Miracle-dz/UniFAR-FTUs huggingface dataset:
A Survey on Energy Efficiency and Cluster Handling in Real Time Wireless Sensor Networks

Wireless networking technology in recent years has seen a thriving development. Wireless sensor networks (WSN) has remote environmental monitoring and target tracking as an important application. This makes sensors smaller and cheaper especially in recent years. These sensors form a network in the wireless interface with which they can communicate with each other. Design of WSN relies heavily on the application such as environment, and it also must consider design objectives, costs, hardware, and factors in which system is constrained. There are so many aspects involved in the wireless sensor networks which need to be readdressed or reviewed for further improvement, generally these are Clustering, Energy saving concepts and Network lifetime. Various researches and journals has been presented so far. In the current paper we are going to enlighten these aspects through survey of research studied that has being done.
THE PERMANENT MAGNETS MAGNETIC CHARACTERISTICS CHANGE UNDER EFFECT OF 10 MEV ELECTRON BEAM

Nd-Fe-B and Sm-Co magnets were irradiated by electron beam with the energy of 10 MeV and bremsstrahlung. The absorbed dose was 16 and 160 Grad. It was found that whereas magnetic flux of Nd-Fe-B magnets decrease with the irradiation, Sm-Co magnets keep magnetic performance.
Interactive , Browser-based Information Foraging in Heterogeneous Space-Centric Networks

Social media data can be thought of as a multi-dimensional dataset that contains references (explicit and implicit) to a myriad of entities of different types: events, places, people, etc. Although there is a wealth of ideas about how to visualize individual dimensions of this heavily interconnected dataset (e.g. a variety of cartographic techniques can be used to explore the spatial properties of the data), attempts to explore the links among these dimensions face a number of both theoretical and practical challenges. A recent development in network science – heterogeneous network modelling – presents a number of unique solutions to some of those issues. This paper explores the potential and challenges associated with integration of the heterogeneous network modelling approach into interactive, visual analytical environments that focus on geographic data. We present a functional prototype implemented as part of SensePlace2, a web-based social media geovisual analytics environment. Index Terms – geovisual analytics, heterogeneous network, information foraging, web-based.
Towards Early Diagnosis and Assessment of Cancer : Role of MRI and in-vivo MR Spectroscopy ( MRS )

Cancer is a major disease that affects men and women, worldwide, while breast cancer is the leading cause of cancer related deaths in women. Early diagnosis is essential for timely initiation of treatment which would improve the quality and overall survival of patients. Last two decades has seen development of non-invasive MRI methods like contrast MRI, diffusion and perfusion MRI for breast cancer diagnosis. MRI is useful for preoperative staging; follow response to therapy, and to detect local recurrences; however it has poor specificity in differentiating benign from malignant lesions, even with the use of contrast agents. Both diffusion MRI and in vivo MR spectroscopy (MRS) have shown great potential to increase the specificity of MRI. This article presents a review of the results obtained from our Institute on the potential of various MRI and MRS methods in the early diagnosis and assessment of tumor response of breast cancer patients.
Dynamic Arbitration of Memory Requests with TDM-like Guarantees

A major challenge with multi-cores in real-time systems is contention between concurrent accesses to shared memory. Dynamic arbitration schemes allow for an optimal utilization of the system's memory, while sacrificing time predictability. Time-Division multiplexing (TDM), on the other hand, sacrifices average-case performance in favor of predictability. In this work, we explore a dynamic arbitration scheme that is essentially based on TDM, and thus preserves many of its guarantees.
Application of peripherally inserted central catheter via femoral vein for pediatric burns

Aims: To explore the efficacy of peripherally inserted central catheter (PICC) via femoral vein and its complication rates in burns children to provide rationales for providing access for venous infusion. Methods: From January 2014 to December 2015, a total of 48 children with moderate-to-severe burns were recruited and assigned into two groups of PICC (n=24) and peripheral intravenous catheter (PIV). And their efficacies and complication rates were compared. Results: Significant inter-group differences existed in one-time puncture success rate, retention duration and overall complication rates. The specific data of PICC and PIV groups were as follows: one-time puncture success rate (95.8% vs 62.5%, X2=8.084, P<0.01); retention duration: (24.92±25.41 vs 2.63±1.16 days, z=5.941, P<0.01); overall complication rate (12.5% vs 58.3%, X2=11.021, P<0.01). Conclusion: With the advantages of higher one-time puncture success rate, longer retention duration and lower complication rate, PICC via femoral vein is ideally suited for infusion in pediatric burns, especially for those with large-area wound, emergency rescue and
Information: a question of quality?

This paper describes the nature of information and its quality criteria. But especially in Internet and portals quality is rather diffuse as many suppliers and users come together, thus multiplying the cognitive triangle. Some help is given by description standards, bibliometric methods or information mining. On the other hand, the user expects transparent and customized systems. Some advantages and disadvantages of each approach are discussed. Some solution can be given by respecting the different complexities of user types, whereas a combination of all quality approaches is still a demanding task
Chapter 14 Patterns and Controls on Nitrogen Cycling of Biological Soil Crusts

Biocrusts play a significant role in the nitrogen (N) cycle within arid and semiarid ecosystems, as they contribute major N inputs via biological fixation and dust capture, harbor intense internal N transformation processes, and direct N losses via dissolved, gaseous, and erosional loss processes (Fig. 14.1). Because soil N availability in arid and semiarid ecosystems is generally low and may limit net primary production (NPP; Hooper and Johnson 1999), especially during periods when adequate water is available, understanding the mechanisms and controls of N input and loss pathways in biocrusts is critically important not only to our broader understanding of N cycling in dryland environments but also of overall dryland fertility. In particular, N cycling by biocrusts likely regulates short-term soil N
Energy Efficient Code Converters Using Reversible Logic Gates

Reversible logic design has been one of the promising technologies gaining greater interest due to less dissipation of heat and low power consumption. Reversible logic has received significant attention in recent years. It has applications in various research areas such as low power CMOS design, optical computing, quantum computing, bioinformatics, thermodynamic technology, DNA computing and nanotechnology. It is not possible to construct quantum circuits without reversible logic gates. Synthesis of reversible logic circuits is significantly more complicated than traditional irreversible logic circuits because in a reversible logic circuit, we are not allowed to use fanout and feedback. In digital systems code conversion is a widely used process for reasons such as enhancing security of data, reducing the complexity of arithmetic operations and thereby reducing the hardware required, dropping the level of switching activity leading to more speed of operation and power saving etc. This paper proposes novel Reversible logic design for code conversion such as Binary to Gray code, Gray to Binary code, BCD to Excess 3 code and Excess 3 to BCD codeconverters.
FUNCTIONAL VERSUS CONSCIOUS AWARENESS IN CSCW-SYSTEMS

An increasing number of groupware systems aim at providing users with awareness information—information about the presence, activities, and availability of the other users of the same system. However, most of these sy tems are designed from a functional rather than a human-oriented point of view. In fact, designers of awareness features more often focus on technical challenges and realisability than on adequate support of group awareness information. In this paper, we relate empirical findings of human behaviour to existing groupware systems identifying requirements for future human oriented groupware systems. When applied from a methodological perspective, this approach leads to the utmost human-centred utilisation of technology to support task accomplishment.
SMALL-SIZED TEST BED FOR DIAGNOSING THE GIGACYCLE FATIGUE PROCESSES

The purpose of this paper is to develop, for highly-resistant materials, a method of forecasting and analysis of gigacycle fatigue durability (10÷10 cycles) relying on vibroacoustic signal analysis. The method proposes the use of results of vibroacoustic signal analysis obtained during accelerated fatigue tests conducted in dedicated test bed constructed specially for this purpose and operating in the frequency range of 10 kHz which corresponds to the resonance frequency of vibration of samples. The presented test bed is a unique small sized structure compared to the foreign solutions which have been constructed while using the supporting structures of classical machines used for durability testing. Thanks to the small dimensions and mass, the test bed can be located on the vibration shaker, thus introducing resonant frequencies modulation. Vibroacoustic diagnosis methods enable not only the detection of surface defects but also detection of defects occurring in the core of a sample. Thus it becomes possible to try to learn the nature of increased durability to fatigue and to try to use the features of vibroacoustic signals in forecasting the gigacycle fatigue durability.
EAI Endorsed Transactions on Internet of Things Research

Image registration is the vital technology in computer vision. By developing precise image registration algorithm will meaningfully improve the techniques for the problems in computer vision. Registration process does geometrical alteration that aligns point present in one view of an object with similar points in another view of that object or another object . Steps involved in image registration are feature finding, matching of features, image transformation and resampling. Feature finding and matching have vital role in accuracy of the process. In this paper we have used SIFT (Scale Invariant Feature Transform) for the feature detection which is invariant to scaling, rotation and noise. KNN nearest neighbor is used for matching similar points and the other efficient method in reducing miss matches in the proposed algorithm is Random sample consensus method.
Privacy-preserving mechanism for social network data publishing

Privacy is receiving growing concern from various parties especially consumers due to the simplification of the collection and distribution of personal data. This research focuses on preserving privacy in social network data publishing. The study explores the data anonymization mechanism in order to improve privacy protection of social network users. We identified new type of privacy breach and has proposed an effective mechanism for privacy protection.
PyRTL in Early Undergraduate Research

Undergraduate research experiences are a promising way to broaden participation in computer architecture research and have been shown to improve student learning, engagement, and retention. These outcomes can be more profound and lasting if students experience research early. However, there are many barriers to early research in computer architecture some of which include the gap between pedagogy and research, the lower emphasis on hardware design compared to software in first year courses, and the lack of online resources. We propose lowering these barriers through a methodical approach by involving undergraduates in early research and by creating freely available and innovative educational tools for designing hardware. We present the experience of a team of undergraduate students with research over one academic year using a Python hardware description language, PyRTL. PyRTL was developed to enable early entry into digital design. Its overarching goals are simplicity, usability, clarity, and extensibility, a stark contrast to traditional languages like Verilog and VHDL that have a steep learning curve. Instead of introducing traditional languages early in the undergraduate curriculum, PyRTL takes the opposite approach, which is to build on what students already know well: a popular programming language (Python), software design patterns, and software engineering principles. The students conducted their research in the context of the Early Research Scholars Program (ERSP), a program designed to expand access to research among women and underrepresented minority students in their second year through a well designed support structure.
The Performance Gain of Cognitive Radio in Adaptive Modulation Scheme

Under the background of intelligent transportation application, QoS for various services is different in wireless communication. Based on the MAC layer protocol, this paper analyzes the QoS in IEEE 802.11 MAC protocol framework, and proposes a new design of a Differentiation Enhanced Adaptive EDCA (enhanced distribution channel access) approach. The proposed approach adjusts the window zooming dynamically according to the collision rate in sending data frames, makes random offset, and further distinguishes the competition parameters of the data frames that have the same priority, so as to reduce the conflict among the data frames, and improve the channel utilization. Experiments with different service cases were conducted. The simulation results show that: comparing with the conventional EDCA method, the proposed approach can ensure that high priority services are sent with priority, and the overall QoS is highly improved.
Tasks Without Borders : A New Approach to Online MultiTask Learning

We introduce MTLAB, a new algorithm for learning multiple related tasks with strong theoretical guarantees. Its key idea is to perform learning sequentially over the data of all tasks, without interruptions or restarts at task boundaries. Predictors for individual tasks are derived from this process by an additional online-to-batch conversion step. By learning across task boundaries, MTLAB achieves a sublinear regret of true risks in the number of tasks. In the lifelong learning setting, this leads to an improved generalization bound that converges with the total number of samples across all observed tasks, instead of the number of examples per tasks or the number of tasks independently. At the same time, it is widely applicable: it can handle finite sets of tasks, as common in multi-task learning, as well as stochastic task sequences, as studied in lifelong learning.
Polymer-like model to study the dynamics of dynamin filaments on deformable membrane tubes

Peripheral membrane proteins with intrinsic curvature can act both as sensors of membrane curvature and shape modulators of the underlying membranes. A well-studied example of such proteins is the mechano-chemical GTPase dynamin that assembles into helical filaments around membrane tubes and catalyzes their scission in a GTPase-dependent manner. It is known that the dynamin coat alone, without GTP, can constrict membrane tubes to radii of about 10 nanometers, indicating that the intrinsic shape and elasticity of dynamin filaments should play an important role in membrane remodeling. However, molecular and dynamic understanding of the process is lacking. Here, we develop a dynamical polymer-chain model for a helical elastic filament bound on a deformable membrane tube of conserved mass, accounting for thermal fluctuations in the filament and lipid flows in the membrane. The model is based on a locally-cylindrical helix approximation for dynamin. We obtain the elastic parameters of the dynamin filament by molecular dynamics simulations of its tetrameric building block and also from coarse-grained structure-based simulations of a 17-dimer filament. The results show that the stiffness of dynamin is comparable to that of the membrane. We determine equilibrium shapes of the filament and the membrane, and find that mostly the pitch of the filament, not its radius, is sensitive to variations in membrane tension and stiffness. The close correspondence between experimental estimates of the inner tube radius and those predicted by the model suggests that dynamin’s “stalk” region is responsible for its GTP-independent membrane-shaping ability. The model paves the way for future mesoscopic modeling of dynamin with explicit motor function.
Scan-Or-Not-ToScan – Balancing Network Selection Accuracy and Energy Consumption

One of the factors influencing the quality of a mobile user’s multimedia experience is the rate at which they can receive data. To connect to the wireless network that best meets their needs a user must first detect available networks and then select the most suitable network. However, it may not always be in the best interest of the user to actually invoke a network detection and selection strategy. Simulation results show that in certain conditions it is detrimental to the end user to switch networks, even when an apparently ‘better’ network is detected. In order to help decide when it is appropriate to invoke network detection and selection algorithms, this paper introduces the Scan-Or-Not-to-Scan (SONS) framework. SONS decides based on environmental inputs, when to invoke or not a network detection and selection algorithm. The use of the SONS framework enables the user to conserve energy by shutting down unused interfaces and maximise data throughput. Reducing the number of unnecessary handovers helps maintain the mobile user multimedia quality of experience. Keywords-wireless communications, advisory system, network selection
An Image Quality Assessment Method Using Models for Both Early Vision System and Visual Attention

This paper presents a comprehensive image quality assessment metric for still images. We take both early vision and visual attention models into account. The early vision model is a combination of the models of Wandell[1], Ahumada[2] and Lambrecht[2]. Device characteristics effects are also considered. An opponent color space is provided by applying true gamma corrections for red, green and blue components and using suitable different filters for each channel. The bottom-up visual attention model of Itti [4] is used to mimic later visual system effects. Several band-oriented selective Gabor filters are used to approximate neuron’s behavior in cortex. At the end, these two parts of human vision model are combined to produce the new metric. The results are compared with a subjective test on jpeg and jpeg2000 compressed images. A correlation of 72.3% with the subjective test is achieved in comparison with a 66.8% correlation of PSNR.
A Comparison of Six Methods for Missing Data Imputation

Missing data are part of almost all research and introduce an element of ambiguity into data analysis. It follows that we need to consider them appropriately in order to provide an efficient and valid analysis. In the present study, we compare 6 different imputation methods: Mean, K-nearest neighbors (KNN), fuzzy K-means (FKM), singular value decomposition (SVD), bayesian principal component analysis (bPCA) and multiple imputations by chained equations (MICE). Comparison was performed on four real datasets of various sizes (from 4 to 65 variables), under a missing completely at random (MCAR) assumption, and based on four evaluation criteria: Root mean squared error (RMSE), unsupervised classification error (UCE), supervised classification error (SCE) and execution time. Our results suggest that bPCA and FKM are two imputation methods of interest which deserve further consideration in practice.
E P ] 1 3 Ju l 2 01 7 The Resilience of Life to Astrophysical Events

Much attention has been given in the literature to the effects of astrophysical events on human and land-based life. However, little has been discussed on the resilience of life itself. Here we instead explore the statistics of events that completely sterilise an Earth-like planet with planet radii in the range 0.5 ́ 1.5RC and temperatures of „ 300 K, eradicating all forms of life. We consider the relative likelihood of complete global sterilisation events from three astrophysical sources – supernovae, gamma-ray bursts, large asteroid impacts, and passing-by stars. To assess such probabilities we consider what cataclysmic event could lead to the annihilation of not just human life, but also extremophiles, through the boiling of all water in Earth’s oceans. Surprisingly we find that although human life is somewhat fragile to nearby events, the resilience of Ecdysozoa such as Milnesium tardigradum renders global sterilisation an unlikely event.
Detection of azole resistance and ERG 11 point mutations in Candida albicans isolates from tertiary hospitals in the Philippines Moron LS

Candida albicans is commonly isolated from nosocomial fungal infections, and controlling these infections depends on the immune status of the patient, gravity of the infection, and the choice of the administered antifungal drug. Increasing worldwide reports of strains that are resistant to the azole drugs, which are commonly used for treatment of diseases caused by C. albicans, warrant the conduct of drug susceptibility testing of clinical isolates, which is not routinely done in the Philippines. Twenty-six local C. albicans clinical isolates were tested for their susceptibility to the azole drugs fluconazole and voriconazole using the standard disc agar diffusion method. Likewise, the ERG11 gene coding for lanosterol-14--demethylase involved in ergosterol synthesis, which is the target of the azole drugs, was studied for the occurrence of point mutations. Results of the assay showed phenotypic resistance patterns to both drugs in 19 isolates (or 73.08%). Six isolates were determined susceptible to both drugs, while one isolate was susceptible-dose dependent also to both antifungals. Detection of ERG11 mutations following nucleotide sequencing revealed the presence of point mutations A369C, T462C and C558T. Mutations A369C and T462C have been identified as possible factors associated with the resistance to azole agents in previous studies. The results imply that it is imperative to continuously perform susceptibility testing on clinical isolates of C. albicans for effective treatment management and for the surveillance of antifungal resistance in the organism.
Automating Large-Scale Annotation for Analysis of Social Media Content

Analytic annotation can shed light on social phenomena embedded in digitally-mediated communication, but methods of manual annotation do not scale well to larger data sets and are not well supported by existing manual labeling tools. We present a set of visual text analytics tasks for maintaining transparency as large text datasets undergo analysis through manual and automatic annotation. The discussion is grounded in our ongoing research on analyzing expressions of affect in chat logs from a distributed scientific collaboration.