Comparison Chart Research Articles

DECISION ALGORITHM FOR INTRA PREDICTION IN HIGH-EFFICIENCY VIDEO CODING (HEVC)

Prediction in HEVC exploits the redundant information in the fame to improve compression efficiency. The computational complexity of prediction is comparatively high as it recursively calculates the depth by comparing the rate-distortion optimization cost (RDO) exhaustively. The deep learning technology has shown a good mark in this area compared to traditional signal processing because of its content-based analysis and learning ability. This paper proposes a deep depth decision algorithm to predict the depth of the coding tree unit (CTU) and store it as a 16-element vector, and this model is pipelined to the HEVC encoder to compare the time taken and bit rate of encoding. The comparison chart clearly shows the reduction in computational time and enhancement in bitrate while encoding. The dataset used here is generated for the model with 110000 frames of the various resolutions, split into test, training, and validation, and trained on a depth decision model. The trained model interfaced with the HEVC encoder is compared with the normal encoder. The evaluation is done for quality check for the proposed model with BD-PSNR and BD-Bitrate shows a dip of 0.6 in BD-PSNR and increment of 6.7 in BD-Bitrate. When pipelined with the original HEVC, the RDO cost shows an improvement over existing techniques. The average encoding time is reduced by about 72% by the pipelined deep depth decision algorithm that points to the reduction in computational complexity. An average time saving of 88.49% is achieved with a deep depth decision algorithm-based encoder compared to the existing techniques.

A Qualified review of ML and DL algorithms for Bearing Fault Diagnosis

Moving machinery is the backbone of socio-economic development. The use of machines helps in increasing the production of everyday used items, and tools, that generate electricity and mechanical energy, and provides easy and fast transportation and help by saving human efforts, energy, and time. The mechanical industry is totally dependent on the bearing and it is considered bread and butter of the system. Bearing failure is about 40% of the total failures of induction motors which is why it is a crucial challenge to predict the failure and helps prevent future downtime events through maintenance schedules with the latest techniques and tools of. This paper presents a review of how DL techniques and algorithms outsmarted ML for bearing fault detection and diagnosis and summarizes the accuracy results generated by most common DL algorithms over classical ML algorithms. Additionally this paper reasons different criteria for which DL algorithms have been proved efficient for building productive model in the field of bearing fault detection. Furthermore, some of the most famous datasets by different universities have been discussed and accuracy results are provided by reviewing algorithms on the CWRU dataset by different researchers and comparison chart is listed in the results section.

Anchored ferrocene based heterogeneous electrocatalyst for the synthesis of benzimidazoles

A facile and sustainable electrochemical synthetic strategy for phenyl benzimidazoles has been developed using a ferrocene-based electrocatalyst anchored on Toray carbon paper (TCP) coated with conducting polymeric film. The developed electrode was used for the electrochemical dehydrogenative cyclization reaction of o-phenylene diamine and benzaldehyde using lithium perchlorate/acetonitrile as electrolyte. The surface characteristic properties of the developed electrode were characterized by FESEM, Optical profilometer and X-ray photoelectron spectroscopy. Electron transfer mechanism of the anchored ferrocene-based electrocatalyst was thoroughly studied. To determine the efficacy of the catalyst, the electron transfer coefficient (0.5) and apparent rate constant 41.4 s−1 were determined. The cyclic voltammetry studies reveal that the electrochemical oxidation peak for the synthesis of benzimidazole occurs at 0.48 V. The formation of the product was confirmed by Gas chromatography and Nuclear Magnetic Resonance spectroscopy. A comparison chart is presented for the green metrics and sustainability of the present strategy with other electrochemical approach.

S1400 The Complexity of NASH Cirrhosis Clinical Trials: Screen Failure Reasons and Baseline Patient Characteristics

Introduction: Patients with NASH cirrhosis has the highest likelihood of developing major adverse liver related events and an unmet need in terms of therapeutic options. Several drugs are being tested in patients with NASH cirrhosis in phase 2 trials. Screen failure (SF) reasons in non-cirrhotic NASH trials have been described; however, limited data exists on the reason for screen failure reasons in NASH cirrhosis trials. The aim of this study was to understand the reasons for screen failure in 5 NASH cirrhosis trials and to describe the patient's characteristics of both screens failed subjects and those who randomised. Methods: Data on patients who were presented for screening visits for five phase 2 NASH cirrhosis trials at one research site were analysed. The reasons for screen failure were divided into 4 major categories: 1. Biopsy, 2. Laboratory tests, 3. Imaging tests, 4. Other. Baseline characteristics including demographics, clinical history, lab values, findings from imaging tests and biopsy were collected. Characteristics of patients that screen failed were compared to those who randomised using 2-sided t-test, p value < 0.05 was considered statistically significant. Results: 68 patients were included in the analysis. 23 randomised (33.8%) and 45 screen failed (66.17%). The mean age was 57.98 years with 45% (31) of the population being male. Mean BMI in the whole population was 38.38 Kg/m2. 51.47% (35) of the patients were found to have type 2 diabetes. The reasons for screen failure were as follows: 4 (8.8%) on biopsy, 12 (26.6%) on labs, 11 (24.4%) in imaging tests, 15 (33.3%) for other reasons. The top 4 causes included in the other category were patients outside of the screening window, using prohibited medications, subject dropping out and presence of esophageal varices. There was no significant difference between the screen failure group and the randomised group in terms of platelet count, INR, bilirubin, FIB4 score and AGILE4 score (p > 0.05 for all). (Figure) Conclusion: NASH cirrhosis trials have similar screen failure rates compared to non-cirrhotic trials; however, the reasons for screen failure are different. In NASH cirrhosis trials, fewer patients screen failed because of not meeting histologic criteria on liver biopsy which has been the major reason for screen failure in non-cirrhotic trials. Baseline laboratory and imaging tests were not different between patients who screen failed and those who randomised. (Table)Figure 1.: Minor causes of screen failure Table 1. - Comparison chart showing basic characteristics of randomised and screen failure population 2 sided T Test Mean Mean Mean Total Population Randomised population Screen Failure population T-Test Age 58.31 60.95 56.88 BMI 37.38 39.88 37.05 Hba1C 6.42 6.43 6.46 % Diabetes 52.90% 48.50% 51.40% Platelets 177.23 159.26 187.30 0.13 Bilirubin 0.795 0.83 0.76 0.52 INR 1.13 1.15 1.12 0.24 kPa 23.31 24.03 22.24 0.79 Agile 4 0.44 0.518 0.42 0.23 CAP score 302.35 310.33 297.57 0.59 Fib 4 3.12 2.95 3.41 0.53

A Survey on Steganography and Steganalysis Techniques in Secret Communication

This paper presents a survey on classical steganographic algorithms and detection techniques (i.e.,steganalysis techniques) along with their mathematical definitions. A little to no studies found thattried to provide mathematical definitions of these algorithms. Wheras, mathematical definitions andexamples of different existing algorithms could help researchers to develop better understand howprevious algorithms and their limitations. In-depth understaning is important to improve existing anddevelop new algorithms. Also, this paper presents a comparison chart of existing algorithms to showadvantages and disadvantages of each steganographic algorithm in terms of steganalysis or detectiontechniques.

Study on the strength mechanism of red clay improved by waste tire rubber powder

The objective of this research is to improve the strength characteristics of red clay as a subgrade filler and increase the stability of subgrade engineering. During the laboratory tests, different amounts of waste tire rubber powder were added to the red clay. This study aims to identify the optimal amount of rubber powder required to improve the strength characteristics of red clay using a triaxial test and Duncan–Chang model. Using the depth of a field microscope, the apparent morphology of red clay and modified red clay was analyzed, and the pore variation of plain red clay and rubber powder modified red clay was described using a mercury intrusion test(MIP). The experimental results indicate that the asymptotic value of the main stress difference is significantly higher than the other four admixtures at 3%. The 3D surface comparison chart indicates that the addition of rubber powder significantly increases the relatively flat area range while reducing the overall area range. According to the comparison of porosity and contact area ratio, RPA1 is larger than RPA2, and RCA1 is smaller than RCA2. According to the characteristics of BJH pore size distribution, modified red clay has a higher pore fractal dimension than pure red clay.

Operation state assessment of wind power system based on PSO + AHP—FCE

Aiming at the shortcomings of the analytic hierarchy process in the comprehensive evaluation of wind power system operation status with strong subjectivity in determining weights, this thesis proposes an analytic hierarchy process (AHP) based on particle swarm optimization (PSO) and constructs an analytic hierarchy process combined with a particle swarm optimization algorithm (PSO + AHP) model to optimize the weights. It overcomes the disadvantage that once given the judgment matrix in the AHP method, the weight values and consistency cannot be improved. In this article, the comparison chart of the consistency indexes calculated according to this method shows that the one-time indexes of Ca as well as C1−C7 are reduced to different degrees, so a weight value with a relatively high degree of consistency can be obtained by this method. Second, for the situation that there are several judgment indexes in the sub-project layer that deviate seriously at the same time, introduce the degradation index, and apply the fuzzy comprehensive judgment method to establish the model of wind power system operation status assessment. Finally, based on the actual monitoring data of a wind farm over a period of time, its operational status was evaluated using the proposed PSO-AHP model based on FCE, and a score that can indicate the operational status can be obtained by calculation. In this article, the evaluation score of a wind farm is 0.556, indicating that the staff needs to carry out maintenance at this time. The comparative analysis shows that compared to the traditional AHP-FCE evaluation method, the assessment results proposed in this article are relatively good and have practical value and significance for improving the real-time reliability of grid-connected operation of wind turbines, optimizing the maintenance strategy of wind turbines, and reducing the cost of wind power generation.

A Water Gauge Scale Capturing Method in Tidal Well Based on Image Recognition

Tide level observation data is an important technical support data for the delimitation of warning tide level and disaster prevention. The performance of the tidal well is tested by regularly checking the external water gauge, so as to maintain the tidal follow-up and wave dissipation of the tidal well. The check of water gauge inside and outside the well shall be carried out once a month. It is time-consuming and labour consuming. The paper proposes a real-time borehole water gauge capturing algorithm in tidal well based on image recognition. Experiments have proved that the method can recognize the water gauge scale effectively. The comparison experiments with the other standard measurement method are done. It can be seen from the comparison chart that the error between the water gauge scale and the tide level value is ± 1cm, which meets the national standard.

Spring Festival Holiday Tourism Data Mining Based on the Deep Learning Model

With the advent of the era of big data, people have entered a situation of information overload, how do users filter out the information they need from a large amount of information. When users browse the website, they will record their search or click behavior, and the recommendation system will mine the data based on these data, and recommend the information they need for each user. With the birth of the recommender system, it has indeed changed the way people obtain information. Instead of relying solely on search engines to obtain information, it can obtain the information they want without people’s “consciousness.” This shift has made it easier for people to access information. This paper conducts research on travel recommendation during the Spring Festival holiday. The paper introduces deep learning model and data mining technology, proposes that the recommendation system has three important modules, and obtains the corresponding flowchart. The recommendation system was optimized, and a comparison chart of coverage before and after optimization was obtained. Before optimization, the coverage rate of cities and scenic spots was 45.52% and 21.25%, respectively, and reached 55.65% and 49.81% after optimization.

Structural Performance and Reasonable Cross-Ratio of Cross-Cable Multi-Tower Cable-Stayed Bridges

The Queensferry Crossing in the UK is the first multi-tower cable-stayed bridge in the world to use mid-span cross-stayed cables to improve structural rigidity. To study the structural performance and economy of cross-cable multi-tower cable-stayed bridges, a total of 11 finite element models were established using two cross-cable setting methods. By changing the number of crossed cables in the mid-span, the variation laws of structural deformation and internal force are obtained. The cross-cable efficiency based on structural stiffness and the cross-cable economy based on the consumption of cables used in the entire bridge are quantitatively analyzed, and it is considered that there is a reasonable cross-ratio of cross-cables. Combined with the current design specification and the empirical data of the actual bridge, the limits of the double indicators were determined, and a scheme comparison chart was formed. The results show that under the action of unbalanced load, the cross cable can greatly reduce deformation and balance the internal force of the structure. The optimal solution is to form a mid-span cable crossing by adjusting the cable spacing, and the reasonable range of cross-ratio is 15%~35%. If the structural stiffness is improved by adding additional cross cables, the cross-ratio should be controlled within 16% to ensure structural economy. This provides a reference for the design and research of cross-cable multi-tower cable-stayed bridges in the future.

Effect of the free parameters on the Biswas-Arshed model with a unified technique

The solitary dynamics of the Biswas–Arshed (BA) model without self-phase modulation are investigated in the present study. To compensate for the deserted small group velocity dispersion, the BA model includes higher-order spatio-temporal dispersion. The optical soliton solutions of the BA model are examined to use the unified strategy. The solutions to the BA model's nonlinear forms are rogue wave, periodic wave solution, periodic combined singular soliton, combined singular soliton, and periodic wave solution. The three-dimensional (3D) and two-dimensional (2D) graphs depict the dynamical physical appearance of the obtained solutions. We compared our results to those found in the existing studies. The 2D comparison chart additionally explored the consequences of the wave profile based on the values of the parameters k and δ. Finally, this technique can solve increasingly complex models, yielding a large number of soliton solutions.

Business process conceptualizations and the flexibility-support tradeoff

PurposeMany organizations struggle to achieve their desired levels of business process flexibility and support. However, these two capabilities conflict with each other and different tradeoffs have to be made. In this paper, the authors analyze different process conceptualizations and discuss their implications. The authors argue that the conceptualizations people adopt to think (conceptualize) about business processes affect the way they model them, which in turn result in different flexibility-support tradeoffs.Design/methodology/approachA set of properties is proposed to compare process conceptualizations: dominant concept, contract, and existential and representational properties. Using these properties, several process conceptualizations are analyzed and integrated in a comparison chart, which highlights different flexibility-support tradeoffs. The storytelling method is adopted to support the analytic process.FindingsThe authors show how different process conceptualizations result in different flexibility-support tradeoffs. The authors suggest that we need to intervene on a set of properties of process conceptualizations to achieve different flexibility-support tradeoffs.Research limitations/implicationsThis research contributes to understanding the relationships between process conceptualizations, process modeling, and the flexibility-support tradeoff. A comparison chart helps organizations analyze their desired levels of flexibility and support using a set of properties.Originality/valueThe extent of covered viewpoints makes this study unique in the process management field. Such effort provides a contribution towards a more multidisciplinary discussion of process models, which integrates different process conceptualizations.

Understanding Material Chemistry of Mobile Handset for Recycling Feasibility Analysis

Mobile phones and the smartness associated with them can be attributed to as the single most important factor for such transformation. With volume of mobile handsets sold seeing an increasing trend, emphasis on recycling and waste policy has increased by multifold. Schematic of metal components constituting production of a typical handset and each of the segmented parts has been showcased along with data of waste generation from various states of India. This paper discusses the economic viability of metal extraction considering factors such as metal process time, relative effort and general requirement which identifies high extraction efficiency of metal. Comparison chart has been tabulated for each of the metals with regard to expenditure, revenue generated, processing methods and processing difficulty. The results obtained provide satisfactory evidence to further improve the process to enhance the metal, calculation comparison chart represent each metal expenditure and revenue of Gold and Platinum takes more time for process i.e Au = 24hr, Pt =24hr, Zinc Copper and Aluminum takes minimum time for process Zn=1hr Cu=1hr Al=2hr. Extraction of gold and platinum process are complex compare to other metal highest expenditure cost of metal Au = 1653Rs, Minimum expenditure cost of metal Al = 620Rs Zn =620Rs, Highest revenue from Aluminum = 9000Rs. Minimum Revenue from Silver =1720Rs, Identified high extraction efficiency metals – Cu =99.95%, Al= 99%, Ag =99%. Identified maximum level of purity accepted metals Pt = 99% Au = 99%.

Developing neuropalliative care for sporadic Creutzfeldt-Jakob Disease

ABSTRACT We aimed to identify targets for neuropalliative care interventions in sporadic Creutzfeldt-Jakob disease by examining characteristics of patients and sources of distress and support among former caregivers. We identified caregivers of decedents with sporadic Creutzfeldt-Jakob disease from the University of California San Francisco Rapidly Progressive Dementia research database. We purposively recruited 12 caregivers for in-depth interviews and extracted associated patient data. We analysed interviews using the constant comparison method and chart data using descriptive statistics. Patients had a median age of 70 (range: 60–86) years and disease duration of 14.5 months (range 4–41 months). Caregivers were interviewed a median of 22 (range 11–39) months after patient death and had a median age of 59 (range 45–73) years. Three major sources of distress included (1) the unique nature of sporadic Creutzfeldt-Jakob disease; (2) clinical care issues such as difficult diagnostic process, lack of expertise in sporadic Creutzfeldt-Jakob disease, gaps in clinical systems, and difficulties with end-of-life care; and (3) caregiving issues, including escalating responsibilities, intensifying stress, declining caregiver well-being, and care needs surpassing resources. Two sources of support were (1) clinical care, including guidance from providers about what to expect and supportive relationships; and (2) caregiving supports, including connection to persons with experience managing Creutzfeldt-Jakob disease, instrumental support, and social/emotional support. The challenges and supports described by caregivers align with neuropalliative approaches and can be used to develop interventions to address needs of persons with sporadic Creutzfeldt-Jakob disease and their caregivers.

(Retracted) COVID-19 detection using machine learning: a large scale assessment of x-ray and CT image datasets

Millions of people are infected by the coronavirus disease 2019 (COVID-19) around the world. Within three months of its first report, it rapidly spread worldwide with thousands of deaths. Since that time, not only underdeveloped and developing countries, but also developed countries have suffered from insufficient medical resources and diagnoses. In this circumstance, researchers from medical and engineering fields have tried to develop automatic COVID-19 detection toolkits using machine learning (ML) techniques. The dataset is the fundamental element of any detection tool; therefore, most of the ML-based COVID-19 detection research was conducted used chest x-ray and computed tomography (CT) image datasets. In our study, we collected a series of publicly available unique COVID-19 x-ray and CT image datasets, then assessed and compared their performances using our proposed 22 layer convolutional neural network model along with ResNet-18 and VGG16. We investigated eight individual datasets known as Twitter, SIRM x-ray, COVID-19 Image Repository, EURORAD, BMICV, SIRM CT, COVID-CT, and SARS-CoV-2 CT. Our model obtained classification accuracy of 91%, 81%, 59%, 98%, 58%, 79%, and 97%, respectively. Our proposed model obtained the highest classification accuracy using four datasets (Twitter, COVID-19 Image Repository, COVID-CT, and SARS-CoV-2 CT). Similarly, ResNet-18 only utilized three (EURORAD, BMICV, and SIRM CT), whereas VGG16 only utilized the SIRM x-ray dataset. Results of this investigation indicate a significant comparison chart among the performance of the datasets. Indeed, our study is a large-scale assessment of existing COVID-19 x-ray and CT image datasets. And to the best of our knowledge, this is the first performance comparison study that includes all publicly available COVID-19 datasets.

Design of library smart cloud service system based on blockchain technology

AbstractBlockchain is equivalent to a transparent billing, and it eventually becomes a perfect storage or storage technology through many ways. Smart cloud uses internet cloud computing and other computing methods to create a scientific and humanized intelligent service system based on office. This article aims to use blockchain technology to design and study a smart cloud service system suitable for optimizing services and managing libraries. This article proposes that a special algorithm using blockchain technology can effectively improve the performance of all aspects of the smart cloud service system and improve the rating scores of users on the service system. In the experiment, the calculation of different iteration times in different algorithms of the blockchain obtains the experimental comparison chart, and it is obtained that the FUJK3 algorithm is better than the other two algorithms. The algorithm can increase the overall performance of the smart cloud service system by about 10 points, and the user's rating score for the service system by about 15 points.

Automotive Fire Control by Designing and Launching a New Intelligent System: Experimental Results, Automotive Notification Design, New Design Comparison Chart

Automotive Fire Control by Designing and Launching a New Intelligent System: Experimental Results, Automotive Notification Design, New Design Comparison Chart

Current Aspects in Early Diagnosis of Cardiotoxic Complications of Drug Therapy in Oncology: A Literature Review

This analysis presents literature data, derived from open authoritative medical sources, dealing with current methods for earliest diagnosis of cardiotoxic complications, especially in the period of their subclinical manifestations. Opportunities and difficulties of diagnosing these complications are studied using the methods suggested, at the stage of sub-clinical myocardial dysfunction. The analysis results are presented in the form of a comparison chart covering positive aspects as well as the challenges occurring in real clinical practice. The current imaging methods showing the heart tissue condition and myocardial competence, characterize the relevant parameters more accurately. In addition to that, they enable to detect minimal changes as compared with standard 3D-echocardiography with the analysis of left ventricular ejection fraction. Therefore, many more new methods for studying cardiotoxicity should be implemented in real clinical practice.

Perbandingan Kualitas Minyak Pirolisis, Minyak Tanah, dan Solar

Plastic is a polymer compound whose main constituent elements consist of carbon and hydrogen where one of the raw materials that is often used to make plastic is naphtha, which is a material produced from refining petroleum or natural gas (Surono, 2013). Chemical decomposition through a heating process without oxygen where the raw material will undergo a breakdown of the gas phase structure called pyrolysis (Jahiding et al., 2020). The quality comparison of pyrolisis oil, kerosene and oil, namely pyrolysis oil is lower than the quality of kerosene but higher than diesel oil based on density oil, duration of combustion, water temperature and volume of water that evaporates. Based on the research that has been done by Wahyudi (2018) and Mustam (2021) which is shown from the comparison chart of kerosene, pyrolysis oil and diesel oil based on the density of oil, duration of oil burning, temperature of cooked water and vaporized water volume. The quality of kerosene is better when compared to pyrolysis oil and diesel oil which is determined by the flash point of kerosene which is lower between pyrolysis oil and diesel oil, which is 47.8 o C. The flash point of diesel oil is 55 o C (the data on the flash point of kerosene and diesel oil were obtained from the Ministry of Energy and Mineral Resources in 2006). While the point of pyrolysis oil can be under the range of > 47.8 o C and < 55 o C. This is because the quality of pyrolysis oil is between kerosene and diesel oil.

Exploring and Validating Container Operational Risk Scale in Container Shipping: The Case of Ethiopian Shipping and Logistics Service Enterprise

The risk associated with container shipping has been a major concern in recent decades. This study presents three major risk frameworks to systematically and inclusively explore and validate container operational risk scales based on risk factors derived from the extant literature. The three risk frameworks identified are risks related to information flow, risks related to physical flow, and risks related to payment flow. Each risk factor is grouped into sub-factors (dimensions), three factors for information flow, two factors for physical flow, and two factors for payment flow. The study uses Ethiopia as a case study and employed both qualitative and quantitative research methods. An interview survey was conducted to explore additional risk factors and validate the identified risk factors in container shipping, and a questionnaire survey was then accompanied to collect the relevant data. A pairwise comparison chart (PCC) was employed to rank the risk dimensions. The results showed that the container operational risk model is satisfactory by employing exploratory and confirmatory factor analysis. Furthermore, the PCC result indicates that risk of loss or damage of goods/assets, payment delay, and decrease in or total loss of payment were ranked first, second, and third, respectively, and consequently the most significant dimensions of the risk factors. This study provides a reliable and valid scale for measuring container operational risk in container shipping companies. It also unlocks future works for using the identified risk factors as guidelines for researchers and experts to design and develop container operational risk dimensions.