Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimized multilayer perceptron using dynamic learning rate based microwave tomography breast cancer screening

A performance of classification tool in a Computer Aided Diagnosis (CAD) software directly affects capacity of entire breast cancer screening. Most developed classification tools have mainly focused on standard techniques, for example, Magnetic Resonance Imaging (MRI), x-ray mammography, and ultrasound. With the advent of new technology, Microwave Tomography Imaging (MTI), it was inevitable to develop a desirable classification tool showing compromised performance. Yet, existing classification model using Artificial Neural Network (ANN) for handling data from the MTI shows non-negligible optimization scheme. In this paper, we present an improved model, Multilayer Perceptron (MLP) using Dynamic Learning Rate (DLR) in order to obtain better performance with optimized setting for binary classification that can be plugged into the CAD software platform. The proposed model has an optimized size of neural network so that it will not fall into indeterminate equation problem by having reasonable amount of weights between each perceptron Also, the proposed model will dynamically assign a learning rate onto each training points in the way that model earmarks a higher learning rate onto each training points belonging into minority class in order to escape from local minima which is a typical jeopardy of ANN. In experiment, we evaluated performance with following measures; precision, recall, specificity, accuracy, and Matthews Correlation Coefficient (MCC). Experimental result shows that MLP using DLR outperforms overall measures over existing ANN dealt with MTI.
Quantitation of aberrant interlocus T‐cell receptor rearrangements in mouse thymocytes and the effect of the herbicide 2,4‐dichlorophenoxyacetic acid

Small studies in human populations have suggested a correlation between the frequency of errors in antigen receptor gene assembly and lymphoid malignancy risk. In particular, agricultural workers exposed to pesticides have both an increased risk for lymphoma and an increased frequency of errors in antigen receptor gene assembly. In order to further investigate the potential of such errors to serve as a mechanistically based biomarker of lymphoid cancer risk, we have developed a sensitive PCR assay for quantifying errors of V(D)J recombination in the thymocytes of mice. This assay measures interlocus rearrangements between two T‐cell receptor loci, V‐gamma and J‐beta, located on chromosomes 13 and 6, respectively. The baseline frequency in four strains of mice was determined at several ages (2–8 weeks of age) and was found to be stable at ∼1.5 × 10‐5 per thymocyte. Strain AKR, which has a high susceptibility to T‐cell lymphomas, did not show an elevated frequency of aberrant V(D)J events. We used this assay to examine the effects of the herbicide 2,4‐dichlorophenoxyacetic acid (2,4‐D) on the frequency of these events. Female B6C3F1 mice, 27 days of age, were exposed to 2,4‐D by gavage at doses of 0, 3, 10, 30, and 100 mg/kg/day for 4 successive days and sacrificed on day 5. Thymus DNA was isolated and examined for illegitimate V(D)J recombination‐mediated gene rearrangements. In addition, pregnant mice were exposed to 2,4‐D and thymocytes from the offspring examined at 2 weeks of age. No significant increase in aberrant V(D)J rearrangements was found, indicating that under these conditions 2,4‐D does not appear to effect this important mechanism of carcinogenesis. Environ. Mol. Mutagen. 42: 37–43, 2003. Published 2003 Wiley‐Liss, Inc.
A robust channel estimator for DS-CDMA systems under multipath fading channels

The paper addresses the problem of channel estimation for DS-CDMA systems undergoing time-varying multipath fading channels. The multipath fading channels are modeled as AR models. Based on the minimum mean square error (MMSE) criterion, the linear optimal estimator is obtained by a spectral factorization and a Diophantine polynomial matrix equation. The uncertainty of the channel model is taken into consideration to improve the robustness of the estimator. Compared with the Kalman estimator, the proposed algorithm has O(K/sup 2/) computational complexity, where K is the number of users. The simulation results show that the proposed estimator provides good estimation performance and robustness for fast fading channels.
Forecasting Realised Volatility of Micex Index

Motivated by recent innovations in volatility forecasting, the presented study analyses the explanatory power of HAR framework in the context of MICEX index seeking to expand the empirical evidence on the subject of the optimal forecasting methodology. The rest of the paper is organized as follows. First part represents the literature review in the form of concise description of history of modeling volatility process, highlights the drawbacks of traditional approaches and summarises the major accomplishments in forecasting methods of recent years. Next section provides an extension of literature review, offering the analyses of the mathematical structure of RV and integrated volatility (IV) as well as HAR specifications employed in underlined study. The third part displays the results of forecasting procedures, accompanied with the description of changes in predictive power and ACF originating from the application of outliers cleaning procedure. The last section recapitulates the major results of the respective study and suggests the possible direction of the further problem elaboration.
A Novel Encryption Scheme based on DNA Computing

— A novel method to encrypt data by applying DNA based computing technology is discussed. Binary data may be encoded in DNA strands by use of an alphabet of short oligonucleotide sequence. The encryption of natural DNA and the encryption of DNA encoding binary data are discussed.A pure XOR based DNA computing scheme is also discussed and the limitations of the proposed scheme are observed.
Caveolin‐1 enhances rapid mucosal restitution by activating TRPC1‐mediated Ca2+ signaling

Early rapid mucosal restitution occurs as a consequence of epithelial cell migration to reseal superficial wounds, a process independent of cell proliferation. Our previous studies revealed that the canonical transient receptor potential‐1 (TRPC1) functions as a store‐operated Ca2+ channel (SOCs) in intestinal epithelial cells (IECs) and regulates epithelial restitution after wounding, but the exact mechanism underlying TRPC1 activation remains elusive. Caveolin‐1 (Cav1) is a major component protein that is associated with caveolar lipid rafts in the plasma membrane and was recently identified as a regulator of store‐operated Ca2+ entry (SOCE). Here, we showed that Cav1 plays an important role in the regulation of mucosal restitution by activating TRPC1‐mediated Ca2+ signaling. Target deletion of Cav1 delayed gastric mucosal repair after exposure to hypertonic NaCl in mice, although it did not affect total levels of TRPC1 protein. In cultured IECs, Cav1 directly interacted with TRPC1 and formed Cav1/TRPC1 complex as measured by immunoprecipitation assays. Cav1 silencing in stable TRPC1‐transfected cells by transfection with siCav1 reduced SOCE without effect on the level of resting [Ca2+]cyt. Inhibition of Cav1 expression by siCav1 and subsequent decrease in Ca2+ influx repressed epithelial restitution, as indicated by a decrease in cell migration over the wounded area, whereas stable ectopic overexpression of Cav1 increased Cav1/TRPC1 complex, induced SOCE, and enhanced cell migration after wounding. These results indicate that Cav1 physically interacts with and activates TRPC1, thus stimulating TRPC1‐mediated Ca2+ signaling and rapid mucosal restitution after injury.
Pulling Together with Type IV Pili

Type IV pili are an efficient and versatile device for bacterial surface motility. They are widespread among the β-, γ-, and δ-proteobacteria and the cyanobacteria. Within that diversity, there is a core of conserved proteins that includes the pilin (PilA), the motors PilB and PilT, and various components of pilus biogenesis and assembly, PilC, PilD, PilM, PilN, PilO, PilP, and PilQ. Progress has been made in understanding the motor and the secretory functions. PilT is a motor protein that catalyzes pilus retraction; PilB may play a similar role in pilus extension. Type IV pili are multifunctional complexes that can act as bacterial virulence factors because pilus-based motility is used to spread pathogens over the surface of a tissue, or to build multicellular structures such as biofilms and fruiting bodies.
E-law Module Supporting Lawyers in the Process of Knowledge Discovery from Legal Documents

E-law module is the web application which works mainly as the set of information retrieval and extraction tools dedicated for the lawyers. E-law module consists of following tools: (1) document search engine; (2) context oriented search engine plugin; (3) legal phrase oriented machine translation; (4) document meta-tagger; (5) verdict ﬁnder. Machine translation, document meta-tagger and verdict ﬁnder tools are available for the general public. Other tools are restricted and are accessible after logging into the module.
Robust gloves for 3D interaction in mobile outdoor AR environments

This paper describes the design of hand-worn gloves for interacting with mobile outdoor augmented reality systems. Most existing systems rely on more traditional 2D input devices such as mice and keyboards. Since augmented reality information is typically registered in 3D to the environment, user interfaces need to be designed that are capable of supporting the more complex operations possible. This paper describes how we used metallic thread and adhesive fabric to add conduction sensing to a standard set of gloves which can survive harsh treatment; how Bluetooth and MSP430 microcontrollers are used to build a small circuit that is wireless and highly portable; and how AR-ToolKit is used for 3D tracking of fiducial markers on the thumbs. While we have previously demonstrated this technology with a number of our previous systems, this paper explains the various techniques we use in the implementation.
Fuzzy rules based indoor human action recognition using multi cameras

In this paper, we propose a method for recognizing human actions indoors using fuzzy rules and multi cameras. To recognize the human actions, initially, we use the background difference method to extract human area candidates. We then extract HOG features and learn to detect humans using the features and AdaBoost. Fuzzy rules are then used of detect the human actions. The detected human is determined to be stationary or not using the distance between the detected areas in consecutive frames. We also estimate the direction the human is facing using the width of detection, and finally recognize the standard action using the height of the detected region. In addition, we recognize suspicious action using duration of detection and presence of abandoned object. After experiments, recognition accuracy achieved for “walking” and “stop” actions is about 87%, for “running” action about 54%, for “sitting” about 96%, for “desk working” about 83%, and “falling” about 88%.
Catha edulis chewing effects on treatment of paranoid schizophrenic patients

Background The current study’s aim is to evaluate the possible interaction effects of khat chewing on treatment of paranoid schizophrenic patients. Patients and methods In the study group, 42 male subjects suffered from paranoid schizophrenia and were classified according to their khat chewing habits into two subgroups: either khat-chewer subgroup (SKc; n=21; r=11, h=10) or non-khat-chewer subgroup (SNKc; n=21, r=11, h=10). Each subgroup was further subdivided according to type of treatment into r (risperidone) and h (haloperidol). Healthy male subjects (37) were subdivided into healthy khat-chewer as positive controls (HKc, n=17) and healthy non-khat-chewer as negative controls (HNKc, n=20). Plasma dopamine, 3,4-dihydroxyphenylacetic acid (DOPAC), homovanillic acid, 5-hydroxytryptamine (serotonin), 5-hydroxyindoleacetic acid, epinephrine, and norepinephrine were estimated. Results ANOVA and post hoc analysis showed that dopamine was illustrating significant elevation in all khat chewing groups. DOPAC was illustrating significant decrease in all khat chewing groups with an interesting outcome showing significant increase in DOPAC in SNKcr group due to risperidone effect. Homovanillic acid, serotonin, hydroxyindoleacetic acid, and norepinephrine were illustrating significant elevations in all khat chewing groups. Epinephrine was illustrating significant elevation in all chewers than non-chewers groups. Unexpected significant decrease in epinephrine in the SNKcr group indicated that risperidone drug is decreasing epinephrine through indirect mechanism involving calcium. Conclusion Khat chewing in schizophrenic patients is contraindicated because it aggravates the disease symptoms, attenuates all used treatment medications, and deteriorates all biochemical markers of the patients.
A Preoperative Marking Template for Deep Inferior Epigastric Artery Perforator Flap Perforators in Breast Reconstruction

Preoperative perforator marking for deep inferior epigastric artery perforator flaps is vital to the success of the procedure in breast reconstruction. Advances in imaging have facilitated accurate identification and preselection of potentially useful perforators. However, the reported imaging accuracy may be lost when preoperatively marking the patient, due to 'mapping errors', as this relies on the use of 2 reported vectors from a landmark such as the umbilicus. Observation errors have been encountered where inaccurate perforator vector measurements have been reported in relation to the umbilicus. Transcription errors have been noted where confusing and wordy reports have been typed or where incorrect units have been given (millimetres vs. centimetres). Interpretation errors have also occurred when using the report for preoperative marking. Furthermore, the marking process may be unnecessarily time-consuming. We describe a bespoke template, created using an individual computed tomography angiography image, that increases the efficiency and accuracy of preoperative marking. The template is created to scale, is individually tailored to the patient, and is particularly useful in cases where multiple potential suitable perforators exist.
Determinants of E-Government Service Adoption: An Innovation Diffusion Perspective

Ranking the world's top E-Government Readiness in 2002, 2004, and 2005, Taiwan's experience in promoting e- government could provide worldwide governors a practical knowledge for planning and implementation. Further, given the e-government services, e.g. tax e-filing system (TEFS) can be seen as an innovation for taxpayers to adopt, Taiwan's experience has also become a sensible example in innovation marketing. This study used three diffusion models, i.e. external, internal, and mixed influence models, to reveal whether the diffusion of TEFS in Taiwan was affected by mass media advertising, interactions among acquaintances, or a combination of both. Findings indicated that the mixed influence model is the best fit, but acquaintances influence is the dominant factor. The authors therefore argue that governors should consider "Source-Strategy Fit", i.e. it is essential to understand TEFS' features and its influential sources when promoting the G2C e-government services. Only when the adequate marketing strategies are developed, the huge investments in building e-government infrastructure can bring about citizens' convenient digital life and government efficiency to the full.
Stable PID tracking control with application to a 7-DoF exoskeleton robot

In this paper, we extend the popular PID regulation control into PID tracking control by using a filtered error and modifying the reference signal. In order to decrease the gains of PID controller, a neural compensator is enclosed. The global and semiglobal asymptotic stability of this PID tracking control with neural compensation are proposed. The proposed PID tracking control is validated with the upper limb exoskeleton of École de Technologie Supérieure (ETS).
CitiSafe: Adaptive Spatial Pattern Knowledge Using Fp-Growth Algorithm for Crime Situation Recognition

Crime prevention and control are issues of great concern to the government and public safety agencies. If these issues are not well controlled and managed, they could drastically affect the economy of a country negatively over time, since more emigration is naturally induced. With the existence of crime databases in the society, data mining techniques are viable tools for crime situation recognition and control. However, most existing techniques often fall short to consider salient features during the mining process. In this paper, we experimented on various crime categories across 32 locations within the western cape province of the republic of South Africa. Our research focus is to create a flexible and effective, yet simple, solution to crime situation recognition. A successful mining mechanism, adopting a batch-merge paradigm, that builds upon the Fp-Growth algorithm, referred to as CitiSafe algorithm is presented, followed by concluding remarks. The visualization techniques presenting the crime patterns, through our algorithm, would assist law enforcement agencies and public safety organisations to channelize their resources accordingly to achieve a focused and effective crime prevention strategy.
Mining time-dependent communities

Time evolution is one important feature of communities in network science. It is related with capturing critical events, characterizing community members, and predicting behaviours of communities in networks with time varying. However, most of existing community detection techniques are proposed for static networks. Here, we present a new framework to uncover community structure for each temporal graph over time. In consideration of regularizing time-dependent communities, the high temporal variations will be prevented and the gained results on community evolution become more reasonable. Having applied it on synthetic networks, the experimental results offer new views in dynamic networks
Dynamic Pipeline Scaling

RAMRAKHYANI, PRAKASH SHYAMLAL Dynamic Pipeline Scaling (Under the direction of Dr. Eric Rotenberg) The classic problem of balancing power and performance continues to exist, as technology progresses. Fortunately, high performance is not a constant requirement in a system. When the performance requirement is not at its peak, the processor can be configured to conserve power, while providing just enough performance. Parameters like voltage, frequency, and cache structure have been proposed to be made dynamically scalable, to conserve power. This thesis analyzes the effects of dynamically scaling a new processor parameter, pipeline depth. We propose Dynamic Pipeline Scaling, a technique to conserve energy at low frequencies when voltage is invariable. When frequency can be lowered enough, adjacent pipeline stages can be merged to form a shallow pipeline. At equal voltage and frequency, the shallow pipeline is more energy-efficient than the deep pipeline. This is because the shallow pipeline has fewer data dependence stalls and a lower branch misprediction penalty. Thus, there are fewer wasteful transitions in a shallow pipeline, which translates directly to lower energy consumption. On a variable-voltage processor, the shallow pipeline requires a higher operating voltage than the deep pipeline for the same frequency. Since energy depends on the square of voltage and depends linearly on the total number of transitions, on a variable-voltage processor, a deep pipeline is typically more energy-efficient than a shallow pipeline. However, there may be situations where variable voltage is not desired. For example, if the latency to switch voltage is large, voltage scaling may not be beneficial in a real-time system with tight deadlines. On such a system, dynamic pipeline scaling can yield energy benefits, in spite of not scaling voltage. Dynamic Pipeline Scaling by PRAKASH SHYAMLAL RAMRAKHYANI A thesis submitted to the Graduate Faculty of North Carolina State University in partial fulfillment of the requirements for the Degree of Master of Science COMPUTER ENGINEERING
4. Data Analysis Approaches, Algorithms and Software 4.1. Related Work and Its Unresolved Problems

Blogs and social networks have proved important in recent years in various senses, but particularly for political mobilization in a whole range of societies. They include not only European countries such as Spain (May 2011) or Russia (December 2011), but also countries with relatively low Internet penetration, such as Egypt. This paper is based on the study of the Russian blogosphere aimed at mapping its thematic, discursive and network structure. The long-term methodological goal of the study is to borrow and/or develop and introduce into social science a range of new methods of collection and analysis of big data in order to be able to derive sociological conclusions from them. The immediate goal of the study presented is to describe topical structure of the Russian language blogosphere as some reflection of public opinion in order to see what social issues are important, what cleavages exist and how it changes over time. Russian elections and protests in December 2011 is the key test issue explored in the project.