bluuebunny/crossref_metadata_2025 huggingface dataset:
A near-infrared benzoquinone-coupled BODIPY: Synthesis, spectroscopic and electrochemical properties
Authors: Gao Hu , Liu Hui , Jiang Liang , Gai Lizhi , Shen Zhen
Published: January 2019

A near-infrared absorbing boron-dipyrromethene (BODIPY) chromophore coupled with two benzoquinone moieties at its 3,5-positions, 3, was prepared via Knoevenagel condensation of 1,3,5,7-tetramethyl-8-(4[Formula: see text]-benzonitrile) BODIPY 1 with 3,5-di-tert-butyl-4-hydroxybenzaldehyde to afford 1,7-dimethyl-3,5-di-(4[Formula: see text]-hydroxy-3[Formula: see text],5[Formula: see text]-di-tert-butyl styryl)-8-(4[Formula: see text]-benzonitrile) BODIPY 2, followed by oxidization with Ag2O in good yield (91%). The UV-vis-NIR absorption spectrum of 3 exhibits two major bands at 795 and 895 nm in the near-IR region, while 2shows maximum absorbance at 661 nm and strong fluorescence at 692 nm ([Formula: see text] 0.59). The cyclic voltammetry of 3 consists of two pairs of reversible one-electron reductions at -0.61 V and -0.88 V and two pairs of one-electron oxidation waves at 0.26 V and 0.54 V. Compared with the redox potentials of 2([Formula: see text] V and [Formula: see text] 0.25 V), the first reduction of 3 is anodically shifted for 710 mV, whereas the first oxidation potential is close. Theoretical calculation reveals that conjugation with the benzoquinone moieties on the BODIPY chromophore significantly lowers the LUMO energy level and the HOMO–LUMO energy gap, resulting in a dramatic bathochromic shift of the S0–S1 transition of 3 compared with that of 2. X-ray crystallographic analysis of 3 reveals that the whole molecule adopts a V-type twisted conformation along the delocalized [Formula: see text]-conjugated pathway.
INNOVATING WITH DOMINANT SUPPLIERS: LESSONS FROM THE RACE FOR LASER LIGHT
Authors: GOLDBERG JANINA MILENA , SCHIELE HOLGER
Published: January 2019

Traditionally, manufacturers could usually choose from several suppliers who would be more than willing to engage in innovation processes with them. However, more often the situation arises that a supplier has a dominant position because of a clear leadership or even exclusivity in a certain technology. How should the buying companies handle such situations when a supplier can choose the customer to collaborate with, rather than cueing in front of the customer’s door? This paper focuses on how a buying company may best handle this situation of innovating with dominant suppliers. The methodology used is a case study that compares, from an original equipment manufacturer’s perspective, two implemented supplier innovations with different expirations — a success case and a failure.

Findings lead to three main propositions: First, firms may benefit from carefully analysing and designing the buyer–supplier constellation in innovation processes and not only the quality of the innovation. Drawing back on attractiveness theory grounded in social exchange theory may provide clues on how to do so. Second, in case of a dominant supplier situation, traditional innovation management processes may fail and need to be amended by a dedicated innovation process with a different order of steps. In the case of supplier dominance, it is essential to first analyse the supplier constellation, and then make the decision for the innovation path to follow — and not the other way around. Third, in the fight for getting access to a supplier’s innovation, a speed-up process with the buying company may be a tool for outperforming other buyers competing for the same supplier.
INITIATING OPEN INNOVATION COLLABORATIONS BETWEEN INCUMBENTS AND STARTUPS: HOW CAN DAVID AND GOLIATH GET ALONG?
Authors: DE GROOTE JULIA K. , BACKMANN JULIA
Published: January 2019

In recent years, the phenomenon of open innovation has been on the rise in established firms, especially in terms of collaboration with startups. While the success factors of open innovation endeavours have been researched intensively, how collaborations are established is not well understood. Furthermore, there is a lack of research regarding asymmetric partnerships in open innovation, occurring when incumbents and startups collaborate. This study used a qualitative research design to approach the question of how incumbents select startups as partners in open innovation. The data incorporate the perspectives of both incumbents and startups along with the views of external experts. The findings are consolidated into a process model of partner selection for open innovation.
Steam Condensation Enhancement by Applying Self-Assembled Monolayer (Chlorosilane) on Titanium Corrugated Tubes
Authors: Kim Nae-Hyun , Han Ho-Seung
Published: January 2019

It is well known that dropwise condensation enhances the condensation heat transfer coefficient significantly compared with film condensation. In the present study, dropwise condensation heat transfer characteristics on titanium corrugated tubes were investigated. Two corrugated tubes with different corrugation pitch and depth were tested at the steam pressures of 5 and 10[Formula: see text]kPa. To promote dropwise condensation, silane-based SAM was coated. For bare corrugated tubes, significant enhancement of condensation heat transfer was noted, especially for the 2.1/0.2 (corrugation pitch/corrugation depth in mm) tube. For SAM-coated tubes, the heat transfer enhancement was significant (2.61 at 5[Formula: see text]kPa and 2.45 at 10[Formula: see text]kPa) for the smooth tube. For the corrugated tubes, however, the enhancement decreased to 1.78 and 2.22 for 8.7/0.4 tube and to 1.26 and 1.52 for 2.1/0.2 tube. The present results suggest that corrugations may not be as an effective heat transfer method for dropwise condensation as it is for film condensation. This result was supported by the photos taken by mist spray, which suggested that surface tension drained condensation by corrugations is not a major heat transfer mechanism for dropwise condensation on corrugated tubes.
Structural and optical properties of a revived Pb0.5Ba1.5BiVO6 perovskite oxide
Authors: Parida R. K. , Pattanayak D. K. , Mohanty Bhagyashree , Nayak Nimai C. , Parida B. N.
Published: January 2019

The polycrystalline ceramic Pb[Formula: see text]Ba[Formula: see text]BiVO6 manifesting the complex double perovskite structure was tailored by the conventional solid state route at a moderate temperature. Qualitative phase analysis and formation of the ceramic were affirmed by XRD analysis. The X-ray powder diffraction pattern of the compound explored at room temperature affirms the single phase formation with double perovskite structure exhibiting rhombohedral phase. Microstructural analysis of the studied compound procured from the Scanning Electron Microscope (SEM) validates the formation of dense microstructures and nonuniformly distributed grains with minimal voids. Compositional analysis was shaped through the Electron Diffraction Spectroscopy (EDS) confirming the absence of contamination of any other metals apart from the mentioned ones. Dielectric (Cr and [Formula: see text]) parameters of the compound were studied using the LCR analyzer at different temperatures and wide range of frequencies. The polarization and dielectric study affirms the presence of ferroelectricity in the material with transition temperature much above the room temperature. The tangent dielectric loss of this sample being almost minimal at room temperature attributes it to find applications in different grounds of electronics. Optical equities of the ceramic were further analyzed by the RAMAN, FTIR, UV–Vis and Photoluminescence spectroscopy.
Experimental Study of Geoacoustic Inversion with Reliable Acoustic Path in the Philippine Sea
Authors: Xu Liya , Yang Kunde , Yang Qiulong
Published: January 2019

The bottom parameters of the deep ocean are difficult to obtain through in situ measurement. These parameters demonstrate a significant physical meaning for predicting sound field accurately. Thus, geoacoustic inversion is required. An acoustic experiment was performed on a reliable acoustic path (RAP) in the Philippine Sea in 2013. A single bottom-moored hydrophone was deployed as the receiver, and the explosive charges were chosen as the sources. The experimental bottom loss (BL) versus angle was obtained with the water depth above 5000[Formula: see text]m for bottom parameter inversion. The inversion sediment parameters show a clay-silt feature. The marginal probability distributions (MPDs) represent that the inversion results have a high credibility. This method provides a feasible solution for the inversion of the bottom parameters in the deep ocean.
Phosphodiesterase-4 inhibition reduces ECLS-induced vascular permeability and improves microcirculation in a rodent model of extracorporeal resuscitation
Authors: Wollborn Jakob , Siemering Svenja , Steiger Christoph , Buerkle Hartmut , Goebel Ulrich , Schick Martin A.
Published: January 2019

Extracorporeal circulation can be accompanied by increased vascular permeability leading to pathological fluid balance and organ dysfunction. The second messenger cAMP is involved in capillary permeability and maintains endothelial integrity. The aim of the present study was to evaluate the effect of phosphodiesterase-4 (PDE4) inhibition with rolipram on extracorporeal circulation-induced capillary leakage, microcirculatory dysfunction, and organ injury in rodents. Rats were randomly allocated to the following groups: sham ( n = 5), venoarterial extracorporeal circulation [extracorporeal life support (ECLS), n = 7], ECLS + rolipram ( n = 7), extracorporeal resuscitation (ECPR; n = 7), and ECPR + rolipram ( n = 7). In the groups that underwent ECPR, ECLS-based cardiopulmonary resuscitation (ECPR) was performed after the induction of hypoxic cardiac arrest. Upon return of spontaneous circulation, rolipram was administered intravenously. The mesenteric microcirculation was studied using intravital microscopy, and organ specimens were harvested upon completion of the study. ECLS and ECPR induced a proinflammatory response (cytokines IL-1β, IL-6, and TNF-α). Although PDE4 expression was upregulated in vascular tissue, PDE4 inhibition abrogated impaired microcirculation and capillary leak (albumin extravasation of the sham group: 1 ± 0.03-fold, ECLS group: 1.2 ± 0.05-fold, ECLS + rolipram group: 0.99 ± 0.04-fold, ECPR group: 1.6 ± 0.04-fold, and ECPR + rolipram group: 1.06 ± 0.02-fold from the sham group, P < 0.05). PDE4 inhibition led to stabilization of vascular cAMP levels but did not affect cytokine levels. Capillary leak was reduced, as demonstrated by the decrease of the systemic biomarkers soluble vascular-endothelial cadherin and activated complement 3. Histological analysis revealed reduced injury to the lungs and kidneys after PDE4 inhibition, with a significant decrease in systemic renal damage markers. Our findings demonstrate that extracorporeal circulation causes an inflammatory reaction associated with decreased vascular cAMP levels, increased vascular permeability, and impaired microcirculation. PDE4 inhibition proved to be capable of reducing these side effects in ECLS and ECPR, leading to reduced microcirculatory, renal, and pulmonary injury.

NEW & NOTEWORTHY Various complications are common after extracorporeal circulation. Among these, endothelial injury may cause impaired microcirculation and capillary leak. Here, we report that phosphodiesterase-4 inhibition targeting endothelial cAMP is capable of reducing microvascular complications in a rodent model of extracorporeal resuscitation. Microcirculation and vascular permeability are influenced without targeting extracorporeal circulation-induced inflammation. Thus, pulmonary and renal organ protection may be conferred.
Keratinocyte Carcinomas: Current Concepts and Future Research Priorities
Authors: Nagarajan Priyadharsini , Asgari Maryam M. , Green Adele C. , Guhan Samantha M. , Arron Sarah T. , Proby Charlotte M. , Rollison Dana E. , Harwood Catherine A. , Toland Amanda Ewart
Published: January 2019

Cutaneous squamous cell carcinoma (cSCC) and basal cell carcinoma (BCC) are keratinocyte carcinomas, the most frequently diagnosed cancers in fair-skinned populations. Ultraviolet radiation (UVR) is the main driving carcinogen for these tumors, but immunosuppression, pigmentary factors, and aging are also risk factors. Scientific discoveries have improved the understanding of the role of human papillomaviruses (HPV) in cSCC as well as the skin microbiome and a compromised immune system in the development of both cSCC and BCC. Genomic analyses have uncovered genetic risk variants, high-risk susceptibility genes, and somatic events that underlie common pathways important in keratinocyte carcinoma tumorigenesis and tumor characteristics that have enabled development of prediction models for early identification of high-risk individuals. Advances in chemoprevention in high-risk individuals and progress in targeted and immune-based treatment approaches have the potential to decrease the morbidity and mortality associated with these tumors. As the incidence and prevalence of keratinocyte carcinoma continue to increase, strategies for prevention, including effective sun-protective behavior, educational interventions, and reduction of tanning bed access and usage, are essential. Gaps in our knowledge requiring additional research to reduce the high morbidity and costs associated with keratinocyte carcinoma include better understanding of factors leading to more aggressive tumors, the roles of microbiome and HPV infection, prediction of response to therapies including immune checkpoint blockade, and how to tailor both prevention and treatment to individual risk factors and needs.
TGFβ Blockade Enhances Radiotherapy Abscopal Efficacy Effects in Combination with Anti-PD1 and Anti-CD137 Immunostimulatory Monoclonal Antibodies
Authors: Rodríguez-Ruiz María E. , Rodríguez Inmaculada , Mayorga Lina , Labiano Tania , Barbes Benigno , Etxeberria Iñaki , Ponz-Sarvise Mariano , Azpilikueta Arantza , Bolaños Elixabet , Sanmamed Miguel F. , Berraondo Pedro , Calvo Felipe A. , Barcelos-Hoff Mary Helen , Perez-Gracia Jose L. , Melero Ignacio
Published: January 2019

Radiotherapy can be synergistically combined with immunotherapy in mouse models, extending its efficacious effects outside of the irradiated field (abscopal effects). We previously reported that a regimen encompassing local radiotherapy in combination with anti-CD137 plus anti–PD-1 mAbs achieves potent abscopal effects against syngeneic transplanted murine tumors up to a certain tumor size. Knowing that TGFβ expression or activation increases in irradiated tissues, we tested whether TGFβ blockade may further enhance abscopal effects in conjunction with the anti–PD-1 plus anti-CD137 mAb combination. Indeed, TGFβ blockade with 1D11, a TGFβ-neutralizing mAb, markedly enhanced abscopal effects and overall treatment efficacy against subcutaneous tumors of either 4T1 breast cancer cells or large MC38 colorectal tumors. Increases in CD8 T cells infiltrating the nonirradiated lesion were documented upon combined treatment, which intensely expressed Granzyme-B as an indicator of cytotoxic effector capability. Interestingly, tumor tissue but not healthy tissue irradiation results in the presence of higher concentrations of TGFβ in the nonirradiated contralateral tumor that showed smad2/3 phosphorylation increases in infiltrating CD8 T cells. In conclusion, radiotherapy-induced TGFβ hampers abscopal efficacy even upon combination with a potent immunotherapy regimen. Therefore, TGFβ blockade in combination with radioimmunotherapy results in greater efficacy.
Insight into the Etiology of Undifferentiated Soft Tissue Sarcomas from a Novel Mouse Model
Authors: Fleming Jonathan T. , Brignola Emily , Chen Lei , Guo Yan , Zhao Shilin , Wang Quan , Li Bingshan , Correa Hernán , Ermilov Alexandre N. , Dlugosz Andrzej A. , Chiang Chin
Published: January 2019

Aberrant activation of the Hedgehog signaling pathway has been linked to the formation of numerous cancer types, including the myogenic soft tissue sarcoma, embryonal rhabdomyosarcoma (eRMS). Here, we report PCG2, a novel mouse model in which human GLI2A, a constitutive activator of Hedgehog signaling, induced undifferentiated sarcomas that were phenotypically divergent from eRMS. Rather, sarcomas arising in PCG2 mice featured some characteristics that were reminiscent of Ewing sarcoma. Even though it is widely understood that Ewing sarcoma formation is driven by EWS-ETS gene fusions, a genetically defined mouse model is not well-established. While EWS-ETS gene fusions were not present in PCG2 sarcomas, precluding their designation as Ewing sarcoma, we did find that GLI2A induced expression of known EWS-ETS gene targets essential to Ewing pathogenesis, most notably, Nkx2.2. Moreover, we found that naïve mesenchymal progenitors originate tumors in PCG2 mice. Altogether, our work provides a novel genetic mouse model, which directly connects oncogenic Hedgehog activity to the etiology of undifferentiated soft tissue sarcomas for the first time.

Implications:

The finding that activation of Gli2 transcription factor is sufficient to induce Ewing-like sarcomas provides a direct transformative role of the Hedgehog signaling pathway in undifferentiated soft tissue sarcoma.
Age Invariant Face Recognition using Convolutional Neural Network
Authors: Nimbarte Mrudula , Bhoyar Kishor
Published: January 2019

In the recent years, face recognition across aging has become very popular and challenging task in the area of face recognition.  Many researchers have contributed in this area, but still there is a significant gap to fill in. Selection of feature extraction and classification algorithms plays an important role in this area. Deep Learning with Convolutional Neural Networks provides us a combination of feature extraction and classification in a single structure. In this paper, we have presented a novel idea of 7-Layer CNN architecture for solving the problem of aging for recognizing facial images across aging. We have done extensive experimentations to test the performance of the proposed system using two standard datasets FGNET and MORPH(Album II). Rank-1 recognition accuracy of our proposed system is 76.6% on FGNET and 92.5% on MORPH(Album II). Experimental results show the significant improvement over available state-of- the-arts with the proposed CNN architecture and the classifier.
Throughput Maximization of Cognitive Radio Multi Relay Network with Interference Management
Authors: Varade Pradip , Wabale Akanksha , Yerram Ravinder , Jaiswal Rupesh
Published: January 2019

In this paper, an Orthogonal Frequency Division Multiplexing (OFDM) based cognitive multi relay network is investigated to maximize the transmission rate of the cognitive radio (CR) with enhanced  fairness among CR users  with interference to the primary users (PUs) being managed below a certain threshold level. In order to improve the transmission rate of the CR, optimization of the subcarrier pairing and power allocation is to be carried out simultaneously. Firstly joint optimization problem is formulated and Composite Genetic and Ordered Subcarrier Pairing (CGOSP) algorithm is proposed to solve the problem. The motivation behind merging genetic and OSP algorithm is to reduce the complexity of Genetic Algorithm (GA). Further, to have a fair allocation of resources among CR users, the Round Robin allocation method is adopted so as to allocate subcarrier pairs to relays efficiently. The degree of fairness of the system is calculated using Jain’s Fairness Index (JFI). Simulation results demonstrate the significant improvement in transmission rate of the CR, low computational complexity and enhanced fairness.
A Survey: Data Leakage Detection Techniques
Authors: Wagh K. S.
Published: January 2019

Data is an important property of various organizations and it is intellectual property of organization. Every organization includes sensitive data as customer information, financial data, data of patient, personal credit card data and other information based on the kinds of management, institute or industry. For the areas like this, leakage of information is the crucial problem that the organization has to face, that poses high cost if information leakage is done. All the more definitely, information leakage is characterize as the intentional exposure of individual or any sort of information to unapproved outsiders. When the important information is goes to unapproved hands or moves towards unauthorized destination. This will prompts the direct and indirect loss of particular industry in terms of cost and time. The information leakage is outcomes in vulnerability or its modification. So information can be protected by the outsider leakages. To solve this issue there must be an efficient and effective system to avoid and protect authorized information. From not so long many methods have been implemented to solve same type of problems that are analyzed here in this survey.  This paper analyzes little latest techniques and proposed novel Sampling algorithm based data leakage detection techniques.
Handover Algorithm based VLP using Mobility Prediction Database for Vehicular Network
Authors: Hasbollah Arfah A. , S. Ariffin Sharifah H. , Ghazali Nurzal E. , Yusuf K. Mohamad , Morino Hiroaki
Published: January 2019

This paper proposes an improved handover algorithm method for vehicle location prediction (VLP-HA) using mobility prediction database. The main advantage of this method is the mobility prediction database is based on real traffic data traces. Furthermore, the proposed method has the ability to reduce handover decision time and solve resource allocation problem. The algorithm is simple and can be computed very rapidly; thus, its implementation for a high-speed vehicle is possible. To evaluate the effectiveness of the proposed method, QualNet simulation is carried out under different velocity scenarios. Its performance is compared with conventional handover method. The superiority of the proposed method over conventional handover method in deciding the best handover location and choosing candidate access points is highlighted by simulation. It was found that VLP-HA has clearly reduced handover delay by 45% compared to handover without VLP, give high accuracy, hence low complexity algorithm.
Web based Water Turbidity Monitoring and Automated Filtration System: IoT Application in Water Management
Authors: Ibrahim S. Noorjannah , Asnawi A. L. , Malik N. Abdul , Mohd Azmin N. F. , Jusoh A. Z. , Mohd Isa F. N.
Published: January 2019

Water supplied to residential areas is prone to contaminants due to pipe residues and silt, and therefore resulted in cloudiness, unfavorable taste, and odor in water. Turbidity, a measure of water cloudiness, is one of the important factors for assessing water quality. This paper proposes a low-cost turbidity system based on a light detection unit to measure the cloudiness in water. The automated system uses Intel Galileo 2 as the microprocessor and a server for a web-based monitoring system. The turbidity detection unit consists of a Light Dependent Resistor (LDR) and a Light Emitting Diode (LED) inside a polyvinyl chloride (PVC) pipe. Turbidity readings were recorded for two different positionings; 90° and 180° between the detector (LDR) and the incident light (LED). Once the turbidity level reached a threshold level, the system will trigger the filtration process to clean the water. The voltage output captured from the designed system versus total suspended solid (TSS) in sample water is graphed and analyzed in two different conditions; in total darkness and in the present of ambient light. This paper also discusses and compares the results from the above-mentioned conditions when the system is submerged in still and flowing water. It was found that the trends of the plotted graph decline when the total suspended solid increased for both 90° and 180° detector turbidimeter in all conditions which imitate the trends of a commercial turbidimeter. By taking the consideration of the above findings, the design can be recommended for a low-cost real-time web-based monitoring system of the water quality in an IOT environment.
A CORDIC based QR Decomposition Technique for MIMO Detection
Authors: A. Shirly Edward , S. Malarvizhi
Published: January 2019

CORDIC based improved real and complex QR Decomposition (QRD) for channel pre-processing operations in (Multiple-Input Multiple-Output) MIMO detectors are presented in this paper. The proposed design utilizes pipelining and parallel processing techniques and reduces the latency and hardware complexity of the module respectively. Computational complexity analysis report shows the superiority of our module by 16% compared to literature. The implementation results reveal that the proposed QRD takes shorter latency compared to literature. The power consumption of 2x2 real channel matrix and 2x2 complex channel matrix was found to be 12mW and 44mW respectively on the state-of-the-art Xilinx Virtex 5 FPGA.
Background Estimation Using Principal Component Analysis Based on Limited Memory Block Krylov Subspace Optimization
Authors: Sari Ilmiyati , Juarna Asep , Harmanto Suryadi , Kerami Djati
Published: January 2019

Given a video of 𝑀 frames of size ℎ × 𝑤. Background components of a video are the elements matrix which relative constant over 𝑀 frames. In PCA (principal component analysis) method these elements are referred as “principal components”. In video processing, background subtraction means excision of background component from the video. PCA method is used to get the background component. This method transforms 3 dimensions video (ℎ × 𝑤 × 𝑀) into 2 dimensions one (𝑁 × 𝑀), where 𝑁 is a linear array of size ℎ × 𝑤. The principal components are the dominant eigenvectors which are the basis of an eigenspace. The limited memory block Krylov subspace optimization then is proposed to improve performance the computation. Background estimation is obtained as the projection each input image (the first frame at each sequence image) onto space expanded principal component. The procedure was run for the standard dataset namely SBI (Scene Background Initialization) dataset consisting of 8 videos with interval resolution [146 150, 352 240], total frame [258,500]. The performances are shown with 8 metrics, especially (in average for 8 videos) percentage of error pixels (0.24%), the percentage of clustered error pixels (0.21%), multiscale structural similarity index (0.88 form maximum 1), and running time (61.68 seconds). 
Modelling and Passivity-based Control of a Non-isolated DC-DC Converter in a Fuel Cell System
Authors: Ahmed Moutabir , Elhassane Abdelmounim , Mohamed Aboulfatah
Published: January 2019

This paper presents the model of a fuel cell and the design and simulation of a cascade of two DC-DC converters. First, a detailed mathematical model of fuel cell is presented and simulated. Then, a nonlinear model of the whole controlled system is developed and a robust nonlinear controller of currents is synthesized using a passivity-based control. A formal analysis based on Lyapunov stability and average theory is developed to describe the control currents loops performances. A classical PI controller is used for the voltages loops. The simulation models have been developed and tested in the MATLAB/SIMULINK. Simulated results are displayed to validate the feasibility and the effectiveness of the proposed strategy.
A New Approach to the Detection of Mammogram Boundary
Authors: Rmili Mohammed , Moutaouakkil Abdelmajid El , Saleck Mousatapha M. , Bouchaib Maksi , Adnani Fatiha , Aroussi El Mehdi El
Published: January 2019

Mammography is a method used for the detection of breast cancer. computer-aided diagnostic (CAD) systems help the radiologist in the detection and interpretation of mass in breast mammography. One of the important information of a mass is its contour and its form because it provides valuable information about the abnormality of a mass. The accuracy in the recognition of the shape of a mass is related to the accuracy of the detected mass contours. In this work we propose a new approach for detecting the boundaries of lesion in mammography images based on region growing algorithm without using the threshold, the proposed method requires an initial rectangle surrounding the lesion selected manually by the radiologist (Region Of Interest), where the region growing algorithm applies on lines segments that attach each pixel of this rectangle with the seed point, such as the ends (seeds) of each line segment grow in a direction towards one another. The proposed approach is evaluated on a set of data with 20 masses of the MIAS base whose contours are annotated manually by expert radiologists. The performance of the method is evaluated in terms of specificity, sensitivity, accuracy and overlap. All the findings and details of approach are presented in detail.
An Efficient Filtering Technique for Denoising Colour Images
Authors: Sai K. Arun , Ravi K.
Published: January 2019

Single-sensor digital cameras capture image with the aid of masking the sensor surface along a colour filter array(CFA) such that every sensor pixel solely samples certain of three primary colour values i.e., R (red)，G (green) and B (blue). To get a full-colour image, an interpolation method commonly referred in conformity with CFA demosaicking is required to estimate the other two contributions for producing a full-colour image. But, the clutter in imaging sensors not only corrupts the colour filter array but also introduces artifacts at some stage in the colour interpolation step and affects the characteristics of image. To acquire high quality full-colour image, a kind of viable and effective interpolation algorithm based over gradient is used. This technique can remove the noise effectively by retaining image border and detail data clearly.
A Study on Big Data Privacy Protection Models using Data Masking Methods
Authors: A. Archana R. , Hegadi Ravindra S. , N. Manjunath T.
Published: January 2019

In today’s predictive analytics world, data engineering play a vital role, data acquisition is carried out from various source systems and process as per the business applications and domain. Big Data integrates, governs, and secures big data with repeatable, reliable, and maintainable processes. Through volume, speed, and assortment of information characteristics try to reveal business esteem from enormous information. However, with information that is frequently deficient, conflicting, ungoverned, and unprotected, which is hazardous and enormous information being a risk instead of an advantage. What's more, with conventional methodologies that are manual and unpredictable, huge information ventures take too long to acknowledge business esteem. Reasonably and over and again conveying business esteem from enormous information requires another technique. In this connection, raw data has to be moved between onsite and offshore environment during this course of action, data privacy is a major concern and challenge. A Big Data Privacy platform can make it easier to detect, investigate, assess, and remediate threats from intruders. We tried to do complete study of Big Data Privacy using data masking methods on various data loads and different types. This work will help data quality analyst and big data developers while building the big data applications.
A Framework for Arabic Concept-Level Sentiment Analysis using SenticNet
Authors: Hassan Hend G. , Bakr Hitham M. Abo , Ziedan Ibrahim E.
Published: January 2019

Arabic Sentiment analysis research field has been progressing in a slow pace compared to English and other languages. In addition to that most of the contributions are based on using supervised machine learning algorithms while comparing the performance of different classifiers with different selected stylistic and syntactic features. In this paper, we presented a novel framework for using the Concept-level sentiment analysis approach which classifies text based on their semantics rather than syntactic features. Moreover, we provided a lexicon dataset of around 69 k unique concepts that covers multi-domain reviews collected from the internet. We also tested the lexicon on a test sample from the dataset it was collected from and obtained an accuracy of 70%. The lexicon has been made publicly available for scientific purposes.
Performance Analysis of IEEE 802.15.4 Transceiver System under Adaptive White Gaussian Channel
Authors: Kadhum Ekhlas , Haitham Russul
Published: January 2019

Zigbee technology has been developed for short range wireless sensor networks and it follows IEEE 802.15.4 standard. For such sensors, several considerations should be taken including; low data rate and less design complexity in order to achieve efficient performance considering to the transceiver systems. This research focuses on implementing a digital transceiver system for Zigbee sensor based on IEEE 802.15.4. The system is implemented using offset quadrature phase shift keying (OQPSK) modulation technique with half sine pulse-shaping method. Direct conversion scheme has been used in the design of Zigbee receiver in order to fulfill the requirements mentioned above. System performance is analyzed considering to BER when it encountered adaptive white Gaussian noise (AWGN), besides showing the effect of using direct sequence spread spectrum (DSSS) technique.
Classification of Macronutrient Deficiencies in Maize Plant Using Machine Learning
Authors: N Leena , Saju K. K.
Published: January 2019

Detection of nutritional deficiencies in plants is vital for improving crop productivity. Timely identification of nutrient deficiency through visual symptoms in the plants can help farmers take quick corrective action by appropriate nutrient management strategies. The application of computer vision and machine learning techniques offers new prospects in non-destructive field-based analysis for nutrient deficiency. Color and shape are important parameters in feature extraction. In this work, two different techniques are used for image segmentation and feature extraction to generate two different feature sets from the same image sets. These are then used for classification using different machine learning techniques. The experimental results are analyzed and compared in terms of classification accuracy to find the best algorithm for the two feature sets.
Adding Psychological Factor in the Model of Electricity Consumption in Office Building
Authors: Susanty Meredita
Published: January 2019

Researches indicate that energy behaviour is the key to energy conservation and suggest that comparative feedback on energy usage can generate savings in residential and organizational settings. In implementing comparative feedback in workplace, there are two different ways to disaggregate collective energy consumption and apportion it to building users; individual or group level. This research uses agent-based modelling and simulation to examine the impact of applying different approaches of energy data apportionment to change staff behaviour toward energy consumption reduction. A simulation model of energy consumption in workplace as a base model is a re-implementation and simplification from former research. Several psychological factors and decision-making mechanism are then being added as an extension. The model divides staffs into four energy awareness stereotypes based on motivation level. Sensitivity analysis suggests that motivation is an important factor in changing user‟s behaviour and the experiment results indicates greater potential for energy saving when energy usage is apportioned to group level. The significant difference of energy consumption level makes user with low and medium motivation should become the target of energy reduction campaign.
Domain Examination of Chaos Logistics Function As A Key Generator in Cryptography
Authors: Wowor Alz Danny , Liwandouw Vania Beatrice
Published: January 2019

The use of logistics functions as a random number generator in a cryptography algorithm is capable of accommodating the diffusion properties of the Shannon principle. The problem that occurs is initialization x was static and was not affected by changes in the key, so that the algorithm will generate a random number that is always the same. This study design three schemes that can providing the ﬂexibility of the input keys in conducting the examination of the value of the domain logistics function. The results of each schemes do not show a pattern that is directly proportional or inverse with the value of x0 and relative error x and successfully fulﬁll the properties of the butterﬂy effect. Thus, the existence of logistics functions in generating chaos numbers can be accommodated based on key inputs. In addition, the resulting random numbers are distributed evenly over the chaos range, thus reinforcing the algorithm when used as a key in cryptography.
A Critical Review of Time-frequency Distribution Analysis for Detection and Classification of Harmonic Signal in Power Distribution System
Authors: Jopri M. H. , Abdullah A. R. , Sutikno T. , Manap M. , Ghani M. R. Ab , Yusoff M. R.
Published: January 2019

This paper presents a critical review of time-frequency distributions (TFDs) analysis for detection and classification of harmonic signal. 100 unique harmonic signals comprise of numerous characteristic are detected and classified by using spectrogram, Gabor transform and S-transform. The rulebased classifier and the threshold settings of the analysis are according to the IEEE Standard 1159 2009. The best TFD for harmonic signals detection and classification is selected through performance analysis with regards to the accuracy, computational complexity and memory size that been used during the analysis.
Hysteresis Loops for Magnetoelectric Multiferroics Using Landau-Khalatnikov Theory
Authors: Gunawan Vincensius , Umiati Ngurah Ayu Ketut
Published: January 2019

We present a theoretical discussion of the hysteresis in magnetoelectric multiferroics with bi-quadratic magnetoelectric coupling. The calculations were performed by employing Landau-Khalatnikov equation of motion for both the ferroelectric and ferromagnetic phase, then solve it simultaneously. In magnetoelectric, we obtain four types of hysteresis: ferroelectric hysteresis, ferromagnetic hysteresis and two types of cross hysteresis (electric field versus magnetization and magnetic field versus electric polarization). The cross hysteresis has butterfly shape which agree with the result from the previous research. It can also be seen from that hysteresis, that magnetization / electric polarization can not be flipped into the opposite direction using external electric / magnetic field when the magnetoelectric coupling is bi-quadratic type. Overall, the result shows that Landau-Khalatnikov equation is able to approximate hysteresis loops in multiferroics system.
A Comparison Study of Reactive Power Control Strategies in Wind Farms with SVC and STATCOM
Authors: Cherkaoui Nazha , Haidi Touria , Belfqih Abdelaziz , Mariami Faissal El , Boukherouaa Jamal
Published: January 2019

In the recent years, the integration of the wind farms into the electrical grids has increased rapidly. Especially, the wind power plants made up with doubly fed induction generators due to its many advatanges, such as being able to control its reactive power. Hence, some countries have published grid code requirements related to the reactive power that the wind turbines have to satisfy. This paper presents a coordinated reactive power control strategy in which STATCOM and doubly fed induction generators in wind power plants are used in order to bring back the voltage at the point of common coupling in the allowable range. First, reactive power requirements that the wind farms have to fulfill in some European countries are introduced. Second, the reactive power limitations of 2MW doubly fed induction generator are determined. Then, the static synchronous compensator (STATCOM) and the synchronous var compensator (SVC) FACTS (Flexible AC Transmission Systems) devices are presented. Finaly, various reactive power control strategies are applied to 10 MW wind farm, and the simulation results are analysed and compared.
An Efficient Activity Detection System based on Skeleton Joints Identification
Authors: P.S Abdul Lateef Haroon , Eranna U.
Published: January 2019

The increasing criminal activities in the current world has drawn lot of interest activity recognition techniques which helps to perform the sophistical analytical operations on human activity and also helps to interface the human and computer interactions. From the existing review analysis it is found that most of the existing systems are not emphasize on computational performance but are more application specific by identifying specific problems. Hence, it is found that all the features are not required for accurate and cost effective human activity detection. Thus, the human skelton action can be considered and presented a simple and accurate process to identify the significant joints only. From the outcomes it is found that the proposed system is cost effective and computational efficient activity recognition technique for human actions.
Using Data Mining to Identify COSMIC Function Point Measurement Competence
Authors: Bagriyanik Selami , Karahoca Adem
Published: January 2019

Cosmic Function Point (CFP) measurement errors leads budget, schedule and quality problems in software projects. Therefore, it’s important to identify and plan requirements engineers’ CFP training need quickly and correctly. The purpose of this paper is to identify software requirements engineers’ COSMIC Function Point measurement competence development need by using machine learning algorithms and requirements artifacts created by engineers. Used artifacts have been provided by a large service and technology company ecosystem in Telco. First, feature set has been extracted from the requirements model at hand. To do the data preparation for educational data mining, requirements and COSMIC Function Point (CFP) audit documents have been converted into CFP data set based on the designed feature set. This data set has been used to train and test the machine learning models by designing two different experiment settings to reach statistically significant results. Ten different machine learning algorithms have been used. Finally, algorithm performances have been compared with a baseline and each other to find the best performing models on this data set. In conclusion, REPTree, OneR, and Support Vector Machines (SVM) with Sequential Minimal Optimization (SMO) algorithms achieved top performance in forecasting requirements engineers’ CFP training need.
Negative Total Float to Improve a Multi-Objective Integer Non-Linear Programming for Project Scheduling Compression
Authors: Fachrurrazi Fachrurrazi , Abdullah Abdullah , Away Yuwaldi , Aulia Teuku Budi
Published: January 2019

This paper presents Multi-Objective Integer Non-Linear Programming (MOINLP) involving Negative Total Float (NTF) for improving the basic model of Multi-Objective Programming (MOP) in case the optimization of the additional cost for Project Scheduling Compression (PSC). Using the basic MOP to solve the more complex problems is a challenging task. We suspect that Negative Total Float (NTF) having an indication to make the basic MOP to solve the more general case, both simple and complex of PSC. The purpose of this research is identifying the conflicting objectives in PSC problem using NTF and improving MOINLP by involving the NTF parameter to solve the PSC problem. The Solver Application, which is an add-in of MS Excel, is used to perform optimization process to the model developed. The results show that NTF has an important role to identify the conflicting objectives in PSC. We define NTF is an automatic maximum value of the activity duration reduction to achieve due date of PSC. Furthermore, the use of NTF as a constraint in MOINLP can solve the more general case for both simple and complex PSC problem. Base on the condition, we state that the basic MOP is still significant to solve the PSC complex problems using MOINLP as a sophisticated MOP technique.
Complaint Analysis in Indonesian Language Using WPKE and RAKE Algorithm
Authors: Wongso Rini , Hanafiah Novita , Hartanto Jaka , Kevin Alexander , Sutanto Charles , Kesuma Fiona
Published: January 2019

Social media provides convenience in communicating and can present two-way communication that allows companies to interact with their customer. Companies can use information obtained from social media to analyze how the communities respond to their services or products. The biggest challenge in processing information in social media like Twitter, is the unstructured sentences which could lead to incorrect text processing. However, this information is very important for companies’ survival. In this research, we proposed a method to extract keywords from tweets in Indonesian language, WPKE. We compared it with RAKE, an algorithm that is language independent and usually used for keyword extraction. Finally, we develop a method to do clustering to groups the topics of complaints with data set obtained from Twitter using the “komplain” hashtag. Our method can obtain the accuracy of 72.92% while RAKE can only obtain 35.42%.
HOPX Crossover Operator for the Fixed Charge Logistic Model with Priority Based Encoding
Authors: Idrissi Ahmed Lahjouji El , Tajani Chakir , Sabbane Mohamed
Published: January 2019

In this paper, we are interested to an important Logistic problem modelised us optimization problem. It is the fixed charge transportation problem (FCTP) where the aim is to find the optimal solution which minimizes the objective function containig two costs, variable costs proportional to the amount shipped and fixed cost regardless of the quantity transported. To solve this kind of problem, metaheuristics and evolutionary methods should be applied. Genetic algorithms (GAs) seem to be one of such hopeful approaches which is based both on probability operators (Crossover and mutation) responsible for widen the solution space. The different characteristics of those operators influence on the performance and the quality of the genetic algorithm. In order to improve the performance of the GA to solve the FCTP, we propose a new adapted crossover operator called HOPX with the priority-based encoding by hybridizing the characteristics of the two most performent operators, the Order Crossover (OX) and Position-based crossover (PX). Numerical results are presented and discussed for several instances showing the performance of the developed approach to obtain optimal solution in reduced time in comparison to GAs with other crossover operators.
Automation of DMPS Manufacturing by using LabView & PLC
Authors: F Fareeza , Rambabu Chunchu , Krishnaveni S. , Kabiso Abel Chernet
Published: January 2019

This Paper is to enable the Siemens (Programmable Logic Control) CPU 313-5A to communicate with the Lab VIEW and to control the process accuracy by image processing. The communication between CPU 313-5A and Lab VIEW is via OPC (OLE for Process Control).Process Accuracy is achieved with the use of Labview Image Processing and Gray Scale matching Pattern. Accuracy in the gray scale matching will purely depend on the calibration of the camera with respect to the corresponding image. The digital output from the labview is communicated to PLC via Ethernet Protocol for the industrial process control. With the use of Labview the dead time while using the normal image vision module in PLC can be minimized. Labview uses the gray scale matching technique which is more accurate than the normal image vision module used in PLC.