Miracle-dz/UniFAR-FTUs huggingface dataset:
Part-of-Speech Tagger for Malay Social Media Texts

Processing the meaning of words in social media texts, such as tweets, is challenging in natural language processing. Malay tweets are no exception because they demonstrate distinct linguistic phenomena, such as the use of dialects from each state in Malaysia; borrowing foreign language terms in the context of Malay language; and using mixed languages, abbreviations and spelling errors or mistakes in sentence structure. Tagging the word class of tweets is an arduous task because tweets are characterised by their distinctive style, linguistic sounds and errors. Currently, existing works on Malay part-of-speech (POS) are based only on standard Malay and formal texts and are thus unsuitable for tagging tweet texts. Thus, a POS model of tweet tagging for non-standardised Malay language must be developed. This study aims to design and implement a non-standardised Malay POS model for tweets and performs assessment on the basis of the word tagging accuracy of test data of unnormalised and normalised tweet texts. A solution that adopts a probabilistic POS tagging called QTAG is proposed. Results show that the Malay QTAG achieves best average POS tagging accuracies of 90% and 88.8% for normalised and unnormalised test datasets, respectively.
Metadata approach in modeling multi structured data collection using object oriented concepts

In designing an enterprise wide system, a system architect must consider different concerns of the stakeholders. In this paper, we propose a generic metadata approach for modeling data with multi structure representations derived from different points of view of the stakeholders. The notion of structures/organizational views of data is separated from the collection of the data itself. We introduce two layers of the generic metamodel: (1) dataset: real data handled as a collection; (2) viewpoint: a more abstract layer describing the many structures/metadata for each point of view. The idea of datasets and viewpoints are adopted from the concepts of abstract and concrete class in object oriented modeling. To validate the generic model, we provide several case studies. We expect the proposed model provides a better architectural way of thinking in modeling an enterprise.
Fundamentals of Decentralized Optimization in Autonomic Systems

An autonomic system is a complex information system comprised of many interconnected components operating at different time scales in a largely independent fashion that manage themselves to satisfy high-level system management requirements and specifications [5]. This includes providing the self∗ properties of self-configuring, self-repairing, self-organizing and self-protecting. A fundamental problem for achieving the goals of selfmanagement concerns the general optimization framework that provides the underlying foundation and supports the design, architecture and algorithms employed throughout the system. Given the increasing complexity of current and future information systems, a decentralized approach is a natural way to design and implement autonomic systems that provide self∗ properties. On the other hand, a centralized approach with complete knowledge over all constituent system components has the potential to provide significant improvements over a decentralized approach, in the same way that solutions to global optimization problems (if attainable) are often superior to the corresponding locally optimal solutions. This fundamental problem involving the tradeoff between centralized and decentralized approaches arises in a wide range of applications, and its solution is especially important to achieve the goals of self-management in autonomic systems.
Priority based optimal resource reservation mechanism in constrained Networks for IOT applications

In recent times Internet of Things (IoT) has gained popularity because of its characteristics in connecting and providing communication among various physical objects and devices enabling collection of diverse data that help making smart and educated decisions which in turn help making human life simple, safe and efficient. Traditional Wireless Sensor Networks (WSNs) are now becoming mainstream data source for IoT applications by connecting to uniquely addressable and routable gateways. Wireless Sensor Networks are defined as a collection of devices with limited resources like processing, memory, power and bandwidth, deployed for sensing various scalar and multimedia data with diverse traffic types. These data are critical and has to reach the sink in time. The constrained nature of the network with inherent approach of best effort data delivery, not only imposes challenges in reliable transmission of data but also the real time delivery of the data. With increasing use of IoT technology in Smart solutions such as Access control, Real time inventory, Flow optimization, one of the key problems of next generation WSNs is the real-time management and control of network paths within the sensor network so that mission critical data from sensor nodes reaches the IoT Gateway in real-time. In addition, given the myriad type of applications in WSN, imposes the need to segregate and treat data traffic variedly based on the criticality of the application and/or data. Hence there is a need to address the aspects of optimal usage of resources for handling delivery of critical data satisfying its Quality of Service (QoS) requirements within the sensor network. This paper proposes optimal resource reservation mechanism which has resulted in optimal utilization of resources by allocating sufficient resources for prominent and critical data and hence reducing the delay and increasing the performance of the system.
The Transcriptome and Metabolic Gene Signature of Protoplasmic Astrocytes in the Adult Murine Cortex

Protoplasmic astrocytes are critically important to energy metabolism in the CNS. Our current understanding of the metabolic interactions between neurons and glia is based on studies using cultured cells, from which mainly inferential conclusions have been drawn as to the relative roles of neurons and glia in brain metabolism. In this study, we used functional genomics to establish the relative compartmentalization of neuronal and astrocytic metabolic pathways in the adult brain. To this end, fluorescence-activated cell sorting was used to directly isolate neurons and protoplasmic astrocytes from the cortex of adult mice. Microarray analysis showed that astrocytes and neurons each express transcripts predicting individual self-sufficiency in both glycolysis and oxidative metabolism. Surprisingly, most enzymes in the tricarboxylic acid (TCA) cycle were expressed at higher relative levels in astrocytes than in neurons. Mass spectrometric analysis of the TCA cycle intermediates confirmed that freshly isolated adult astrocytes maintained an active TCA cycle, whereas immuno-electron microscopy revealed that fine astrocytic processes encompassing synapses contained a higher density of mitochondria than surrounding cells. These observations indicate that astrocytes exhibit robust oxidative metabolism in the intact adult brain and suggest a prominent contribution of astrocytic metabolism to functional brain imaging, including BOLD (blood-oxygen level-dependent) functional magnetic resonance imaging signals.
Modulation of B7.1 and B7.2 Expression Activated Macrophages Through the Costimulatory Activity of Resting and VIP and PACAP Differentially Regulate the

Vasoactive intestinal peptide (VIP) and pituitary adenylate cyclase activating polypeptide (PACAP), two structurally related neuropeptides produced and/or released within the lymphoid microenvironment, modulate numerous immune functions. Although primarily antiinﬂammatory in nature, VIP and PACAP also affect resting macrophages. In this study, we report on in vitro and in vivo dual effects of VIP/PACAP on the expression of B7.1 and B7.2 and on the costimulatory activity for T cells in unstimulated and LPS/IFN- g -activated macrophages. VIP and PACAP up-regulate B7.2, but not B7.1, expression and induce the capacity to stimulate the proliferation of naive T cells in response to soluble anti-CD3 or allogeneic stimulation. In contrast, both neuropeptides down-regulate B7.1/B7.2 expression on LPS/IFN- g -activated macrophages and inhibit the endotoxin-induced costimulatory activity for T cells. Interestingly, both the stimulatory and the inhibitory effects of VIP/PACAP are mediated through the speciﬁc receptor VPAC1 and involve the cAMP/protein kinase A transduction pathway. The dual effect on B7.1 and B7.2 expression occurs at both mRNA and protein level and correlates with the VIP/PACAP regulation of the macrophage costimulatory activity. Through their regulatory role for resting and activated macrophages, VIP and PACAP act as endogenous par-ticipants in the control of immune homeostasis. Their effects depend not only on the timing of their release, but also on the activation and differentiation state of the neighboring immune cells. The Journal of Immunology, 1999, 163: 4213–4223. B7.2 expression in unstimulated macrophages, and the inhibitory effect on B7.1/B7.2 expression in activated macrophages, are mediated through increases in intracellular cAMP.
Robustness With Respect to Sampling for Stabilization of Riesz Spectral Systems

We suppose that a continuous-time feedback is input-output stabilizing for an infinite-dimensional system. We address the question of whether the sampled-data controller obtained by applying idealized sample-and-hold to this continuous-time feedback is also input-output stabilizing if the sampling time is small enough. This question has been previously addressed for fairly general systems under various conditions. In this note, we restrict our attention to Riesz spectral systems, for which we generalize the existing results. Specifically, we give two relatively simple conditions which, combined, are sufficient for the sampled-data controller to be stabilizing. The first condition is a spectrum decomposition for the open-loop system generator, which by itself is necessary, but not sufficient, for the system to be stabilizable by sampled-data control. The second is a summability condition relating the real part of the spectrum of the generator and the expansion coefficients for the input and feedback operators
Observer-based control for absolute orientation estimation of a five-link walking biped robot

Reference trajectories for a cyclic walking gait of a five-link biped without feet are designed by optimization. These reference trajectories are polynomial functions using the absolute orientation of the virtual stance leg which is quite difficult to measure. Then a high gain observer coupled with a nonlinear control law is designed to estimate this absolute orientation of the virtual stance leg
Threat-Based Risk Assessment for Enterprise Networks

Protecting enterprise networks requires continuous risk assessment that automatically identifies and prioritizes cybersecurity risks, enables efficient allocation of cybersecurity resources, and enhances protection against modern cyberthreats. Lincoln Laboratory developed a foundational network security maturity model to guide development of such risk assessments and has developed practical risk metrics for the most important cyberthreats. These metrics can be computed automatically and continuously from security-relevant network data.
Hi-C Chromatin Interaction Networks Predict Co-expression in the Mouse Cortex

The three dimensional conformation of the genome in the cell nucleus influences important biological processes such as gene expression regulation. Recent studies have shown a strong correlation between chromatin interactions and gene co-expression. However, predicting gene co-expression from frequent long-range chromatin interactions remains challenging. We address this by characterizing the topology of the cortical chromatin interaction network using scale-aware topological measures. We demonstrate that based on these characterizations it is possible to accurately predict spatial co-expression between genes in the mouse cortex. Consistent with previous findings, we find that the chromatin interaction profile of a gene-pair is a good predictor of their spatial co-expression. However, the accuracy of the prediction can be substantially improved when chromatin interactions are described using scale-aware topological measures of the multi-resolution chromatin interaction network. We conclude that, for co-expression prediction, it is necessary to take into account different levels of chromatin interactions ranging from direct interaction between genes (i.e. small-scale) to chromatin compartment interactions (i.e. large-scale).
Sensor localization using acoustic doppler shift with a mobile access point

The nodes in a sensor network are often deployed in random locations. However, most applications require that the location and/or orientation of the nodes be known, so post-deployment algorithms for self-localization of the sensor nodes are important. We consider using a mobile access point (AP) for sensor node localization in a randomly deployed sensor network. We focus on the particular case in which the sensors measure the acoustic Doppler shift in a tone that is emitted from the mobile AP. In addition to the acoustic emission, the mobile AP broadcasts a radio signal that contains AP position, velocity, timing, and parameters of the acoustic signal. We demonstrate that atmospheric turbulence has a significant impact on the accuracy of sensor localization, degrading performance by as much as two orders of magnitude relative to an ideal, plane-wave propagation model. We present Cramer-Rao bounds (CRBs) for sensor localization accuracy and compare the performance of algorithms to the CRBs under "cloudy" and "sunny" weather conditions
The Independence Number of Dense Graphs with Large Odd Girth

Let $G$ be a graph with $n$ vertices and odd girth $2k+3$. Let the degree of a vertex $v$ of $G$ be $d_1 (v)$. Let $\alpha (G)$ be the independence number of $G$. Then we show $\alpha (G) \geq 2^{-\left({{k-1}\over {k}}\right)} \left[ \displaystyle{\sum_{v\in G}} d_1 (v)^{{{1}\over {k-1}}} \right]^{(k-1)/k}$. This improves and simplifies results proven by Denley.
Cloud Balancing – A Survey

In its generally essential structure, cloud balancing furnishes an organization with the capacity to convey requisition requests over any number of application deployments spotted in data centers and through cloud-computing suppliers. Cloud balancing takes a broader perspective of provision conveyance and applies specified limits and administration level agreements to each request. The utilization of cloud balancing can bring about the dominant part of clients being served by provision arrangements in the cloud providers’ environments, in spite of the fact that the local application deployment or inner, private cloud may have all that could possibly be needed limit to serve that client. A variant of cloud balancing called cloud bursting, which sends abundance traffic to cloud implementations, is additionally being executed over the globe today. Cloud bursting conveys the profits of cloud providers when utilization is high, without the out of pocket when organizational data centers incorporating internal cloud arrangements can handle the workload.
Kidney histology and function in liver transplant patients.

BACKGROUND Chronic kidney disease is a common complication after liver transplantation. However, few reports regarding kidney histology exist for this setting. METHODS Inulin clearance was measured and a kidney biopsy was performed in 99 patients at 60 ± 48 months after liver transplantation. Kidney biopsies were scored according to the Banff classification, and interstitial fibrosis was measured by a computerized quantitative method. RESULTS There was a steep decrease in kidney function within the first 6 months following transplantation, but this lessened thereafter. At kidney biopsy, inulin clearance and estimated glomerular filtration rate (eGFR) (using the abbreviated Modification of Diet in Renal Disease equation) were highly correlated (r(2) = 0.47, P < 0.0001). A decrease in eGFR at 6 months post-transplant was the sole predictive factor for inulin clearance of < 60 mL/min/1.73 m(2) at 5 years post-transplant. Few patients had a specific pattern of kidney histopathology and all patients had complex primary lesions. Lowered eGFR at 6 months post-transplant was a predictive factor for > 50% sclerotic glomeruli on the kidney biopsy. The duration of tacrolimus therapy, as compared to cyclosporine A, was a protective factor for < 20% interstitial fibrosis on the kidney biopsy. CONCLUSION In the setting of liver transplantation, this is the largest kidney-histology study to confirm that histological kidney lesions are complex, multiple and interrelated. Kidney function at 6 months post-transplant can predict long-term kidney function and histology.
A low power 9.5 ENOB 100MS/s pipeline ADC using correlated level shifting

In this work the design of a low power 10-bit 100MS/s pipeline ADC is presented. Low power consumption is realized by using an optimum bit per stage resolution and also by applying the correlated level shifting (CLS) technique for the first four stages. Moreover, by obviating the need for a first stage S/H, power consumption was reduced considerably. The first stage of the pipeline has a 2.5-bit resolution, following six 1.5-bit stages with a 2-bit flash ADC at the end. For more power efficiency, stage scaling for the first three stages was also applied. Simulation results in HSPICE using a standard 0. 18μm CMOS technology showed a SNDR and SFDR of 59.97dB and 64.8dB, respectively, for a 49.2MHz 2-Vp-p input signal. ADC power consumption excluding buffers and bonding-pads is 6.67mW from a 1.8V supply voltage.
Physical Activity and Coronary Heart Disease Risk in Men: Does the Duration of Exercise Episodes Predict Risk?

BackgroundPhysical activity is associated with a decreased risk of coronary heart disease (CHD). However, it is unclear whether the duration of exercise episodes is important: Are accumulated shorter sessions as predictive of decreased risk as longer sessions if the same amount of energy is expended? Methods and ResultsIn the Harvard Alumni Health Study, we prospectively followed 7307 Harvard University alumni (mean age 66.1 years) from 1988 through 1993. At baseline, men reported their walking, stair climbing, and participation in sports or recreational activities. For each of the latter activities, they also reported the frequency and average duration per episode. During follow-up, 482 men developed CHD. In age-adjusted analysis, a longer duration of exercise episodes predicted lower CHD risk (P trend=0.04). However, after total energy expended on physical activity and potential confounders was accounted for, duration no longer had an independent effect on CHD risk (P trend=0.25); that is, longer sessions of exercise did not have a different effect on risk compared with shorter sessions, as long as the total energy expended was similar. In contrast, higher levels of total energy expenditure significantly predicted decreased CHD risk in both age-adjusted (P trend=0.009) and multivariate (P trend=0.046) analyses. ConclusionsThese data clearly indicate that physical activity is associated with decreased CHD risk. Furthermore, they lend some support to recent recommendations that allow for the accumulation of shorter sessions of physical activity, as opposed to requiring 1 longer, continuous session of exercise. This may provide some impetus for those sedentary to become more active.
Image segmentation of blood cells in leukemia patients

The early identification of leukemia form in cancer patients can greatly increase the likelihood of recovery. Diagnostic methods that distinguish among the disease's many forms are either costly or do not exist. Amongst the existing diagnostic methods are immune-phenotype and cytogenetic abnormality, which require time to obtain results and are costly to perform due to their requirement of well equipped laboratories. Thus, there is a need for fast and cost-effective method that results in the identification of the different leukemia forms or types. Therefore, we propose the use of morphological analysis of microscopic images of leukemic blood cells for the identification purpose. We present in this paper the first phase of an automated leukemia form identification system, which is the segmentation of infected cell images. The segmentation process provides two enhanced images for each blood cell; containing the cytoplasm and the nuclei regions. Unique features for each form of leukemia can then be extracted from the two images and used for identification.
A web search survey: A study for fusion of different sources to determine relevance

With ever increasing number of users on Internet there is a necessity to make Web retrieval process to be more efficient. The users face the problem which is how to get relevant and useful information from the large disorder information. Web mining can change the way results are provided to user queries presently i.e. ranked list of content based results. This work focuses on the study of different filtering and ranking methods and introducing a combined approach for finding relevance. The relevancy and ranking of the document will be performed by going through the content of web pages, link structure and user choice. The framework using the combination of three approaches as a hybrid approach is introduced. Here in this paper we want to focus on how to locate the resources on World Wide Web which is high in quality and relevant to information need.