model. We searched for information of experimental and clinical studies in four major databases without time and language limits. Intervention was defined as any flavonoid derivate compared with other flavonoid, placebo, or without comparator. In addition, we evaluated NG on a bile duct-ligated model in order to contribute evidence of its actions. Eleven experimental reports that support the efficacy of flavonoids in cholestatic liver disease were identified. However, there was no homogeneity in efficacy endpoints evaluated and methodology. On the other hand, NG showed beneficial effects by improving specific metabolic (cholesterol and lipoproteins) and liver damage (bilirubin and alkaline phosphatase) biomarkers. The review lacks homogeneous evidence about efficacy of flavonoids in experimental settings, and is susceptible to risk for bias. NG only showed improvements in specific disease biomarkers. More investigation is still needed to determine its potential for drug development.
Fluorescent Carbon Dots Ink for Gravure Printing
Authors: Koutsioukis Apostolos , Belessi Vassiliki , Georgakilas Vasilios
Published: March 2019

In the present article, we describe the use of highly fluorescent carbon dots (CDs) for the preparation of an effective water-based carbon dot ink (CD-ink) for gravure printing. Carbon dots were prepared hydrothermally from citrate and triethylenetetramine, and mixed properly with certain resins that are used in gravure inks. The as-produced CD gravure ink was used successfully for printing high quality fluorescent images.
Direct Synthesis of Ti-Containing CFI-Type Extra-Large-Pore Zeolites in the Presence of Fluorides
Authors: Wang Yichen , Wang Hongjuan , Shao Yuanchao , Li Tianduo , Tatsumi Takashi , Wang Jin-Gui
Published: March 2019

Ti-containing zeolites showed extremely high activity and selectivity in numerous friendly environmental oxidation reactions with hydrogen peroxide as a green oxidant. It will be in high demand to synthesize Ti-containing crystalline extra-large-pore zeolites due to the severe restrictions of medium-pore and/or large-pore zeolites for bulky reactant oxidations. However, the direct synthesis of extra-large-pore Ti-zeolites was still challengeable. Here, we firstly report a strategy to directly synthesize high-performance Ti-containing CFI-type extra-large-pore (Ti-CFI) zeolites assisted with fluorides. The well-crystallized Ti-CFI zeolites with framework titanium species could be synthesized in the hydrofluoric acid system with seed or in the ammonium fluoride system without seed, which showed higher catalytic activity for cyclohexene oxidation than that synthesized from the traditional LiOH system.
The Role of Primary Cilia in the Crosstalk between the Ubiquitin–Proteasome System and Autophagy
Authors: Wiegering Antonia , Rüther Ulrich , Gerhardt Christoph
Published: March 2019

Protein degradation is a pivotal process for eukaryotic development and homeostasis. The majority of proteins are degraded by the ubiquitin–proteasome system and by autophagy. Recent studies describe a crosstalk between these two main eukaryotic degradation systems which allows for establishing a kind of safety mechanism. If one of these degradation systems is hampered, the other compensates for this defect. The mechanism behind this crosstalk is poorly understood. Novel studies suggest that primary cilia, little cellular protrusions, are involved in the regulation of the crosstalk between the two degradation systems. In this review article, we summarise the current knowledge about the association between cilia, the ubiquitin–proteasome system and autophagy.
The Use of Pluripotent Stem Cell-Derived Organoids to Study Extracellular Matrix Development during Neural Degeneration
Authors: Yan Yuanwei , Bejoy Julie , Marzano Mark , Li Yan
Published: March 2019

The mechanism that causes the Alzheimer’s disease (AD) pathologies, including amyloid plaque, neurofibrillary tangles, and neuron death, is not well understood due to the lack of robust study models for human brain. Three-dimensional organoid systems based on human pluripotent stem cells (hPSCs) have shown a promising potential to model neurodegenerative diseases, including AD. These systems, in combination with engineering tools, allow in vitro generation of brain-like tissues that recapitulate complex cell-cell and cell-extracellular matrix (ECM) interactions. Brain ECMs play important roles in neural differentiation, proliferation, neuronal network, and AD progression. In this contribution related to brain ECMs, recent advances in modeling AD pathology and progression based on hPSC-derived neural cells, tissues, and brain organoids were reviewed and summarized. In addition, the roles of ECMs in neural differentiation of hPSCs and the influences of heparan sulfate proteoglycans, chondroitin sulfate proteoglycans, and hyaluronic acid on the progression of neurodegeneration were discussed. The advantages that use stem cell-based organoids to study neural degeneration and to investigate the effects of ECM development on the disease progression were highlighted. The contents of this article are significant for understanding cell-matrix interactions in stem cell microenvironment for treating neural degeneration.
Impact of Climate Change on Twenty-First Century Crop Yields in the U.S.
Authors: Petersen Lillian
Published: March 2019

Crop yields are strongly dependent on the average climate, extreme temperatures, and carbon dioxide concentrations, all of which are projected to increase in the coming century. In this study, a statistical model was created to predict US yields to 2100 for three crops using low and high-emissions future scenarios (RCP 4.5 and 8.5). The model is based on linear regressions between historical crop yields and daily weather observations since 1970 for every county in the US. Yields were found to be most strongly dependent on heat waves, summer average temperatures, and killing degree days; these relationships were hence used to predict future yields. The model shows that warming temperatures will significantly decrease corn and soybean yields, but will not have as strong of an influence on rice. Before accounting for CO2 fertilization, crops in the high-emissions scenario are predicted to produce 77%, 85%, and 96% of their expected yield without climate change for corn, soybeans, and rice, respectively. When a simple CO2 fertilization factor is included, corn, a C4 plant, increases slightly, while the yields of the C3 plants (soybeans and rice) are actually predicted to increase compared to today’s yields. This study exhibits the wide range of possible impacts of climate change on crop yields in the coming century, and emphasizes the need for field research on the combined effects of CO2 fertilization and heat extremes.
Concepts of a Modular System Architecture for Distributed Robotic Systems
Authors: Jahn Uwe , Wolff Carsten , Schulz Peter
Published: March 2019

Modern robots often use more than one processing unit to solve the requirements in robotics. Robots are frequently designed in a modular manner to fulfill the possibility to be extended for future tasks. The use of multiple processing units leads to a distributed system within one single robot. Therefore, the system architecture is even more important than in single-computer robots. The presented concept of a modular and distributed system architecture was designed for robotic systems. The architecture is based on the Operator–Controller Module (OCM). This article describes the adaption of the distributed OCM for mobile robots considering the requirements on such robots, including, for example, real-time and safety constraints. The presented architecture splits the system hierarchically into a three-layer structure of controllers and operators. The controllers interact directly with all sensors and actuators within the system. For that reason, hard real-time constraints need to comply. The reflective operator, however, processes the information of the controllers, which can be done by model-based principles using state machines. The cognitive operator is used to optimize the system. The article also shows the exemplary design of the DAEbot, a self-developed robot, and discusses the experience of applying these concepts on this robot.
The Use of an Artificial Neural Network to Process Hydrographic Big Data during Surface Modeling
Authors: Wlodarczyk-Sielicka Marta , Lubczonek Jacek
Published: March 2019

At the present time, spatial data are often acquired using varied remote sensing sensors and systems, which produce big data sets. One significant product from these data is a digital model of geographical surfaces, including the surface of the sea floor. To improve data processing, presentation, and management, it is often indispensable to reduce the number of data points. This paper presents research regarding the application of artificial neural networks to bathymetric data reductions. This research considers results from radial networks and self-organizing Kohonen networks. During reconstructions of the seabed model, the results show that neural networks with fewer hidden neurons than the number of data points can replicate the original data set, while the Kohonen network can be used for clustering during big geodata reduction. Practical implementations of neural networks capable of creating surface models and reducing bathymetric data are presented.
Impact of Delay Time before Annealing MAI-PbI2-DMSO Intermediate Phase on Perovskite Film Quality and Photo-Physical Properties
Authors: Yao Yujun , Zou Xiaoping , Cheng Jin , Chen Dan , Chang Chuangchuang , Ling Tao , Ren Haiyan
Published: March 2019

High-performance perovskite solar cells are strongly dependent on the quality of the perovskite layer. Two-step sequential deposition of CH3NH3PbI3 (MAPbI3) films is widely used to fabricate perovskite solar cells and many factors influence the quality of perovskite films, such as the delay time before annealing the MAI-PbI2-DMSO intermediate phase, which would impact the morphology and photo-physical properties of perovskite thin films. Here, the experimental research indicates that the impact of the delay time before annealing the MAI-PbI2-DMSO intermediate phase on the quality, crystallinity, and photo-physical properties of perovskite film is crucial. During the delay process, the delay time before annealing the MAI-PbI2-DMSO intermediate phase plays an important role in the nucleation process of perovskite grains inside the intermediate phase. With the extension of the delay time before annealing, the quality of the perovskite film deteriorates, thus the photo-physical properties change. We found that after the localized liquid–liquid diffusion of MAI and PbI2, with the extension of the delay time before annealing the MAI-PbI2-DMSO intermediate phase, the nucleation number of the perovskite grains increases and the grain size becomes smaller. Therefore, with the extension of the delay time before annealing, the device performance deteriorates.
Representative Stress Correlation of Global Scratch Quantities at Scratch Testing: Experimental Verification
Authors: Larsson Per-Lennart
Published: March 2019

Evaluation and correlation of global quantities, i.e., normal and tangential hardness, at scratch testing in the context of a representative stress description was investigated. In particular, verification based on experimental results is at issue. It has been shown previously that within the framework of classical von Mises elasto-plasticity and quasi-static conditions, correlation can be achieved by using a combination of stresses at different levels of plastic strains to define representative quantities at scratching, accounting for the difference in mechanical behavior at elasto-plastic and rigid plastic scratching. However, verification from experimental results is required, which has been attempted in this study. Predictions based on previous theoretical results were compared with experimental findings for polymeric materials, as well as for different metals. Good agreement was found between the two sets of results, particularly so for the case of polymers modelled by von Mises elasto-plasticity. Accordingly, these results are of direct practical, accurate, and novel relevance for semi-crystalline polymers where viscoelastic effects are negligible.
Non-Geodesic Incompleteness in Poincaré Gauge Gravity
Authors: Cembranos José Alberto Ruiz , Valcarcel Jorge Gigante , Torralba Francisco J. Maldonado
Published: March 2019

In this work, we review the study of singularities in Poincaré gauge theories of gravity. Since one of the most recent studies used the appearance of black hole regions of arbitrary dimension as an indicator of singular behavior, we also give some explicit examples of these structures and study how particles behave around them.
Data-Rate Constrained Observers of Nonlinear Systems
Authors: Voortman Quentin , Pogromsky Alexander Yu. , Matveev Alexey S. , Nijmeijer Henk
Published: March 2019

In this paper, the design of a data-rate constrained observer for a dynamical system is presented. This observer is designed to function both in discrete time and continuous time. The system is connected to a remote location via a communication channel which can transmit limited amounts of data per unit of time. The objective of the observer is to provide estimates of the state at the remote location through messages that are sent via the channel. The observer is designed such that it is robust toward losses in the communication channel. Upper bounds on the required communication rate to implement the observer are provided in terms of the upper box dimension of the state space and an upper bound on the largest singular value of the system’s Jacobian. Results that provide an analytical bound on the required minimum communication rate are then presented. These bounds are obtained by using the Lyapunov dimension of the dynamical system rather than the upper box dimension in the rate. The observer is tested through simulations for the Lozi map and the Lorenz system. For the Lozi map, the Lyapunov dimension is computed. For both systems, the theoretical bounds on the communication rate are compared to the simulated rates.
Blackbox Large-Signal Modeling of Grid-Connected DC-AC Electronic Power Converters
Authors: Guarderas Galo , Frances Airan , Ramirez Dionisio , Asensi Rafael , Uceda Javier
Published: March 2019

Modern electric power distribution systems are progressively integrating electronic power converters. However, the design of electronic-power-converter-based systems is not a straightforward task, as the interactions among the different converters can lead to dynamic degradation or instabilities. In addition, electric power distribution systems are expected to consist of commercial-off-the-shelf converters, which implies limited information about the dynamic behavior of the devices. Large-signal blackbox modeling approaches have been proposed in order to obtain accurate dynamic models of commercial converters that can be used for system-level analyses. However, most of the works are focused on DC-DC converters. In this work, a large-signal blackbox model is proposed to model grid-connected three-phase DC-AC converters. An experimental setup has been used to demonstrate the limitations of small-signal models and the capability of the proposed modeling approach to capture the dynamic behavior of the converter when large perturbations are applied. Finally, the automation of the model identification process is discussed.
Short-Term Load Forecasting with Tensor Partial Least Squares-Neural Network
Authors: Feng Yu , Xu Xianfeng , Meng Yun
Published: March 2019

Short-term load forecasting is very important for power systems. The load is related to many factors which compose tensors. However, tensors cannot be input directly into most traditional forecasting models. This paper proposes a tensor partial least squares-neural network model (TPN) to forecast the power load. The model contains a tensor decomposition outer model and a nonlinear inner model. The outer model extracts common latent variables of tensor input and vector output and makes the residuals less than the threshold by iteration. The inner model determines the relationship between the latent variable matrix and the output by using a neural network. This model structure can preserve the information of tensors and the nonlinear features of the system. Three classical models, partial least squares (PLS), least squares support vector machine (LSSVM) and neural network (NN), are selected to compare the forecasting results. The results show that the proposed model is efficient for short-term load and daily load peak forecasting. Compared to PLS, LSSVM and NN, the TPN has the best forecasting accuracy.
Fault Detection of a Spherical Tank Using a Genetic Algorithm-Based Hybrid Feature Pool and k-Nearest Neighbor Algorithm
Authors: Hasan Md Junayed , Kim Jong-Myon
Published: March 2019

Fault detection in metallic structures requires a detailed and discriminative feature pool creation mechanism to develop an effective condition monitoring system. Traditional fault detection methods incorporate handcrafted features either from the time, frequency or time-frequency domains. To explore the salient information provided by the acoustic emission (AE) signals, a hybrid of feature pool creation and an optimal features subset selection mechanism is proposed for crack detection in a spherical tank. The optimal hybrid feature pool creation process is composed of two major parts: (1) extraction of statistical features from time and frequency domains, as well as extraction of traditional features associated with the AE signals; and (2) genetic algorithm (GA)-based optimal features subset selection. The optimal features subset is then provided to the k-nearest neighbor (k-NN) classifier to distinguish between normal (NC) and crack conditions (CC). Experimental results show that the proposed approach yields an average 99.8% accuracy for heath state classification. To validate the effectiveness of the proposed approach, it is compared to conventional non-linear dimensionality reduction techniques, as well as those without feature selection schemes. Experimental results show that the proposed approach outperforms conventional non-linear dimensionality reduction techniques, achieving at least 2.55% higher classification accuracy.
Energy Efficiency Optimization for AF Relaying with TS-SWIPT
Authors: Lu Guangyue , Lei Chan , Ye Yinghui , Shi Liqin , Wang Tianci
Published: March 2019

In this paper, we focus on energy efficiency (EE) maximization for simultaneous wireless information and power transfer (SWIPT) based energy-constrained and amplify-and-forward (AF) relay networks. We adopt low-complexity time-switching (TS) protocol to realize SWIPT at the energy-constrained relay node, and formulate an EE maximization problem in which TS factor and transmit power control are needed to be jointly optimized. Since the formulated problem is non-convex and difficult to solve, we propose an algorithm combining fractional programming and alternating convex optimization to optimize TS factor and transmit power iteratively with low complexity. Simulation results are provided to demonstrate the convergence of the proposed algorithm, as well as the performance gains in terms of EE compared with other existing schemes.
A Model for Multi-Energy Demand Response with Its Application in Optimal TOU Price
Authors: Zhao Nan , Wang Beibei , Wang Mingshen
Published: March 2019

With the generalization of the integrated energy system (IES) on the demand side, multi-energy users may participate in a demand response (DR) program based on their flexible consumption of energy. However, since users could choose using alternative energy or transfer energy consumption to other time periods, obtaining response characteristics of this type of DR usually appears more complicated than traditional single-energy DR. To obtain the response characteristic, a response model for multi-energy DR, which reflects the relations between electricity (gas) response and time-of-use (TOU) electric prices, is proposed. The model is characterized by several coefficients which are associated with electric and heat efficiency. The model is obtained through the derivation process of optimizing user’s energy-using problem. Then, as a typical application of the response model, the TOU electric pricing for multi-energy users is able to be formulated by an interior point algorithm after giving the Kuhn-Tucker conditions of the optimal problem. Typical results of the optimal TOU pricing are further illustrated through the formulation on a PJM five-bus test system. It demonstrates that optimal TOU pricing can be effectively pre-calculated by the utility company using the proposed response model.
A Dynamic Adam Based Deep Neural Network for Fault Diagnosis of Oil-Immersed Power Transformers
Authors: Ou Minghui , Wei Hua , Zhang Yiyi , Tan Jiancheng
Published: March 2019

This paper presents a Dynamic Adam and dropout based deep neural network (DADDNN) for fault diagnosis of oil-immersed power transformers. To solve the problem of incomplete extraction of hidden information with data driven, the gradient first-order moment estimate and second-order moment estimate are used to calculate the different learning rates for all parameters with stable gradient scaling. Meanwhile, the learning rate is dynamically attenuated according to the optimal interval. To prevent over-fitted, we exploit dropout technique to randomly reset some neurons and strengthen the information exchange between indirectly-linked neurons. Our proposed approach was utilized on four datasets to learn the faults diagnosis of oil-immersed power transformers. Besides, four benchmark cases in other fields were also utilized to illustrate its scalability. The simulation results show that the average diagnosis accuracies on the four datasets of our proposed method were 37.9%, 25.5%, 14.6%, 18.9%, and 11.2%, higher than international electro technical commission (IEC), Duval Triangle, stacked autoencoders (SAE), deep belief networks (DBN), and grid search support vector machines (GSSVM), respectively.
Cost-Optimal Maintenance Planning for Defects on Wind Turbine Blades
Authors: Yang Yi , Sørensen John Dalsgaard
Published: March 2019

Due to the considerable increase in clean energy demand, there is a significant trend of increased wind turbine sizes, resulting in much higher loads on the blades. The high loads can cause significant out-of-plane deformations of the blades, especially in the area nearby the maximum chord. This paper briefly presents a discrete Markov chain model as a simplified probabilistic model for damages in wind turbine blades, based on a six-level damage categorization scheme applied by the wind industry, with the aim of providing decision makers with cost-optimal inspection intervals and maintenance strategies for the aforementioned challenges facing wind turbine blades. The in-history inspection information extracted from a database with inspection information was used to calibrate transition probabilities in the discrete Markov chain model. With the calibrated transition probabilities, the damage evolution can be statistically simulated. The classical Bayesian pre-posterior decision theory, as well as condition-based maintenance strategy, was used as a basis for the decision-making. An illustrative example with transverse cracks is presented using a reference wind turbine.
System Configuration, Fault Detection, Location, Isolation and Restoration: A Review on LVDC Microgrid Protections
Authors: Javed Waqas , Chen Dong , Farrag Mohamed Emad , Xu Yan
Published: March 2019

Low voltage direct current (LVDC) distribution has gained the significant interest of research due to the advancements in power conversion technologies. However, the use of converters has given rise to several technical issues regarding their protections and controls of such devices under faulty conditions. Post-fault behaviour of converter-fed LVDC system involves both active converter control and passive circuit transient of similar time scale, which makes the protection for LVDC distribution significantly different and more challenging than low voltage AC. These protection and operational issues have handicapped the practical applications of DC distribution. This paper presents state-of-the-art protection schemes developed for DC Microgrids. With a close look at practical limitations such as the dependency on modelling accuracy, requirement on communications and so forth, a comprehensive evaluation is carried out on those system approaches in terms of system configurations, fault detection, location, isolation and restoration.
Effect of Different Interval Lengths in a Rolling Horizon MILP Unit Commitment with Non-Linear Control Model for a Small Energy System
Authors: Erichsen Gerrit , Zimmermann Tobias , Kather Alfons
Published: March 2019

In this paper, a fixed electricity producer park of both a short- and long-term renewable energy storage (e.g., battery, power to gas to power) and a conventional power plant is combined with an increasing amount of installed volatile renewable power. For the sake of simplicity, the grid is designed as a single copper plate with island restrictions and constant demand of 1000 MW; the volatile input is deducted from scaled 15-min input data of German grid operators. A mixed integer linear programming model is implemented to generate an optimised unit commitment (UCO) for various scenarios and configurations using CPLEX® as the problem solver. The resulting unit commitment is input into a non-linear control model (NLC), which tries to match the plan of the UCO as closely as possible. Using the approach of a rolling horizon the result of the NLC is fed back to the interval of the next optimisation run. The problem’s objective is set to minimise CO2 emissions of the whole electricity producer park. Different interval lengths are tested with perfect foresight. The results gained with different interval lengths are compared to each other and to a simple heuristic approach. As non-linear control model a characteristic line model is used. The results show that the influence of the interval length is rather small, which leads to the conclusion that realistic forecast lengths of two days can be used to achieve not only a sufficient quality of solutions, but shorter computational times as well.
Effect of LaNi3 Amorphous Alloy Nanopowders on the Performance and Hydrogen Storage Properties of MgH2
Authors: El-Eskandarany M. , Saeed Maryam , Al-Nasrallah Eissa , Al-Ajmi Fahad , Banyan Mohammad
Published: March 2019

Due to its affordable price, abundance, high storage capacity, low recycling coast, and easy processing, Mg metal is considered as a promising hydrogen storage material. However, the poor de/rehydrogenation kinetics and strong stability of MgH2 must be improved before proposing this material for applications. Doping MgH2 powders with one or more catalytic agents is one common approach leading to obvious improving on the behavior of MgH2. The present study was undertaken to investigate the effect of doping MgH2 with 7 wt% of amorphous(a)-LaNi3 nanopowders on hydrogenation/dehydrogenation behavior of the metal hydride powders. The results have shown that rod milling MgH2 with a-LaNi3 abrasive nanopowders led to disintegrate microscale-MgH2 powders to nanolevel. The final nanocomposite product obtained after 50 h–100 h of rod milling revealed superior hydrogenation kinetics, indexed by short time (8 min) required to absorb 6 wt% of H2 at 200 °C/10 bar. At 225 °C/200 mbar, nanocomposite powders revealed outstanding dehydrogenation kinetics, characterized by very short time (2 min) needed to release 6 wt% of H2. This new tailored solid-hydrogen storage system experienced long cycle-life-time (2000 h) at 225 °C without obeying to sever degradation on its kinetics and/or storage capacity.