Image Compression Techniques: A Survey in Lossless and Lossy algorithms

The bandwidth of the communication networks has been increased continuously as results of technological advances. However, the introduction of new services and the expansion of the existing ones have resulted in even higher demand for the bandwidth. This explains the many efforts currently being invested in the area of data compression. The primary goal of these works is to develop techniques of coding information sources such as speech, image and video to reduce the number of bits required to represent a source without significantly degrading its quality. With the large increase in the generation of digital image data, there has been a correspondingly large increase in research activity in the field of image compression. The goal is to represent an image in the fewest number of bits without losing the essential information content within. Images carry three main type of information: redundant, irrelevant, and useful. Redundant information is the deterministic part of the information, which can be reproduced without loss from other information contained in the image. Irrelevant information is the part of information that has enormous details, which are beyond the limit of perceptual significance (i.e., psychovisual redundancy). Useful information, on the other hand, is the part of information, which is neither redundant nor irrelevant. Human usually observes decompressed images. Therefore, their fidelities are subject to the capabilities and limitations of the Human Visual System. This paper provides a survey on various image compression techniques, their limitations, compression rates and highlights current research in medical image compression

Interfacial cracks in bi-material solids: Stroh formalism and skew-symmetric weight functions

A new general approach for deriving the weight functions for 2D interfacial cracks in anisotropic bimaterials has been developed.For perfect interface conditions, the new method avoid the use of Wiener-Hopf technique and the challenging factorization problem connected. Both symmetric and skew-symmetric weight functions can be derived by means of the new approach. Weight functions can be used for deriving singular integral formulation of interfacial cracks in anisotropic media. The proposed method can be applied for studying interfacial cracks problems in many materials:monoclinic, orthotropic, cubic, piezoelectrics, poroelastics, quasicrystals

Hybrid Neural Network Predictive-Wavelet Image Compression System

This paper considers a novel image compression technique called hybrid predictive wavelet coding. The new proposed technique combines the properties of predictive coding and discrete wavelet coding. In contrast to JPEG2000, the image data values are pre-processed using predictive coding to remove interpixel redundancy. The error values, which are the difference between the original and the predicted values, are discrete wavelet coding transformed. In this case, a nonlinear neural network predictor is utilised in the predictive coding system. The simulation results indicated that the proposed technique can achieve good compressed images at high decomposition levels in comparison to JPEG2000

A position paper on predicting the onset of nocturnal enuresis using advanced machine learning

Bed-wetting during normal sleep in children and young people has a significant impact on the child and their parents. The condition is known as nocturnal enuresis and its underlying cause has been subject to different explanatory factors that include, neurological, urological, sleep, genetic and psychosocial influences. Several clinical and technological interventions for managing nocturnal enuresis exist that include the clinician’s opinions, pharmacology interventions, and alarm systems. However, most have failed to produce any convincing results. Clinical information is often subjective and often inaccurate, the use of desmopressin and tricyclic antidepressants only report between 20 % and 40 % success, and alarms only a 50 % success fate. This position paper posits an alternative research idea concerned with the early detection of impending involuntary bladder release. The proposed framework is a measurement and prediction system that processes moisture and bladder volume data from sensors fitted into undergarments that are used by patients suffering with nocturnal enuresis. The proposed framework represents a level of sophistication in nocturnal enuresis treatment not previously considered

Detection and quantification of nitric oxide–derived oxidants in biological systems

The free radical nitric oxide (NO) exerts biological effects through the direct and reversible interaction with specific targets (e.g. soluble guanylate cyclase) or through the generation of secondary species, many of which can oxidize, nitrosate or nitrate biomolecules. The NO -derived reactive species are typically short-lived, and their preferential fates depend on kinetic and compartmentalization aspects. Their detection and quantification are technically challenging. In general, the strategies employed are based either on the detection of relatively stable end products or on the use of synthetic probes, and they are not always selective for a particular species. In this study, we describe the biologically relevant characteristics of the reactive species formed downstream from NO , and we discuss the approaches currently available for the analysis of NO , nitrogen dioxide (NO2 ), dinitrogen trioxide (N2O3), nitroxyl (HNO), and peroxynitrite (ONOO /ONOOH), as well as peroxynitrite-derived hydroxyl (HO) and carbonate anion (CO3) radicals. We also discuss the biological origins of and analytical tools for detecting nitrite (NO2), nitrate (NO3), nitrosyl–metal complexes, S-nitrosothiols, and 3-nitrotyrosine. Moreover, we highlight state– of–the–art methods, alert readers to caveats of widely used techniques, and encourage retirement of approaches that have been supplanted by more reliable and selective tools for detecting and measuring NO -derived oxidants. We emphasize that the use of appropriate analytical methods needs to be strongly grounded in a chemical and biochemical understanding of the species and mechanistic pathways involveAgencia Nacional de Investigación e Innovación FCE_1_2017_1_136043Comisión Sectorial de Investigación Científica (CSIC)Universidad de la República. Espacio Interdisciplinari

A Framework to Support Ubiquitous Healthcare Monitoring and Diagnostic for Sickle Cell Disease

Recent technology advances based on smart devices have improved the medical facilities and become increasingly popular in association with real-time health monitoring and remote/personals health-care. Healthcare organisations are still required to pay more attention for some improvements in terms of cost-effectiveness and maintaining efficiency, and avoid patients to take admission at hospital. Sickle cell disease (SCD) is one of the most challenges chronic obtrusive disease that facing healthcare, affects a large numbers of people from early childhood. Currently, the vast majority of hospitals and healthcare sectors are using manual approach that depends completely on patient input, which can be slowly analysed, time consuming and stressful. This work proposes an alert system that could send instant information to the doctors once detects serious condition from the collected data of the patient. In addition, this work offers a system that can analyse datasets automatically in order to reduce error rate. A machine-learning algorithm was applied to perform the classification process. Two experiments were conducted to classify SCD patients from normal patients using machine learning algorithm in which 99 % classification accuracy was achieved using the Instance-based learning algorithm

An Investigation into Gender Disparities in the Field of Computing

This paper explains the reasons as to why there is under-representation of females computer science. Recent research undertaken at a British University focused on gender imbalance amongst academic staff in the Faculty of Technology and Environment, Liverpool John Moores University. The paper presents evidence that suggests the significance of identifying female role models in the field as a precursor to improving the current gender imbalance amongst academic faculty. In addition, the paper suggests the importance of addressing the negative stereotypical images related to the discipline and suggests the importance of identifying barriers to access and mobility females encounter in the field. The results of this initial investigation demonstrate the subjective belief amongst female academic faculty that in the School of Computing is dominated by male academics. Further, this belief pattern manifests itself in a perceived lack of motivation for promotion in the School. It can be concluded that the deeply entrenched belief system determines a lack of attempts to seek and secure promotion amongst all grades of female faculty. The paper proposes recommendations which the School could adopt to improve recruitment and retention of female academic staff and students

Verifikasi Lapangan Peta Kemiskinan Indonesia 2010

Laporan studi verifikasi lapangan ini merupakan salah satu bagian dari studi peta kemiskinan dan penghidupan Indonesia. studi ini bertujuan untuk membuat estimasi angka kemiskinan di wilayah kecil, hingga tingkat kecamatan dan desa/kelurahan, serta menyusun peta kemiskinan dan penghidupan masyarakat. estimasi angka kemiskinan dibuat untuk seluruh Indonesia berdasarkan pendekatan pengeluaran rumah tangga dengan menggunakan data-data dari survey sosial-ekonomi nasional (susenas) 2010, potensi desa (podes) 2011, dan sensus penduduk (sp) 2010. studi verifikasi lapangan peta kemiskinan Indonesia 2010 ini dilakukan untuk mengetahui apakah estimasi kemiskinan yang telah dilakukan sesuai dengan kondisi kemiskinan masyarakat sebenarnya. studi ini dilakukan di tiga provinsi (Sulawesi Selatan, Nusa Tenggara Barat, dan bangka belitung) dan dilaksanakan pada tiga kabupaten/kota di setiap provinsi sebagai sampel (kota parepare, kabupaten sumbawa barat dan kabupaten bangka barat). pengumpulan data dilakukan melalui focus group discussion (fgd) di tingkat kabupaten, kecamatan dan desa untuk mengetahui gambaran kondisi kemiskinan di masing-masing wilayah. selain itu, juga dilakukan wawancara dengan aparat pemerintah, tokoh masyarakat dan penduduk desa/kelurahan untuk memperkaya informasi kondisi kemiskinan masyarakat. analisis data dilakukan dengan menggunakan rank correlation dan pairwaise correlation sebagai alat untuk mengetahui kesesuian antara hasil estimasi kemiskinan dengang hasil fgd dan wawancara. secara rata-rata, lebih dari 55% ranking antardaerah berdasarkan estimasi kemiskinan 2010 sesuai dengan hasil fgd untuk kondisi tahun 2010 dan 2013. tingkat kesesuaian ranking 2010 lebih baik dari pada tahun 2013. di kabupaten yang sama, kecamatan yang memiliki nilai relative standard error (rse) yang tinggi memiliki rank correlation dan tingkat kesesuaian (match) yang lebih rendah jika dibandingkan dengan kecamatan yang memiliki rse rendah. perbandingan antara kondisi kemiskinan berdasarkan garis kemiskinan nasional (gkn) dengan garis kemiskinan $2 purchasing power parity (ppp) pada 2010 dan 2013 memperlihatkan bahwa persepsi masyarakat terhadap proporsi penduduk miskin berdasarkan standar lokal lebih mendekati angka proporsi penduduk di bawah$2ppp daripada proporsi penduduk di bawah gkn. oleh karena itu, estimasi angka kemiskinan 2010 di tingkat kecamatan dan desa/kelurahan ini perlu digunakan dengan kehati-hatian, dengan memperhatikan nilai rse, Perubahan kondisi saat ini dibandingkan dengan kondisi 2010 dan karakteristik lokal yang ada. kata kunci: peta kemiskinan, verifikasi, fgd, rank correlation, pairwaise correlatio

Association Mapping Approach into Type 2 Diabetes using Biomarkers and Clinical Data

The global growth in incidence of Type 2 Diabetes (T2D) has become a major international health concern. As such, understanding the aetiology of Type 2 Diabetes is vital. This paper investigates a variety of statistical method-ologies at various level of complexity to analyse genotype data and identify bi-omarkers that show evidence of increase susceptibility to T2D and related traits. A critical overview of several selected statistical methods for population-based association mapping particularly case-control genetic association analysis is pre-sented. A discussion on a dataset accessed in this paper that includes 3435 female subjects for cases and controls with genotype information across 879071 Single Nucleotide Polymorphism (SNPs) is presented. Quality control steps into the dataset through pre-processing phase are performed to remove samples and markers that failed the quality control test. Association analysis is discussed to address which statistical method can be appropriate to the dataset. Our genetic association analysis produces promising results and indicated that Allelic asso-ciation test showed one SNP above the genome-wide significance threshold of 5×10−8 which is rs10519107 (Odds Ratio (OR)=0.7409,P−Value (P)=1.813×10−9), While, there are several SNPs above the suggestive association threshold of 5×10−6 these SNPs could worth further investigation. Furthermore, Logistic Regression analysis adjusted for multiple confounder factors indicated that none of the genotyped SNPs has passed genome-wide significance threshold of 5×10−8 . Nevertheless, four SNPs (rs10519107, rs4368343, rs6848779, rs11729955) have passed suggestive association threshold