Miracle-dz/UniFAR-FTUs huggingface dataset:
Inter-Firm Linkages and Learning. An Empirical Exploration of Firms in the Third World

The main purpose of this study is to contribute to a better understanding of how inter-firm linkages determine the conditions for firm learning. The overall objective is to explore the relationship between the organizing of linkages and the process of accumulating capability. These goals are achieved by focusing on the analysis of how a firm's diverse set of linkages affects the conditions for learning. The conceptual framework developed differentiates between three types of inter-firm linkages; activity coordinating, resource combining, and actor connecting. Learning, defined as the process of capability accumulation, is assumed to be related to the nature and pattern of a firm's linkages. In order to link the framework with real life phenomena, the methodology of the study reflects a hermeneutic approach which emphasizes understanding and interpretation rather than verification of theories and hypotheses. For the sake of `understanding' three case studies from firms in Kenya and Tanzania are presented that explore the different roles of various types of linkages in determining conditions facilitating or constraining learning. The main assumption that a firm's linkages comprise a precondition for learning has proven fruitful, in the light of the study's empirical findings. The study points to the central influence on capability accumulation of establishing different types of linkages. The cases reveal that the firms had a diverse and differentiated set of linkages. These were typically manifested in market-like relationships with other local firms, whereas linkages to international firms were of relational nature. Actual linkage formation is explained as the result of firms' efforts, which in an interactive fashion, are linked to the type of opportunity provided to firms. However, this is to a great extent the perceived set of opportunity from the perspective of a firm rather than the actual reality. The study concludes that the prevalent way of organizing inter-firm linkages has created vicious circles which should be seen as a challenge to policy makers to counter negative effects.
2020 5th International Conference on Mechanical, Control and Computer Engineering (ICMCCE)

Convolutional neural network is very important for super-resolution reconstruction of face images. However, deeper convolutional networks are more difficult to train for face superresolution reconstruction. The input low-resolution face images contain a wealth of low-frequency information, these lowfrequency information is processed equally in the channel, which hinders the characterization ability of the convolutional neural network, sequentially the recovery performance is affected, so that the super-resolution reconstruction results obtained are inaccurate. In order to solve these problems, we propose a residual convolution network with a compact structure. Specifically, we propose a modified residual structure group to deepen the network structure. In the residual structure group, the compact and dense connection structure is combined to make full use of the high frequency information learned by the previous network, and the features of the shallow small perception field are transmitted to the network to complete the specific task. In addition, we introduce an attentional mechanism for adaptive re-estimation of channel characteristics by considering the dependencies between channels. Experiment results show that the proposed network achieves better accuracy and satisfactory visual effect. Keywords-Face Image Super-Reconstruction; Channel Attention; Residual in Residual; Dense Connection Structure
Solar Tracking System Installed with photovoltaic (PV) Panels to Connection Grid Tie Low Voltage (Sunflower)

The electricity is an essential factor in everyday society, and this consumption is increasing exponentially. Beyond this fact, there is also concern about the impacts suffered by the environment, caused by the current system of generation electric power system. Systems for solar, renewable and clean energy is one of the most used and implemented around the globe. This article presents a proposal for a solar tracking system installed with photovoltaic (PV) panels to connection Grid Tie low voltage, named Sunflower. The main content of this research focuses on the operating principles of Sunflower, as well as the development of a prototype Sunflower in reduced scale. The principal experiment focuses on tests between the Sunflower prototype and photovoltaic (PV) panels, to compare the efficiency of solar tracking. The deductions, based on the research tests, confirm that the Sunflower prototype is more efficient than photovoltaic (PV) panel. Furthermore, the cost of energy production is close to the price of electricity, for residential customers in Brazil.
Finite Element Analysis of Soft-Body Impact

Abstract : This report describes the development of analytical and numerical methods for determining the dynamic structural response caused by soft body impact. The prediction of stress and deflection behavior of aircraft transparencies due to collisions with birds is the primary area of application. When the structure is relatively flexible, such an impact involves strong coupling between the dynamic motion of the colliding bodies. The developed techniques use appropriate finite element methods in each region, together with a contact solution algorithm, to compute the coupled structural response, while the soft-body motions are integrated using a simpler explicit technique. The soft body dynamic analysis uses a Lagrangian description to track the free surface and impact region accurately, with an automatic rezoning procedure to correct large mesh distortions. Originator supplied keywords; Nonlinear structural analysis; Finite element method; Soft body impact; Hydrodynamic impact; Aircraft transparency; Impact loading; MAGNA computer program.
Design of System for Determining Corn Seed Color Quality Standards using the Fuzzy Logic Method through the Localhost Network

Control of quality standards is very important role in ensuring corn on the market. Corn seed quality standards are determined from the results of classification process applied. So far, evaluation process of classification of corn seeds quality is still done manually which takes a long time and the quality of product is'nt evenly distributed. So, we need a tool to determine corn seeds quality to improve its quality. This study conducted color readings of corn seeds using TCS230 color sensors and sorting diameter of corn seeds using a small, medium, and large diameter sieve machine. The method for classifying quality standard of corn seed color uses fuzzy logic. The test was carried out by taking data from 3 TCS230 color sensors on each diameter of the sieve machine for corn seeds types used are BISI-2 and BIMA-19. The sensor accuracy is known by comparing data from sensor with data from Color Grab application. The reading results of BISI-2 on the color sensor-1 shows an accuracy rate of 0.3%, the color sensor-2 shows an accuracy rate of 0.72%, and the color sensor-3 shows an accuracy rate of 1.76%. For BIMA-19 corn seeds, the reading on color sensor-1 shows an accuracy of 1.11%, the color sensor-2 shows an accuracy of 24.6%, the color sensor-3 shows an accuracy of 1.10%. The results of fuzzy testing on BISI-2 and BIMA-19 showed that quality standard of maize seeds was good at medium and large diameters, while those on small diameters showed poor quality standards.
Conduction invasion noise in nanoparticle WO3/Au thin-film devices for gas sensing application

Conduction noise measurements were carried out in the 0.3–45 Hz frequency range on Au films covered by a thin layer of tungsten trioxide (WO3) nanoparticles. Exposing the films to alcohol vapor resulted in a gradually increased noise intensity which went through a maximum after an exposure time of the order of 15 min. The maximum noise intensity could increase by several orders of magnitude above the initial level. Longer exposure times made the noise decrease and approach its original value. This effect was not observed in the absence of WO3 nanoparticles. The phenomenon is discussed in terms of a new 'invasion noise' model in which the noise is related to the insertion and extraction of mobile chemical species.
Military Performance and Health Monitoring in Extreme Environments

Abstract : The Netherlands Defence Organization aims at an optimal deployment of their personnel. However, during missions such as in Afghanistan soldiers encounter adverse and extreme environments and have to sustain their performance for several days, sometimes approaching or exceeding the limits of their capabilities and health. Therefore, in 2008 a 4-year Defense Research Program was initiated on 'Military Performance and Health Monitoring'. This program aims at developing knowledge on physical and cognitive sustainability during military operations in extreme environments. In return this knowledge will be used to develop (real-time) performance and health monitoring systems for individual operational readiness. To judge individual operational readiness, commanders merely have to rely on subjective observations. Technological developments enable (real-time) assessment of the physical and cognitive state of individual soldiers under operational circumstances. To define and predict individual readiness, commanders can benefit from decision support tools. Knowledge from NATO HFM-132 (RTG) was used to define and develop a mobile field lab to assess physiological and cognitive performance during military operations. Combined with environmental data and observational measures, this field lab has been applied to gather data during training courses for the Air Mobile Brigade and the Marines. These data and data from future investigations will be used to build a multi-parameter model for predicting operational readiness. This model will serve as the basis for the commander support tool. Furthermore research will be done on new ambulatory measurement techniques as well as the validation of applied methods using gold standards and laboratory research. Other topics covered in this research program are; the data-processing, the user interface, and the presentation of information to the user. The research program will also address issues as operational feasibility, ethical consideration
Model predictive control for time-optimal point-to-point motion control

Abstract This paper presents a time-optimal model predictive control approach, which is a new type of MPC approach for motion systems that aims at performing time-optimal point-to-point motions. It is shown how the structure of the underlying optimal control problem can be exploited such that it can be solved in real-time at a sampling rate of 200 Hz. Numerical and experimental validation on a linear motor drive system and comparison with traditional MPC and linear control techniques clearly demonstrate the advantages of time-optimal model predictive control.
Agile-Lean Software Engineering (ALSE) Evaluating Kanban in Systems Engineering

Abstract : This research project evaluates the use of on-demand (pull or kanban) scheduling approaches in systems engineering (SE). Such approaches have been seen to be valuable in software system development. In particular, the research focuses on SE where rapid response software development projects incrementally evolve capabilities of existing systems and/or systems of systems. Phase I considered the problem and possible applications of alternative scheduling methods and suggested possible outcomes of on-demand scheduling coupled with a service-oriented approach to SE. It defined a conceptual model and developed initial simulations to capture the model and better understand the impact. Phase II focuses on applying the method to multi-level service-based SE in complex systems of systems. Using the models and simulations from Phase I, Phase II defines a prototype network of kanban-based scheduling systems (KSS) for a target environment based on a large multi-facility hospital system. The definition is simulated to demonstrate its behavior. Follow on work is planned to use the prototype in comparing performance with traditional SE methods. This will enable determination if SE functions are accomplished more effectively and efficiently, whether the overall value of the systems of systems over time is increased, and whether other expected results are fulfilled.
Influence factors of two dimensional position map on photomultiplier detector block designed by quadrant sharing technique

Abstract The position decoding accuracy and the spatial resolution of positron emission tomography detectors are greatly influenced by the performance of the two-dimensional position map, including the gain uniformity of photomultiplier tube (PMT), the baseline offset of the PMT signals and the accuracy of analogue to digital converter (ADC). In this work, a PMT-quadrant sharing detector was designed. Two data acquisition platforms are employed to conduct the influence factors on the two-dimensional position map performances, one was that the waveforms of the PMT signals were scanned by the sequence acquisition mode based on the oscilloscope of LeCroy waveRunner 204MXi-A, and another was a self-developed high speed ADC data acquisition module. Results show that the event decoding positions were concentrated on the PMT with higher gain, the position map was distorted at the baseline offset of signal, and the cross-line artifacts were caused by the insufficient ADC sampling bit for a larger size position map. All the parameters need be adjusted properly to stabilize a real system, and the flexible oscilloscope platform can be used to design the detector block and the other platform with high ADC accuracy. Likely, the electrical circuit with a proper ADC accuracy adjusts the PMT gains and baseline offsets.
Marcus-Hush Theory Revealed by Electron Tunneling Through Hexagonal Boron Nitride

Marcus-Hush theory of electron transfer is one of the pillars of modern electrochemistry with a large body of supporting experimental evidence presented to date. However, some predictions, such as the electrochemical behavior at microdisk electrodes, remain unverified. Herein, we present a study of electron tunneling across a hexagonal boron nitride barrier between a graphite electrode and redox levels in a liquid solution. This was achieved by the fabrication of microdisk electrodes with a typical diameter of 5 µm. Analysis of voltammetric measurements, using two common redox mediators, yielded several electrochemical parameters, including the electron transfer rate constant, limiting current, and transfer coefficient. They show a significant departure from the Butler-Volmer behavior in a clear manifestation of the Marcus-Hush theory of electron transfer. In addition, our system provides a novel experimental platform, which could be applied to address a number of scientific problems such as identification of reaction mechanisms, surface modification, or long-range electron transfer.
Security wireless sensor networks: prospects, challenges, and future

With the advancements of networking technologies and miniaturization of electronic devices, wireless sensor network (WSN) has become an emerging area of research in academic, industrial, and defense sectors. Different types of sensing technologies combined with processing power and wireless communication capability make sensor networks very lucrative for their abundant use in near future. However, many issues are yet to be solved before their full-scale practical implementations. Among all the research issues in WSN, security is one of the most challenging topics to deal with. The major hurdle of securing a WSN is imposed by the limited resources of the sensors participating in the network. Again, the reliance on wireless communication technology opens the door for various types of security threats and attacks. Considering the special features of this type of network, in this chapter we address the critical security issues in wireless sensor networks. We talk about cryptography, steganography, and other basics of network security and their applicability in WSN. We explore various types of threats and attacks against wireless sensor networks, possible countermeasures, mentionable works done so far, other research issues, etc. We also introduce the view of holistic security and future trends towards research in wireless sensor network security.
Actin dynamics control ploidy-dependent size scaling in Schizosaccharomyces pombe

It has long been known that eukaryotic cells with more DNA content are larger in cell size. However, no molecular mechanisms for this universal rule have been given. Here I identify cell division genes that dose-dependently control cell growth or cell extension rate (CER) of diploid cells of the fission yeast Schizosaccharomyces pombe. Genetic analysis revealed a negative role of Cdc2, a conserved master regulator of eukaryotic cell cycle. Surprisingly, half dosage of cdc25 or nim1 (cdc25Δ/+ or nim1Δ/+), both activator for Cdc2, decreased CER. I discovered that these genes constitute three overlapping regulatory mechanisms for Cdc2: positive and negative feedback loops and a feedforward network. In the negative feedback loop, Cdc2-activating Cdc25 is required for nuclear accumulation of GFP-Wee1 that inhibits Cdc2. Actin monomers are associated with nuclear localization of GFP-Wee1 and accelerate CER, while actin polymers are related to nuclear accumulation of Cdc25-GFP. In the positive feedback loop, actin monomers are relevant to inhibition of Nim1 and subsequent activation of Cdc2 independently of Wee1, resulting in decrease in CER. Nim1 also plays a key role in the feedforward network for supplying sufficient amount of nuclear GFP-Wee1 and closely cooperates with Cdc25 in order to adjust CER to ploidy. Remarkably, doubling cell division genes in haploids reproduced CER of diploids. These findings establish that yeast cells control CER dependently upon dosage of cell division genes during G2 period in the cell division cycle, and provide a solid foundation for understanding the cell-size scaling with DNA content in other eukaryotes.
The Role of Metaheuristic Algorithm in weight Training and Architecture evolving of Feedforward Neural Networks

Neural network and metaheuristic algorithm are two technique of machine learning. Each of them is employed for different purposes. NN is used for classification, regression, etc., however, a metaheuristic algorithm is used to find the optima in a huge search space. To use a neural network, first, it should be trained. In the process of training, the weight of each connection is obtained so that the total error (real output minus predicted amount) became minimum. That’s where stochastic search space come in to help find the best set of weights. Therefore, finding weights of a neural network can be interpreted as finding the optima of a vast search space. The focus of this paper is on the use of metaheuristic algorithm on training and evolving structure of feed-forward neural networks
Energy Efficient Engine (E3) combustion system component technology performance report

The Energy Efficient Engine (E3) combustor effort was conducted as part of the overall NASA/GE E3 Program. This effort included the selection of an advanced double-annular combustion system design. The primary intent of this effort was to evolve a design that meets the stringent emissions and life goals of the E3, as well as all of the usual performance requirements of combustion systems for modern turbofan engines. Numerous detailed design studies were conducted to define the features of the combustion system design. Development test hardware was fabricated, and an extensive testing effort was undertaken to evaluate the combustion system subcomponents in order to verify and refine the design. Technology derived from this effort was incorporated into the engine combustion hardware design. The advanced engine combustion system was then evaluated in component testing to verify the design intent. What evolved from this effort was an advanced combustion system capable of satisfying all of the combustion system design objectives and requirements of the E3.
Pressure in a cavity of building-high double facade

A numerical method is developed for estimating pressure in a cavity of a high double skin facade. The method is based on an extended Bernoulli’s theory, in which the pressure consists of friction loss and velocity pressure. The calculation consists of two stages. In the first stage, the pressure and the velocity by the friction loss in the cavity are calculated by the pressures at the openings of the double skin, which are given by the wind tunnel result for the normal single skin building. Then, velocity pressure is calculated by the velocity. By the comparison with the experimental results, the method can predict well the pressure in the cavity.
The twofold role of Cloud Computing in Digital Forensics: target of investigations and helping hand to evidence analysis

This PhD thesis discusses the impact of Cloud Computing infrastructures on Digital Forensics in the twofold role of target of investigations and as a helping hand to investigators. The Cloud offers a cheap and almost limitless computing power and storage space for data which can be leveraged to commit either new or old crimes and host related traces. Conversely, the Cloud can help forensic examiners to find clues better and earlier than traditional analysis applications, thanks to its dramatically improved evidence processing capabilities. In both cases, a new arsenal of software tools needs to be made available. The development of this novel weaponry and its technical and legal implications from the point of view of repeatability of technical assessments is discussed throughout the following pages and constitutes the unprecedented contribution of this work
Effects of electroacupuncture therapy for depression: study protocol for a multi-centered, randomized controlled trial

Background As a major public health problem, depression has a negative impact on individuals and society. The aim of this well-designed trial is to evaluate the efficacy and safety of electroacupuncture (EA) treatment for depression. Methods/Design A three-arm parallel, non-blinded, randomized controlled trial was performed in four hospitals (centers). 144 participants will be divided into three groups: electroacupuncture (EA) group, hand acupuncture (HA) group and western medicine group. Participants in EA group and HA group received 12 sessions of acupuncture treatment for 4 weeks. Participants allocated to western medicine group will only take 20mg fluoxetine orally per day for 4 weeks. The primary outcome is Hamilton Depression Scale (HAMD). Secondary outcomes are Self-Rating Depression Scale (SDS), Depression Scale of traditional Chinese medicine (Depression Scale of TCM), brain fMRI and blood biomarkers including neurotransmitters 5-HT, DA, NE, inflammatory cytokines IL-1β, TNF-α, IL-6 and neurotrophin BDNF. All the outcomes will be assessed at baseline, 4 weeks after EA treatment onset and 6-month follow-up. Discussion The results of this trial will verify the efficacy and safety of EA treatment for depressive patients and provide acupuncturists and clinicians with robust clinical evidence.