nils-herrmann/clean_scirepeval huggingface dataset:
Network forensics: Review, taxonomy, and open challenges
Venue: J. Netw. Comput. Appl.
Year: 2016

In recent years, a number of network forensics techniques have been proposed to investigate the increasing number of cybercrimes. Network forensics techniques assist in tracking internal and external network attacks by focusing on inherent network vulnerabilities and communication mechanisms. However, investigation of cybercrime becomes more challenging when cyber criminals erase the traces in order to avoid detection. Therefore, network forensics techniques employ mechanisms to facilitate investigation by recording every single packet and event that is disseminated into the network. As a result, it allows identification of the origin of the attack through reconstruction of the recorded data. In the current literature, network forensics techniques are studied on the basis of forensic tools, process models and framework implementations. However, a comprehensive study of cybercrime investigation using network forensics frameworks along with a critical review of present network forensics techniques is lacking. In other words, our study is motivated by the diversity of digital evidence and the difficulty of addressing numerous attacks in the network using network forensics techniques. Therefore, this paper reviews the fundamental mechanism of network forensics techniques to determine how network attacks are identified in the network. Through an extensive review of related literature, a thematic taxonomy is proposed for the classification of current network forensics techniques based on its implementation as well as target data sets involved in the conducting of forensic investigations. The critical aspects and significant features of the current network forensics techniques are investigated using qualitative analysis technique. We derive significant parameters from the literature for discussing the similarities and differences in existing network forensics techniques. The parameters include framework nature, mechanism, target dataset, target instance, forensic processing, time of investigation, execution definition, and objective function. Finally, open research challenges are discussed in network forensics to assist researchers in selecting the appropriate domains for further research and obtain ideas for exploring optimal techniques for investigating cyber crimes.
Manajemen Daya Listrik dengan Sistem Automatic Transfer and Synchronization Switch berbasis PLC
Year: 2015

In the current electric energy supply crisis, Indonesian Government encourages the citizen to save electric energy. Therefore, we should control the electric power consumption in the offices or houses intelligently. Using one of automation technologies, Programmable Logic Controller (PLC) we can control electricity usage in our surroundings. This research focuses on the development of Automatic Transfer Switch (ATS) system to become Automatic Transfer and Synchonization Switch (ATSS) The system can monitor electric power consumption connected to PLN. If the electric power consumption has reached 80% then the generator as electric energy back up supply will support in a synchronized way. If electric power load is 80% maka generator sebagai suplai energi listrik cadangan akan membantu dengan cara sinkronisasi. Bila daya beban berkurang kembali menjadi 80% secara otomatis generator dinonaktifkan. Sistem ATSS ini juga dapat berfungsi sebagai ATS yaitu sebagai suplai cadangan bila suplai PLN terputus. Dari hasil pengujian diketahui daya listrik PLN sebesar 900 watt jika dibebani maksimum 1.060 watt, dengan bantuan generator 300 watt cadangan dengan cara disinkron mampu memikul daya beban sampai dengan 1.450 watt.
Research on autonomous collision avoidance of merchant ship based on inverse reinforcement learning
Year: 2020

To learn the optimal collision avoidance policy of merchant ships controlled by human experts, a finite state Markov decision process model for ship collision avoidance is proposed based on the analysis of collision avoidance mechanism, and an inverse reinforcement learning (IRL) method based on cross entropy and projection is proposed to obtain the optimal policy from expert's demonstrations. Collision avoidance simulations in different ship encounters are conducted and the results show that the policy obtained by the proposed IRL has a good inversion effect on two kinds of human experts, which indicate that the proposed method can effectively learn the policy of human experts for ship collision avoidance.
Impact of quality management practices on quality performance and financial performance: evidence from Indian manufacturing companies
Year: 2016

The 'quality performance financial performance' relationship has been significantly studied in managerial literature. However, no definite quantification has been given regarding its type. This study aims to explore the relationship between quality management (QM) practices, quality performance and financial performance of the manufacturing firm. First, critical QM practices have been identified and classified into categories. Then, a structural model linking these practices, quality performance and financial performance factors has been proposed and empirically tested. The empirical data were obtained from a questionnaire based survey of 152 Indian manufacturing companies. After the data were collected, the scales were purified using loading values and composite reliability. The resultant purified scales were then tested for convergent validity through partial least square path modelling using Visual PLS software. The result showed a positive relationship between QM practices, quality performance and financial performance. In addition, the result illustrates the direct impact of quality performance on financial performance.
Decoupling Control of Bearingless Induction Motor Based on LS SVM Inverse System
Year: 2014

According to the strong coupling between the electromagnetic torque and radial suspension force, and the difficulty of establishing a precise mathematical model of bearingless induction motor, least squares support vector machine is proposed in this paper. The inverse model approximated by the LS SVM is connected with the original system, decoupling a complex nonlinear multivariable system into four relatively independent pseudo linear sub systems of single input and single output. At the same time, fuzzy PID control strategy is introduced to the pseudo linear system to ensure the robustness and anti jamming ability of the control system. Then the performance is simulated with Matlab/ Simulink. The theory research and simulation experiment have validated that the decoupling control of inverse system based on least squares support vector machine method can be successfully realized, which between the electromagnetic torque and radial suspension force, and the good performance of dynamic and static state of system can be also obtained.
Uncertainty analysis of hygrometer obtained water activity measurements of saturated salt slurries and food materials.
Year: 2009

Water activity is a critical food stability parameter. Thus, assessment of the uncertainty associated with the instruments and measurement procedures used to obtain a w data is critical and can be accomplished using uncertainty analysis. Uncertainty analysis was applied to a w data obtained for two saturated salt slurries (potassium acetate and potassium chloride) and two food materials (corn flakes and grape jam) at 25 degC using a commercially available dew point hygrometer, the AquaLab 3TE. Sources of uncertainty investigated included sample and dew point temperatures, sample lot, cup volume, and sample preparation "as is" or ground) and day to day changes. Uncertainty analysis revealed that the magnitude of the different sources of uncertainty depended on material type, but that the dew point hygrometer instrument uncertainty was always significantly smaller than each of the other sources of uncertainty investigated, except for jam cup volume, which was exceeding small. Uncertainty analysis also revealed that dew point hygrometer accuracy was better than the 0.003 a w value reported by the manufacturer. Measurement procedures were identified that could be implemented to reduce a w measurement uncertainty for corn flake and jam food materials. The uncertainty analysis used herein can also be applied to investigate other food materials and/or instruments.
Anti Inflammatory Effects of Cumin Essential Oil by Blocking JNK, ERK, and NF kB Signaling Pathways in LPS Stimulated RAW 264.7 Cells
Venue: Evidence based complementary and alternative medicine eCAM
Year: 2015

Cumin seeds (Cuminum cyminum L. have been commonly used in food flavoring and perfumery. In this study, cumin essential oil (CuEO) extracted from seeds was employed to investigate the anti inflammatory effects in lipopolysaccharide (LPS stimulated RAW 264.7 cells and the underlying mechanisms. A total of 26 volatile constituents were identified in CuEO by GC MS, and the most abundant constituent was cuminaldehyde (48.773% Mitochondrial respiration dependent 3 (4,5 dimethylthiazol 2 yl) 2,5 diphenyltetrazolium (MTT) reduction assay demonstrated that CuEO did not exhibit any cytotoxic effect at the employed concentrations (0.0005 0.01% Real time PCR tests showed that CuEO significantly inhibited the mRNA expressions of inducible nitric oxide synthase (iNOS) cyclooxygenase (COX 2) interleukin (IL 1, and IL 6. Moreover, western blotting analysis revealed that CuEO blocked LPS induced transcriptional activation of nuclear factor kappa B (NF kB) and inhibited the phosphorylation of extracellular signal regulated kinase (ERK) and c Jun N terminal kinase (JNK) These results suggested that CuEO exerted anti inflammatory effects in LPS stimulated RAW 264.7 cells via inhibition of NF kB and mitogen activated protein kinases ERK and JNK signaling; the chemical could be used as a source of anti inflammatory agents as well as dietary complement for health promotion.
AI for humanitarian action: Human rights and ethics
Venue: International Review of the Red Cross
Year: 2020

Artificial intelligence (AI) supported systems have transformative applications in the humanitarian sector but they also pose unique risks for human rights, even when used with the best intentions. Drawing from research and expert consultations conducted across the globe in recent years, this paper identifies key points of consensus on how humanitarian practitioners can ensure that AI augments rather than undermines human interests while being rights respecting. Specifically, these consultations emphasized the necessity of an anchoring framework based on international human rights law as an essential baseline for ensuring that human interests are embedded in AI systems. Ethics, in addition, can play a complementary role in filling gaps and elevating standards above the minimum requirements of international human rights law. This paper summarizes the advantages of this framework, while also identifying specific tools and best practices that either already exist and can be adapted to the AI context, or that need to be created, in order to operationalize this human rights framework. As the COVID crisis has laid bare, AI will increasingly shape the global response to the world's toughest problems, especially in the development and humanitarian sector. To ensure that AI tools enable human progress and contribute to achieving the Sustainable Development Goals, humanitarian actors need to be proactive and inclusive in developing tools, policies and accountability mechanisms that protect human rights.
Reproducible Research is more than Publishing Research Artefacts: A Systematic Analysis of Jupyter Notebooks from Research Articles
Venue: ArXiv
Year: 2019

With the advent of Open Science, researchers have started to publish their research artefacts (i. e. data, software, and other products of the investigations) in order to allow others to reproduce their investigations. While this publication is beneficial for science in general, it often lacks a comprehensive documentation and completeness with respect to the artefacts. This, in turn, prevents the successful reproduction of the analyses. Typical examples are missing scripts, incomplete datasets or specification of used software. Moreover, issues about licences often create legal concerns. This is true for the use of commercial software but also for the publication of research artefacts without proper sharing licence. As a result, the sole publication of research artefacts does not automatically result in reproducible research. To empirically confirm this, we have been systematically analysing research publications that also published their investigations as Jupyter notebooks. In this paper, we present preliminary results of this analysis for five publications. The results show, that the quality of the published research artefacts must be improved in order to assure reproducibility.
Prospective EFL Teachers' Perceptions of ICT Integration: A Study of Distance Higher Education in Turkey
Venue: J. Educ. Technol. Soc.
Year: 2012

This paper aims to investigate the perceptions of prospective EFL teachers in the distance higher education system toward ICT implementation in teaching English as a foreign language. The majority of respondents who expressed negative attitudes to ICT integration found the nature, level and delivery of the training inadequate and accordingly affirmed that they do not feel sufficiently competent to use ICT in their future subject teaching without having sufficient prior knowledge of ICT dissemination. The results of the study imply that training that will enable teachers to become competent in and receptive to ICT is quite critical in distance education realms.
Structure Topology Optimization Design of Brake Pad in Large Megawatt Wind Turbine Disc Brake
Year: 2015

The brake pad of disc brake, as an actuator while wind turbine braking, plays an important role in braking system. For seeking an optimum structure of brake pad, its mechanical model during braking process of large megawatt wind turbine in actual working circumstance is established in this paper. Accordingly, model of topology optimization is figured out. Based on the results of topological optimization, a new structure of brake pad is analyzed and a new design plan combined with actual working circumstance is suggested. Testing about new structure which has been done in this paper assures the accuracy.
A drone based networked system and methods for combating coronavirus disease (COVID 19) pandemic
Venue: Future Generation Computer Systems
Year: 2020

Coronavirus disease (COVID 19) is an infectious disease caused by a newly discovered coronavirus. It is similar to influenza viruses and raises concerns through alarming levels of spread and severity resulting in an ongoing pandemic worldwide. Within eight months (by August 2020) it infected 24.0 million persons worldwide and over 824 thousand have died. Drones or Unmanned Aerial Vehicles (UAVs) are very helpful in handling the COVID 19 pandemic. This work investigates the drone based systems, COVID 19 pandemic situations, and proposes an architecture for handling pandemic situations in different scenarios using real time and simulation based scenarios. The proposed architecture uses wearable sensors to record the observations in Body Area Networks (BANs) in a push pull data fetching mechanism. The proposed architecture is found to be useful in remote and highly congested pandemic areas where either the wireless or Internet connectivity is a major issue or chances of COVID 19 spreading are high. It collects and stores the substantial amount of data in a stipulated period and helps to take appropriate action as and when required. In real time drone based healthcare system implementation for COVID 19 operations, it is observed that a large area can be covered for sanitization, thermal image collection, and patient identification within a short period (2 KMs within 10 min approx. through aerial route. In the simulation, the same statistics are observed with an addition of collision resistant strategies working successfully for indoor and outdoor healthcare operations. Further, open challenges are identified and promising research directions are highlighted.
Magmas Overexpression Inhibits Staurosporine Induced Apoptosis in Rat Pituitary Adenoma Cell Lines
Venue: PloS one
Year: 2013

Magmas is a nuclear gene that encodes for the mitochondrial import inner membrane translocase subunit Tim16. Magmas is overexpressed in the majority of human pituitary adenomas and in a mouse ACTH secreting pituitary adenoma cell line. Here we report that Magmas is highly expressed in two out of four rat pituitary adenoma cell lines and its expression levels inversely correlate to the extent of cellular response to staurosporine in terms of apoptosis activation and cell viability. Magmas over expression in rat GH/PRL secreting pituitary adenoma GH4C1 cells leads to an increase in cell viability and to a reduction in staurosporine induced apoptosis and DNA fragmentation, in parallel with the increase in Magmas protein expression. These results indicate that Magmas plays a pivotal role in response to pro apoptotic stimuli and confirm and extend the finding that Magmas protects pituitary cells from staurosporine induced apoptosis, suggesting its possible involvement in pituitary adenoma development.
A Robust Intrusion Detection System using Ensemble Machine Learning
Venue: 2020 IEEE International Women in Engineering (WIE) Conference on Electrical and Computer Engineering (WIECON ECE)
Year: 2020

In today's world there is a rising need for network attack analysis because of rising cyber threats and attacks worldwide. Network traffic, if monitored dynamically in real time could prevent a big cyber attack or even alert before. In this paper, UNSW NB 15 dataset is used on Ensemble method to analyze the network traffic. The major contribution of this paper is the novel Algorithms powered by boosting algorithm to come up with the best classifier from the list of classifiers. It compares the classifier in terms of accuracy as well as training time which is significant in real time analysis of network traffic. We performed experiment in which we took 10 classifiers and our proposed algorithm came up with XGB Classifier as the best one from the set in terms of accuracy and training time combined. We have demonstrated the comparison between running time of complete experiment on Central Processing Unit (CPU) and Graphical Processing Unit GPU)
Detection of infectious spleen and kidney necrosis virus (ISKNV) and turbot reddish body iridovirus (TRBIV) from archival ornamental fish samples.
Venue: Diseases of aquatic organisms
Year: 2016

Although infections caused by megalocytiviruses have been reported from a wide range of finfish species for several decades, molecular characterisation of the viruses involved has been undertaken only on more recent cases. Sequence analysis of the major capsid protein and adenosine triphosphatase genes is reported here from formalin fixed, paraffin embedded material from 2 archival ornamental fish cases from 1986 and 1988 in conjunction with data for a range of genes from fresh frozen tissues from 5 cases obtained from 1991 through to 2010. Turbot reddish body iridovirus (TRBIV) genotype megalocytiviruses, previously not documented in ornamental fish, were detected in samples from 1986, 1988 and 1991. In contrast, megalocytiviruses from 1996 onwards, including those characterised from 2002, 2006 and 2010 in this study, were almost indistinguishable from infectious spleen and kidney necrosis virus (ISKNV) Three of the species infected with TRBIV like megalocytiviruses from 1986 to 1991, viz. dwarf gourami Trichogaster lalius (formerly Colisa lalia) freshwater angelfish Pterophyllum scalare and oscar Astronotus ocellatus, were infected with ISKNV genotype megalocytiviruses from 2002 to 2010. The detection of a TRBIV genotype isolate in ornamental fish from 1986 represents the index case, confirmed by molecular sequence data, for the genus Megalocytivirus.
Service Dominant Logic as a Foundation for Service Science: Clarifications
Year: 2009

Service science is an emerging discipline concerned with the evolution, interaction, and reciprocal cocreation of value among service systems (Maglio and Spohrer [Maglio, P. P. J. Spohrer. 2008.  18 20. Spohrer et al. [Spohrer, J. S. Vargo, N. Caswell, P. Maglio. 2008. The Service System is the Basic Abstraction of Service Science. 41st Annual  Service dominant (S D) logic (Vargo and Lusch [Vargo, S. R. F. Lusch. 2004a. Evolving to a New Dominant Logic for Marketing. Journal of Marketing 68(1) 1 17. [Vargo, S. R. F. Lusch.  1 10. is an alternative to the traditional, goods dominant (G D) paradigm for understanding economic exchange and value creation. This service centered view is based on the idea that service the application of competences for the benefit of another is the ba.
Pressure promoted low temperature melting of metal organic frameworks
Venue: Nature Materials
Year: 2019

abstractMetal organic frameworks (MOFs) are microporous materials with huge potential for chemical processes. Structural collapse at high pressure, and transitions to liquid states at high temperature, have recently been observed in the zeolitic imidazolate framework (ZIF) family of MOFs. Here, we show that simultaneous high pressure and high temperature conditions result in complex behaviour in ZIF 62 and ZIF 4, with distinct high and low density amorphous phases occurring over different regions of the pressure temperature phase diagram. In situ powder X ray diffraction, Raman spectroscopy and optical microscopy reveal that the stability of the liquid MOF state expands substantially towards lower temperatures at intermediate, industrially achievable pressures and first principles molecular dynamics show that softening of the framework coordination with pressure makes melting thermodynamically easier. Furthermore, the MOF glass formed by melt quenching the high temperature liquid possesses permanent, accessible porosity. Our results thus imply a route to the synthesis of functional MOF glasses at low temperatures, avoiding decomposition on heating at ambient pressure.The simultaneous high pressure and high temperature phase diagram of two MOFs, ZIF 4 and ZIF 62, is mapped. Crystalline, pressure and temperature amorphous, and liquid states are found, while melting temperature is found to decrease with pressure.
Mobile Serious Game Design using User Experience: Modeling of Software Product Line Variability
Venue: iJET
Year: 2019

In recent years, gamification has emerged as a new approach to increasing learner engagement. It covers a very wide range of games with very different purposes and with many fields of application. However, most of the gamification solutions proposed do not adopt the same modeling approach and little attention has been paid to mobile serious games (MSG) belonging to different pedagogical contexts. In order to overcome these difficulties, we have developed in this paper a generic model based on the Software Product Line (SPL) approach to manage the common and variable points of the MSG product set. We have also focused on the User eXperience (UX) concept to study the aspects that most affect the player's experience in the context of MSGs. These aspects have been modeled in the form of features in the SPL Feature Model. MSG designers can use the model proposed during the development process, both to manage variability and to create an effective and fun learning environment.