Feature based three-dimensional object recognition using disparity maps

The human vision system is able to recognize objects it has seen before even if the particular orientation of the object being viewed was not specifically seen before. This is due to the adaptability of the cognitive abilities of the human brain to categorize objects by different features. The features and experience used in the human recognition system are also applicable to a computer recognition system. The recognition of three-dimensional objects has been a popular area in computer vision research in recent years, as computer and machine vision is becoming more abundant in areas such as surveillance and product inspection. The purpose of this study is to explore and develop an adaptive computer vision based recognition system which can recognize 3D information of an object from a limited amount of training data in the form of disparity maps. Using this system, it should be possible to recognize an object in many different orientations, even if the specific orientation had not been seen before, as well as distinguish between different objects

Anterior Cervical Discectomy and Fusion with Stand-Alone Trabecular Metal Cages as a Surgical Treatment for Cervical Radiculopathy: Mid-Term Outcomes

Study DesignRetrospective case cohort study done between 2002 and 2012.PurposeTo assess the mid-term clinical and radiological outcomes of 1-level and 2-level anterior cervical discectomy and fusion (ACDF) with stand-alone trabecular metal cages.Overview of LiteratureACDF is the gold standard surgical treatment for cervical degenerative disease. The usual surgical practice is to use an anteriorly placed fusion plate with or without interdiscal cages.MethodsPatients between 36 and 64 years of age diagnosed with cervical radiculopathy who underwent ACDF using stand-alone trabecular metal cages with at least 3 years follow-up were included in this study. Recorded clinical outcomes included residual axial neck pain, radicular arm pain, upper extremity weakness, and upper extremity altered sensation. Visual Analogue scores were also recorded. Fusion was assessed by lateral radiographs looking for bone breaching and radiolucent lines around the device at the latest follow-up.ResultsNinety patients were included in the study. Fifty-one patients underwent 2-level surgery and 39 patients underwent 1-level surgery. Mean age was 44±10.4 years and mean follow-up time was 4.5±2.6 years. Patients reported excellent or good outcomes (90%), as well as improvements in axial neck pain (80%), radicular arm pain (95%), upper extremity weakness (85%), and upper extremity altered sensation (90%). Most patients (90%) progressed to fusion at the 1-year follow-up. The reoperation rate was 3.6%. There was no reported persistent dysphagia, voice complaints, dural tear, or tracheal or oesophageal perforation in any of the patients. One patient developed a deep methicillin-resistant Staphylococcus aureus infectious infarction of the spinal cord, which was treated with antibiotics. Recovery was complete at the 1-year follow up.ConclusionsMid-term results show that surgical treatment with ACDF with trabecular metal cages is a safe and effective treatment of single and 2-level cervical disc radiculopathy and neck pain

Efficient blockchain-based group key distribution for secure authentication in VANETs

This paper proposes a group key distribution scheme using smart contract-based blockchain technology. The smart contract’s functions allow for securely distributing the group session key, following the initial legitimacy detection using public key infrastructure-based authentication. For message authentication, we propose a lightweight symmetric key cryptography-based group signature method, supporting the security and privacy requirements of vehicular ad hoc networks (VANETs). Our discussion examined the scheme’s robustness against typical adversarial attacks. To evaluate the gas costs associated with smart contract’s functions, we implemented it on the Ethereum main network. Finally, comprehensive analyses of computation and communication costs demonstrate the scheme’s effectiveness

Blockchain-based secret key extraction for efficient and secure authentication in VANETs

Intelligent transportation systems are an emerging technology that facilitates real-time vehicle-to-everything communication. Hence, securing and authenticating data packets for intra- and inter-vehicle communication are fundamental security services in vehicular ad-hoc networks (VANETs). However, public-key cryptography (PKC) is commonly used in signature-based authentication, which consumes significant computation resources and communication bandwidth for signatures generation and verification, and key distribution. Therefore, physical layer-based secret key extraction has emerged as an effective candidate for key agreement, exploiting the randomness and reciprocity features of wireless channels. However, the imperfect channel reciprocity generates discrepancies in the extracted key, and existing reconciliation algorithms suffer from significant communication costs and security issues. In this paper, PKC-based authentication is used for initial legitimacy detection and exchanging authenticated probing packets. Accordingly, we propose a blockchain-based reconciliation technique that allows the trusted third party (TTP) to publish the correction sequence of the mismatched bits through a transaction using a smart contract. The smart contract functions enable the TTP to map the transaction address to vehicle-related information and allow vehicles to obtain the transaction contents securely. The obtained shared key is then used for symmetric key cryptography (SKC)-based authentication for subsequent transmissions, saving significant computation and communication costs. The correctness and security robustness of the scheme are proved using Burrows–Abadi–Needham (BAN)-logic and Automated Validation of Internet Security Protocols and Applications (AVISPA) simulator. We also discussed the scheme’s resistance to typical attacks. The scheme’s performance in terms of packet delay and loss ratio is evaluated using the network simulator (OMNeT++). Finally, the computation analysis shows that the scheme saves ~99% of the time required to verify 1000 messages compared to existing PKC-based schemes

The relationship between tissue transglutaminase IgA antibodies and the clinical manifestations in a group of children, adolescent and adult patients with type -I diabetes mellitus

Background: Type-1 diabetes mellitus (T1-DM) is the commonest endocrine-metabolic disease in childhood. The prevalence of CD in type-1 DM ranges from 0.6 to 16.4% compared with 0.01–0.03% in the general population. The mechanism of association between the two diseases involves a shared genetic background of HLA genotype. Serum tissue transglutaminase IgA antibodies (tTG IgA) are considered specific and sensitive markers for screening of Celiac disease in more than 95 % of patients.Objective: Screening for the presence of serum tissue transglutaminase IgA antibodies (tTG ab) as a specific and sensitive biochemical marker for Celiac disease in patients with type-1DM and its relation to the clinical manifestations of those patients.Methods: One hundred-forty-nine patients with type-1 DM attending the out-patient clinic of endocrine and metabolism, Minia University Hospital were screened for the presence of serum tissue transglutaminase IgA antibodies during the period from March 2014 to November 2015.Results: Out of 149 patients 8 patients (5.3%) were positive for IgA tTG antibodies. They who were predominantly of female gender (75% were females). According to each age group, there were four sero-positive cases in children (with age group between 9 and ≤ 12 years); two cases in adolescents (with age group between 12 and ≤ 16 years) and two cases in adults (with age group 16-21 years). Intestinal manifestations, chronic diarrhea, recurrent abdominal pain/ distension, recurrent aphtha's stomatitis, anemia and bleeding tendency were significantly more common in sero-positive cases (P=0.001, 0.001, 0.016, 0.00, 0.001and 0.04 respectively). All sero-positive cases (100%) had lower BMIs than normal. There were no correlations between the tTG antibodies levels and HbA1c levels.Conclusions: The presence of tTG IgA antibodies is associated with significant changes in the clinical status of patient with type-1 DM. Celiac disease related manifestations like weight loss; anemia and chronic diarrhea were more common in sero-positive diabetic patients. Serological screening for CD should be performed in all patients with type-1DM for early diagnosis and prevention of complications.Keywords: Type-1 DM, tissue transglutaminase, IgA antibodie

An Efficient Deep Learning-based Spectrum Awareness Approach for Vehicular Communication

Constellation images of different wireless modulation orders (PSK and QAM

A Comparative Study of Single and Multi-Stage Forecasting Algorithms for the Prediction of Electricity Consumption Using a UK-National Health Service (NHS) Hospital Dataset

Accurately looking into the future was a significantly major challenge prior to the era of big data, but with rapid advancements in the Internet of Things (IoT), Artificial Intelligence (AI), and the data availability around us, this has become relatively easier. Nevertheless, in order to ensure high-accuracy forecasting, it is crucial to consider suitable algorithms and the impact of the extracted features. This paper presents a framework to evaluate a total of nine forecasting algorithms categorised into single and multistage models, constructed from the Prophet, Support Vector Regression (SVR), Long Short-Term Memory (LSTM), and the Least Absolute Shrinkage and Selection Operator (LASSO) approaches, applied to an electricity demand dataset from an NHS hospital. The aim is to see such techniques widely used in accurately predicting energy consumption, limiting the negative impacts of future waste on energy, and making a contribution towards the 2050 net zero carbon target. The proposed method accounts for patterns in demand and temperature to accurately forecast consumption. The Coefficient of Determination (R 2 ), Mean Absolute Error (MAE), and Root Mean Square Error (RMSE) were used to evaluate the algorithms’ performance. The results show the superiority of the Long Short-Term Memory (LSTM) model and the multistage Facebook Prophet model, with R 2 values of 87.20% and 68.06%, respectivel

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London