Search results for: incomplete count data
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 24861

Search results for: incomplete count data

24501 The Effect of Mist Cooling on Sexual Behavior and Semen Quality of Sahiwal Bulls

Authors: Khalid Ahmed Elrabie Abdelrasoul

Abstract:

The present study was carried out on Sahiwal cattle bulls maintained at the Artificial Breeding Complex, NDRI, Karnal, Hayana, India, to assess the effect of cooling using mist cooling and fanning on Sahiwal bulls in the dry hot summer season. Fourteen Sahiwal bulls were divided into two groups of seven each. Sexual behavior and semen quality traits considered were: Reaction time (RT), Dismounting time (DMT), Total time taken in mounts (TTTM), Flehmen response (FR), Erection Score (ES), Protrusion Score (PS), Intensity of thrust (ITS), Temperament Score (TS), Libido Score (LS), Semen volume, Physical appearance, Mass activity, Initial progressive motility, Non-eosinophilic spermatozoa count (NESC) and post thaw motility percent. Data were analyzed by least squares technique. Group-1 was the control, whereas group-2 (treatment group) bulls were exposed to mist cooling and fanning (thrice a day 15 min each) in the dry hot summer season. Group-2 showed significantly (p < 0.01) higher value in DMT (sec), ES, PS, ITS, LS, semen volume (ml), semen color density, mass activity, initial motility, progressive motility and live sperm.

Keywords: mist cooling, Sahiwal bulls, semen quality, sexual behavior

Procedia PDF Downloads 296
24500 Linguistic Analysis of Borderline Personality Disorder: Using Language to Predict Maladaptive Thoughts and Behaviours

Authors: Charlotte Entwistle, Ryan Boyd

Abstract:

Recent developments in information retrieval techniques and natural language processing have allowed for greater exploration of psychological and social processes. Linguistic analysis methods for understanding behaviour have provided useful insights within the field of mental health. One area within mental health that has received little attention though, is borderline personality disorder (BPD). BPD is a common mental health disorder characterised by instability of interpersonal relationships, self-image and affect. It also manifests through maladaptive behaviours, such as impulsivity and self-harm. Examination of language patterns associated with BPD could allow for a greater understanding of the disorder and its links to maladaptive thoughts and behaviours. Language analysis methods could also be used in a predictive way, such as by identifying indicators of BPD or predicting maladaptive thoughts, emotions and behaviours. Additionally, associations that are uncovered between language and maladaptive thoughts and behaviours could then be applied at a more general level. This study explores linguistic characteristics of BPD, and their links to maladaptive thoughts and behaviours, through the analysis of social media data. Data were collected from a large corpus of posts from the publicly available social media platform Reddit, namely, from the ‘r/BPD’ subreddit whereby people identify as having BPD. Data were collected using the Python Reddit API Wrapper and included all users which had posted within the BPD subreddit. All posts were manually inspected to ensure that they were not posted by someone who clearly did not have BPD, such as people posting about a loved one with BPD. These users were then tracked across all other subreddits of which they had posted in and data from these subreddits were also collected. Additionally, data were collected from a random control group of Reddit users. Disorder-relevant behaviours, such as self-harming or aggression-related behaviours, outlined within Reddit posts were coded to by expert raters. All posts and comments were aggregated by user and split by subreddit. Language data were then analysed using the Linguistic Inquiry and Word Count (LIWC) 2015 software. LIWC is a text analysis program that identifies and categorises words based on linguistic and paralinguistic dimensions, psychological constructs and personal concern categories. Statistical analyses of linguistic features could then be conducted. Findings revealed distinct linguistic features associated with BPD, based on Reddit posts, which differentiated these users from a control group. Language patterns were also found to be associated with the occurrence of maladaptive thoughts and behaviours. Thus, this study demonstrates that there are indeed linguistic markers of BPD present on social media. It also implies that language could be predictive of maladaptive thoughts and behaviours associated with BPD. These findings are of importance as they suggest potential for clinical interventions to be provided based on the language of people with BPD to try to reduce the likelihood of maladaptive thoughts and behaviours occurring. For example, by social media tracking or engaging people with BPD in expressive writing therapy. Overall, this study has provided a greater understanding of the disorder and how it manifests through language and behaviour.

Keywords: behaviour analysis, borderline personality disorder, natural language processing, social media data

Procedia PDF Downloads 307
24499 Molecular Insights into the 5α-Reductase Inhibitors: Quantitative Structure Activity Relationship, Pre-Absorption, Distribution, Metabolism, and Excretion and Docking Studies

Authors: Richa Dhingra, Monika, Manav Malhotra, Tilak Raj Bhardwaj, Neelima Dhingra

Abstract:

5-Alpha-reductases (5AR), a membrane bound, NADPH dependent enzyme and convert male hormone testosterone (T) into more potent androgen dihydrotestosterone (DHT). DHT is the required for the development and function of male sex organs, but its overproduction has been found to be associated with physiological conditions like Benign Prostatic Hyperplasia (BPH). Thus the inhibition of 5ARs could be a key target for the treatment of BPH. In present study, 2D and 3D Quantitative Structure Activity Relationship (QSAR) pharmacophore models have been generated for 5AR based on known inhibitory concentration (IC₅₀) values with extensive validations. The four featured 2D pharmacophore based PLS model correlated the topological interactions (–OH group connected with one single bond) (SsOHE-index); semi-empirical (Quadrupole2) and physicochemical descriptors (Mol. wt, Bromines Count, Chlorines Count) with 5AR inhibitory activity, and has the highest correlation coefficient (r² = 0.98, q² =0.84; F = 57.87, pred r² = 0.88). Internal and external validation was carried out using test and proposed set of compounds. The contribution plot of electrostatic field effects and steric interactions generated by 3D-QSAR showed interesting results in terms of internal and external predictability. The well validated 2D Partial Least Squares (PLS) and 3D k-nearest neighbour (kNN) models were used to search novel 5AR inhibitors with different chemical scaffold. To gain more insights into the molecular mechanism of action of these steroidal derivatives, molecular docking and in silico absorption, distribution, metabolism, and excretion (ADME) studies were also performed. Studies have revealed the hydrophobic and hydrogen bonding of the ligand with residues Alanine (ALA) 63A, Threonine (THR) 60A, and Arginine (ARG) 456A of 4AT0 protein at the hinge region. The results of QSAR, molecular docking, in silico ADME studies provide guideline and mechanistic scope for the identification of more potent 5-Alpha-reductase inhibitors (5ARI).

Keywords: 5α-reductase inhibitor, benign prostatic hyperplasia, ligands, molecular docking, QSAR

Procedia PDF Downloads 139
24498 Frequent Item Set Mining for Big Data Using MapReduce Framework

Authors: Tamanna Jethava, Rahul Joshi

Abstract:

Frequent Item sets play an essential role in many data Mining tasks that try to find interesting patterns from the database. Typically it refers to a set of items that frequently appear together in transaction dataset. There are several mining algorithm being used for frequent item set mining, yet most do not scale to the type of data we presented with today, so called “BIG DATA”. Big Data is a collection of large data sets. Our approach is to work on the frequent item set mining over the large dataset with scalable and speedy way. Big Data basically works with Map Reduce along with HDFS is used to find out frequent item sets from Big Data on large cluster. This paper focuses on using pre-processing & mining algorithm as hybrid approach for big data over Hadoop platform.

Keywords: frequent item set mining, big data, Hadoop, MapReduce

Procedia PDF Downloads 394
24497 Operative Technique of Glenoid Anteversion Osteotomy and Soft Tissue Rebalancing for Brachial Plexus Birth Palsy

Authors: Michael Zaidman, Naum Simanovsky

Abstract:

The most of brachial birth palsies are transient. Children with incomplete recovery almost always develop an internal rotation and adduction contracture. The muscle imbalance around the shoulder results in glenohumeral joint deformity and functional limitations. Natural history of glenohumeral deformity is it’s progression with worsening of function. Anteversion glenoid osteotomy with latissimus dorsi and teres major tendon transfers could be an alternative procedure of proximal humeral external rotation osteotomy for patients with severe glenohumeral dysplasia secondary to brachial plexus birth palsy. We will discuss pre-operative planning and stepped operative technique of the procedure on clinical example.

Keywords: obstetric brachial plexus palsy, glenoid anteversion osteotomy, tendon transfer, operative technique

Procedia PDF Downloads 41
24496 The Role Of Data Gathering In NGOs

Authors: Hussaini Garba Mohammed

Abstract:

Background/Significance: The lack of data gathering is affecting NGOs world-wide in general to have good data information about educational and health related issues among communities in any country and around the world. For example, HIV/AIDS smoking (Tuberculosis diseases) and COVID-19 virus carriers is becoming a serious public health problem, especially among old men and women. But there is no full details data survey assessment from communities, villages, and rural area in some countries to show the percentage of victims and patients, especial with this world COVID-19 virus among the people. These data are essential to inform programming targets, strategies, and priorities in getting good information about data gathering in any society.

Keywords: reliable information, data assessment, data mining, data communication

Procedia PDF Downloads 158
24495 Cosmetic Dermatology Procedures: Survey Results of American Society for Dermatologic Surgery

Authors: Marina S. Basta, Kirollos S. Basta

Abstract:

Cosmetic dermatology procedures have witnessed exponential growth and diversification over the last 10 years. Thus, the purpose of this study was to collect data about the latest trends for cosmetic procedures reported by dermatologists during the year 2018. This study was performed by American Society for Dermatologic Surgery (ASDS) in 2018 through sending survey invitations to 3,358 practicing dermatologists in the U.S. containing streamline questions as well as statistical questions targeted to specific analysis of cosmetic dermatology trends. Out of the targeted physicians, only 596 dermatologists reply to the survey invitation (15% overall response rate). It was noted that data collected from that survey was generalized to represent all ASDS members. Results show that there is an increase in cosmetic dermatology procedures since 12.5 million procedures were reported for 2018 compared to only 7.8 million for 2012. Injectable neuromodulators and soft tissue fillers have topped the list with a 3.7 million procedure count. Body sculpting, chemical peeling, hair transplantation, and microneedling procedures were reported to be 1.57 million cases combined. Also, the top two procedures using laser were represented in wrinkle treatment as well as sun damage correction, while the lowest two trends for laser usage were for treatments of tattoos and birthmarks. Cryolipolysis was found to be at the head of body sculpting procedures with 287,435 cases, while tumescent liposuction was reported as the least performed body sculpting procedure (18,286 cases). In conclusion, comparing the procedural trends for the last 7 years has indicated that there has been a 78% increase in soft tissue filler treatment compared to 2012. In addition, it was further noted that laser procedures scored 74% increase in the last 7 years while body contouring procedures have had four folds increase in general compared to 2012.

Keywords: cosmetic dermatology, ASDS procedure survey, laser, body sculpting

Procedia PDF Downloads 107
24494 The Application of Data Mining Technology in Building Energy Consumption Data Analysis

Authors: Liang Zhao, Jili Zhang, Chongquan Zhong

Abstract:

Energy consumption data, in particular those involving public buildings, are impacted by many factors: the building structure, climate/environmental parameters, construction, system operating condition, and user behavior patterns. Traditional methods for data analysis are insufficient. This paper delves into the data mining technology to determine its application in the analysis of building energy consumption data including energy consumption prediction, fault diagnosis, and optimal operation. Recent literature are reviewed and summarized, the problems faced by data mining technology in the area of energy consumption data analysis are enumerated, and research points for future studies are given.

Keywords: data mining, data analysis, prediction, optimization, building operational performance

Procedia PDF Downloads 825
24493 To Handle Data-Driven Software Development Projects Effectively

Authors: Shahnewaz Khan

Abstract:

Machine learning (ML) techniques are often used in projects for creating data-driven applications. These tasks typically demand additional research and analysis. The proper technique and strategy must be chosen to ensure the success of data-driven projects. Otherwise, even exerting a lot of effort, the necessary development might not always be possible. In this post, an effort to examine the workflow of data-driven software development projects and its implementation process in order to describe how to manage a project successfully. Which will assist in minimizing the added workload.

Keywords: data, data-driven projects, data science, NLP, software project

Procedia PDF Downloads 57
24492 Assessment of Cattle Welfare Traveling Long Distance from Jessore (Indian Border) to Chittagong, Bangladesh

Authors: Mahabub Alam, Mohammad Mahmudul Hassan, M. Hasanuzzaman, M. Ahasanul Hoque

Abstract:

Animals are transported from one place to another for different purposes in Bangladesh. However, the potential effect of long-distance transport on cattle health has not frequently been studied. Therefore, this study was conducted to assess health conditions of cattle transported from a long distance to Chittagong in Bangladesh. A total of 100 adult cattle, regardless of breed and sex, were selected at Benapole live cattle market in Jessore between August and September 2015 for the study. Blood samples were taken from 50 randomly selected cattle at 0 hours before transportation, just after transportation, at 12-16 hours post-conclusion of transportation, and 24 hours after transportation. The external health conditions and injuries of the cattle were assessed by close inspection, and the trader was interviewed using the structured questionnaire. Images of cattle injuries were taken with a camera. The basic internal health of the cattle was evaluated using standard hemato-biochemical tests. Animals were fasted and remained standing within a small space allocation (8-10 sq feet/animal) in the vehicle during transportation. Animals were provided only with paddy straw and water prior to selling at the destination market. The overall frequency of cattle injuries varied significantly (26% before vs. 47% after transportation; p < 0.001). The frequency of different cattle injuries also significantly varied by types such as abrasion (11% vs. 21%; p < 0.05) and barbed wire injury (9% vs. 18%; p < 0.05). Single cattle injury differed significantly (21% vs. 36%; p < 0.001). Cattle health conditions varied significantly (nasal discharge: 15% vs. 28%; p < 0.05; diarrhea: 15% vs. 23%; p < 0.05 and severe dehydration: 8% vs. 20%; p < 0.001). The values of hemoglobin (Hb), total erythrocyte count (TEC), total leukocyte count (TLC), lymphocyte (L), neutrophil (N) and eosinophil (E) varied significantly (p ≤ 0.01) (Hb: 11.1mg/dl vs. 12.3mg/dl; TEC: 4.7 million/ml vs. 5.7million/ml; TLC: 6.2 thousand/ml vs. 7.3 thousand/ml; L: 61.7% vs. 58.1%; N: 29.7% vs. 32.8%; E: 3.8% vs. 4.7%). The values of serum total protein (TP), creatine kinase (CK), triglyceride (TG), calcium (Ca), phosphorus (P) and alkaline phosphatase (ALP) significantly differed (p ≤ 0.05) (TP: 6.8g/dl vs. 8.2g/dl; CK:574.9u/l vs. 1288u/l; TG: 104.7mg/dl vs. 127.7mg/dl; Ca: 11.3mg/dl vs. 13mg/dl; P: 7.3mg/dl vs. 7.6mg/dl; ALP: 303u/l vs. 363u/l). The identified status of external and internal health conditions of the cattle for trading purpose due to long-distance transportation in the present study indicates a high degree of transport stress and poor animal welfare.

Keywords: animal welfare, cattle, external and internal health conditions, transportation

Procedia PDF Downloads 153
24491 Deep Learning for Renewable Power Forecasting: An Approach Using LSTM Neural Networks

Authors: Fazıl Gökgöz, Fahrettin Filiz

Abstract:

Load forecasting has become crucial in recent years and become popular in forecasting area. Many different power forecasting models have been tried out for this purpose. Electricity load forecasting is necessary for energy policies, healthy and reliable grid systems. Effective power forecasting of renewable energy load leads the decision makers to minimize the costs of electric utilities and power plants. Forecasting tools are required that can be used to predict how much renewable energy can be utilized. The purpose of this study is to explore the effectiveness of LSTM-based neural networks for estimating renewable energy loads. In this study, we present models for predicting renewable energy loads based on deep neural networks, especially the Long Term Memory (LSTM) algorithms. Deep learning allows multiple layers of models to learn representation of data. LSTM algorithms are able to store information for long periods of time. Deep learning models have recently been used to forecast the renewable energy sources such as predicting wind and solar energy power. Historical load and weather information represent the most important variables for the inputs within the power forecasting models. The dataset contained power consumption measurements are gathered between January 2016 and December 2017 with one-hour resolution. Models use publicly available data from the Turkish Renewable Energy Resources Support Mechanism. Forecasting studies have been carried out with these data via deep neural networks approach including LSTM technique for Turkish electricity markets. 432 different models are created by changing layers cell count and dropout. The adaptive moment estimation (ADAM) algorithm is used for training as a gradient-based optimizer instead of SGD (stochastic gradient). ADAM performed better than SGD in terms of faster convergence and lower error rates. Models performance is compared according to MAE (Mean Absolute Error) and MSE (Mean Squared Error). Best five MAE results out of 432 tested models are 0.66, 0.74, 0.85 and 1.09. The forecasting performance of the proposed LSTM models gives successful results compared to literature searches.

Keywords: deep learning, long short term memory, energy, renewable energy load forecasting

Procedia PDF Downloads 237
24490 The Relationship Between Artificial Intelligence, Data Science, and Privacy

Authors: M. Naidoo

Abstract:

Artificial intelligence often requires large amounts of good quality data. Within important fields, such as healthcare, the training of AI systems predominately relies on health and personal data; however, the usage of this data is complicated by various layers of law and ethics that seek to protect individuals’ privacy rights. This research seeks to establish the challenges AI and data sciences pose to (i) informational rights, (ii) privacy rights, and (iii) data protection. To solve some of the issues presented, various methods are suggested, such as embedding values in technological development, proper balancing of rights and interests, and others.

Keywords: artificial intelligence, data science, law, policy

Procedia PDF Downloads 87
24489 Self-Inflating Soft Tissue Expander Outcome for Alveolar Ridge Augmentation a Randomized Controlled Clinical and Histological Study

Authors: Alaa T. Ali, Nevine H. Kheir El Din, Ehab S. Abdelhamid, Ahmed E. Amr

Abstract:

Objective: Severe alveolar bone resorption is usually associated with a deficient amount of soft tissues. soft tissue expansion is introduced to provide an adequate amount of soft tissue over the grafted area. This study aimed to assess the efficacy of sub-periosteal self-inflating osmotic tissue expanders used as preparatory surgery before horizontal alveolar ridge augmentation using autogenous onlay block bone graft. Methods: A prospective randomized controlled clinical trial was performed. Sixteen partially edentulous patients demanding horizontal bone augmentation in the anterior maxilla were randomly assigned to horizontal ridge augmentation with autogenous bone block grafts harvested from the mandibular symphysis. For the test group, soft tissue expanders were placed sub-periosteally before horizontal ridge augmentation. Impressions were taken before and after STE, and the cast models were optically scanned and superimposed to be used for volumetric analysis. Horizontal ridge augmentation was carried out after STE completion. For the control group, a periosteal releasing incision was performed during bone augmentation procedures. Implants were placed in both groups at re-entry surgery after six months period. A core biopsy was taken. Histomorphometric assessment for newly formed bone surface area, mature collagen area fraction, the osteoblasts count, and blood vessel count were performed. The change in alveolar ridge width was evaluated through bone caliper and CBCT. Results: Soft tissue expander successfully provides a Surplus amount of soft tissues in 5 out of 8 patients in the test group. Complications during the expansion period were perforation through oral mucosa occurred in two patients. Infection occurred in one patient. The mean soft tissue volume gain was 393.9 ± 322mm. After 6 months. The mean horizontal bone gains for the test and control groups were 3.14 mm and 3.69 mm, respectively. Conclusion: STE with a sub-periosteal approach is an applicable method to achieve an additional soft tissue and to reduce bone block graft exposure and wound dehiscence.

Keywords: soft tissue expander, ridge augmentation, block graft, symphysis bone block

Procedia PDF Downloads 102
24488 Simulation Data Summarization Based on Spatial Histograms

Authors: Jing Zhao, Yoshiharu Ishikawa, Chuan Xiao, Kento Sugiura

Abstract:

In order to analyze large-scale scientific data, research on data exploration and visualization has gained popularity. In this paper, we focus on the exploration and visualization of scientific simulation data, and define a spatial V-Optimal histogram for data summarization. We propose histogram construction algorithms based on a general binary hierarchical partitioning as well as a more specific one, the l-grid partitioning. For effective data summarization and efficient data visualization in scientific data analysis, we propose an optimal algorithm as well as a heuristic algorithm for histogram construction. To verify the effectiveness and efficiency of the proposed methods, we conduct experiments on the massive evacuation simulation data.

Keywords: simulation data, data summarization, spatial histograms, exploration, visualization

Procedia PDF Downloads 157
24487 A Study of Electrowetting-Assisted Mold Filling in Nanoimprint Lithography

Authors: Wei-Hsuan Hsu, Yi-Xuan Huang

Abstract:

Nanoimprint lithography (NIL) possesses the advantages of sub-10-nm feature and low cost. NIL patterns the resist with physical deformation using a mold, which can easily reproduce the required nano-scale pattern. However, the variation of process parameters and environmental conditions seriously affect reproduction quality. How to ensure the quality of imprinted pattern is essential for industry. In this study, the authors used the electrowetting technology to assist mold filling in the NIL process. A special mold structure was designed to cause electrowetting. During the imprinting process, when a voltage was applied between the mold and substrate, the hydrophilicity/hydrophobicity of the surface of the mold can be converted. Both simulation and experiment confirmed that the electrowetting technology can assist mold filling and avoid incomplete filling rate. The proposed method can also reduce the crack formation during the de-molding process. Therefore, electrowetting technology can improve the process quality of NIL.

Keywords: electrowetting, mold filling, nano-imprint, surface modification

Procedia PDF Downloads 148
24486 The Association between Affective States and Sexual/Health-Related Status among Men Who Have Sex with Men in China: An Exploration Study Using Social Media Data

Authors: Zhi-Wei Zheng, Zhong-Qi Liu, Jia-Ling Qiu, Shan-Qing Guo, Zhong-Wei Jia, Chun Hao

Abstract:

Objectives: The purpose of this study was to understand and examine the association between diurnal mood variation and sexual/health-related status among men who have sex with men (MSM) using data from MSM Chinese Twitter messages. The study consists of 843,745 postings of 377,610 MSM users located in Guangdong that were culled from the MSM Chinese Twitter App. Positive affect, negative affect, sexual related behaviors, and health-related status were measured using the Simplified Chinese Linguistic Inquiry and Word Count. Emotions, including joy, sadness, anger, fear, and disgust were measured using the Weibo Basic Mood Lexicon. A positive sentiment score and a positive emotions score were also calculated. Linear regression models based on a permutation test were used to assess associations between affective states and sexual/health-related status. In the results, 5,871 active MSM users and their 477,374 postings were finally selected. MSM expressed positive affect and joy at 8 a.m. and expressed negative affect and negative emotions between 2 a.m. and 4 a.m. In addition, 25.1% of negative postings were directly related to health and 13.4% reported seeking social support during that sensitive period. MSM who were senior, educated, overweight or obese, self-identified as performing a versatile sex role, and with less followers, more followers, and less chat groups mainly expressed more negative affect and negative emotions. MSM who talked more about sexual-related behaviors had a higher positive sentiment score (β=0.29, p < 0.001) and a higher positive emotions score (β = 0.16, p < 0.001). MSM who reported more on their health status had a lower positive sentiment score (β = -0.83, p < 0.001) and a lower positive emotions score (β = -0.37, p < 0.001). The study concluded that psychological intervention based on an app for MSM should be conducted, as it may improve mental health.

Keywords: affect, men who have sex with men, sexual related behavior, health-related status, social media

Procedia PDF Downloads 139
24485 Effects of Mild Heat Treatment on the Physical and Microbial Quality of Salak Apricot Cultivar

Authors: Bengi Hakguder Taze, Sevcan Unluturk

Abstract:

Şalak apricot (Prunus armeniaca L., cv. Şalak) is a specific variety grown in Igdir, Turkey. The fruit has distinctive properties distinguish it from other cultivars, such as its unique size, color, taste and higher water content. Drying is the widely used method for preservation of apricots. However, fresh consumption is preferred for Şalak apricot instead of drying due to its low dry matter content. Higher amounts of water in the structure and climacteric nature make the fruit sensitive against rapid quality loss during storage. Hence, alternative processing methods need to be introduced to extend the shelf life of the fresh produce. Mild heat (MH) treatment is of great interest as it can reduce the microbial load and inhibit enzymatic activities. Therefore, the aim of this study was to evaluate the impact of mild heat treatment on the natural microflora found on Şalak apricot surfaces and some physical quality parameters of the fruit, such as color and firmness. For this purpose, apricot samples were treated at different temperatures between 40 and 60 ℃ for different periods ranging between 10 to 60 min using a temperature controlled water bath. Natural flora on the fruit surfaces was examined using standard plating technique both before and after the treatment. Moreover, any changes in color and firmness of the fruit samples were also monitored. It was found that control samples were initially containing 7.5 ± 0.32 log CFU/g of total aerobic plate count (TAPC), 5.8±0.31 log CFU/g of yeast and mold count (YMC), and 5.17 ± 0.22 log CFU/g of coliforms. The highest log reductions in TAPC and YMC were observed as 3.87-log and 5.8-log after the treatments at 60 ℃ and 50 ℃, respectively. Nevertheless, the fruit lost its characteristic aroma at temperatures above 50 ℃. Furthermore, great color changes (ΔE ˃ 6) were observed and firmness of the apricot samples was reduced at these conditions. On the other hand, MH treatment at 41 ℃ for 10 min resulted in 1.6-log and 0.91-log reductions in TAPC and YMC, respectively, with slightly noticeable changes in color (ΔE ˂ 3). In conclusion, application of temperatures higher than 50 ℃ caused undesirable changes in physical quality of Şalak apricots. Although higher microbial reductions were achieved at those temperatures, temperatures between 40 and 50°C should be further investigated considering the fruit quality parameters. Another strategy may be the use of high temperatures for short time periods not exceeding 1-5 min. Besides all, MH treatment with UV-C light irradiation can be also considered as a hurdle strategy for better inactivation results.

Keywords: color, firmness, mild heat, natural flora, physical quality, şalak apricot

Procedia PDF Downloads 113
24484 Content Analysis of Gucci’s ‘Blackface’ Sweater Controversy across Multiple Media Platforms

Authors: John Mark King

Abstract:

Beginning on Feb. 7, 2019, the luxury brand, Gucci, was met with a firestorm on social media over fashion runway images of its black balaclava sweater, which covered the bottom half of the face and featured large, shiny bright red lips surrounding the mouth cutout. Many observers on social media and in the news media noted the garment resembled racist “blackface.” This study aimed to measure how items were framed across multiple media platforms. The unit of analysis was any headline or lead paragraph published using the search terms “Gucci” and “sweater” or “jumper” or “balaclava” during the one-year timeframe of Feb. 7, 2019, to Feb. 6, 2020. Limitations included headlines and lead paragraphs published in English and indexed in the Lexis/Nexis database. Independent variables were the nation in which the item was published and the platform (newspapers, blogs, web-based publications, newswires, magazines, or broadcast news). Dependent variables were tone toward Gucci (negative, neutral or positive) and frame (blackface/racism/racist, boycott/celebrity boycott, sweater/balaclava/jumper/fashion, apology/pulling the product/diversity initiatives by Gucci or frames unrelated to the controversy but still involving Gucci sweaters) and word count. Two coders achieved 100% agreement on all variables except tone (94.2%) and frame (96.3%). The search yielded 276 items published from 155 sources in 18 nations. The tone toward Gucci during this period was negative (69.9%). Items that were neutral (16.3%) or positive (13.8%) toward the brand were overwhelmingly related to items about other Gucci sweaters worn by celebrities or fashion reviews of other Gucci sweaters. The most frequent frame was apology/pulling the product/diversity initiatives by Gucci (35.5%). The tone was most frequently negative across all continents, including the Middle East (83.3% negative), Asia (81.8%), North America (76.6%), Australia/New Zealand (66.7%), and Europe (59.8%). Newspapers/magazines/newswires/broadcast news transcripts (72.4%) were more negative than blogs/web-based publications (63.6%). The most frequent frames used by newspapers/magazines/newswires/broadcast news transcripts were apology/pulling the product/diversity initiatives by Gucci (38.7%) and blackface/racism/racist (26.1%). Blogs/web-based publications most frequently used frames unrelated to the controversial garment, but about other Gucci sweaters (42.9%) and apology/pulling the product/diversity initiatives by Gucci (27.3%). Sources in Western nations (34.7%) and Eastern nations (47.1%) most frequently used the frame of apology/pulling the product/diversity initiatives by Gucci. Mean word count was higher for negative items (583.58) than positive items (404.76). Items framed as blackface/racism/racist or boycott/celebrity boycott had higher mean word count (668.97) than items framed as sweater/balaclava/jumper/fashion or apology/pulling the product/diversity initiatives by Gucci (498.22). The author concluded that during the year-long period, Gucci’s image was likely damaged by the release of the garment at the center of the controversy due to near-universally negative items published, but Gucci’s apology/pulling the product off the market/diversity initiatives by Gucci and items about other Gucci sweaters worn by celebrities or fashion reviews of other Gucci sweaters were the most common frames across multiple media platforms, which may have mitigated the damage to the brand.

Keywords: Blackface, branding, Gucci, media framing

Procedia PDF Downloads 123
24483 Optimal Number and Placement of Vertical Links in 3D Network-On-Chip

Authors: Nesrine Toubaline, Djamel Bennouar, Ali Mahdoum

Abstract:

3D technology can lead to a significant reduction in power and average hop-count in Networks on Chip (NoCs). It offers short and fast vertical links which copes with the long wire problem in 2D NoCs. This work proposes heuristic-based method to optimize number and placement of vertical links to achieve specified performance goals. Experiments show that significant improvement can be achieved by using a specific number of vertical interconnect.

Keywords: interconnect optimization, monolithic inter-tier vias, network on chip, system on chip, through silicon vias, three dimensional integration circuits

Procedia PDF Downloads 270
24482 The Effect of Air Filter Performance on Gas Turbine Operation

Authors: Iyad Al-Attar

Abstract:

Air filters are widely used in gas turbines applications to ensure that the large mass (500kg/s) of clean air reach the compressor. The continuous demand of high availability and reliability has highlighted the critical role of air filter performance in providing enhanced air quality. In addition to being challenged with different environments [tropical, coastal, hot], gas turbines confront wide array of atmospheric contaminants with various concentrations and particle size distributions that would lead to performance degradation and components deterioration. Therefore, the role of air filters is of a paramount importance since fouled compressor can reduce power output and availability of the gas turbine to over 70 % throughout operation. Consequently, accurate filter performance prediction is critical tool in their selection considering their role in minimizing the economic impact of outages. In fact, actual performance of Efficient Particulate Air [EPA] filters used in gas turbine tend to deviate from the performance predicted by laboratory results. This experimental work investigates the initial pressure drop and fractional efficiency curves of full-scale pleated V-shaped EPA filters used globally in gas turbine. The investigation involved examining the effect of different operational conditions such as flow rates [500 to 5000 m3/h] and design parameters such as pleat count [28, 30, 32 and 34 pleats per 100mm]. This experimental work has highlighted the underlying reasons behind the reduction in filter permeability due to the increase of flow rates and pleat density. The reasons, which led to surface area losses of filtration media, are due to one or combination of the following effects: pleat-crowding, deflection of the entire pleated panel, pleat distortion at the corner of the pleat and/or filtration medium compression. This paper also demonstrates that the effect of increasing the flow rate has more pronounced effect on filter performance compared to pleating density. This experimental work suggests that a valid comparison of the pleat densities should be based on the effective surface area, namely, the area that participates in the filtration process, and not the total surface area the pleat density provides. Throughout this study, optimal pleat count that satisfies both initial pressure drop and efficiency requirements may not have necessarily existed.

Keywords: filter efficiency, EPA Filters, pressure drop, permeability

Procedia PDF Downloads 217
24481 Regional Analysis of Freight Movement by Vehicle Classification

Authors: Katerina Koliou, Scott Parr, Evangelos Kaisar

Abstract:

The surface transportation of freight is particularly vulnerable to storm and hurricane disasters, while at the same time, it is the primary transportation mode for delivering medical supplies, fuel, water, and other essential goods. To better plan for commercial vehicles during an evacuation, it is necessary to understand how these vehicles travel during an evacuation and determine if this travel is different from the general public. The research investigation used Florida's statewide continuous-count station traffic volumes, where then compared between years, to identify locations where traffic was moving differently during the evacuation. The data was then used to identify days on which traffic was significantly different between years. While the literature on auto-based evacuations is extensive, the consideration of freight travel is lacking. To better plan for commercial vehicles during an evacuation, it is necessary to understand how these vehicles travel during an evacuation and determine if this travel is different from the general public. The goal of this research was to investigate the movement of vehicles by classification, with an emphasis on freight during two major evacuation events: hurricanes Irma (2017) and Michael (2018). The methodology of the research was divided into three phases: data collection and management, spatial analysis, and temporal comparisons. Data collection and management obtained continuous-co station data from the state of Florida for both 2017 and 2018 by vehicle classification. The data was then processed into a manageable format. The second phase used geographic information systems (GIS) to display where and when traffic varied across the state. The third and final phase was a quantitative investigation into which vehicle classifications were statistically different and on which dates statewide. This phase used a two-sample, two-tailed t-test to compare sensor volume by classification on similar days between years. Overall, increases in freight movement between years prevented a more precise paired analysis. This research sought to identify where and when different classes of vehicles were traveling leading up to hurricane landfall and post-storm reentry. Of the more significant findings, the research results showed that commercial-use vehicles may have underutilized rest areas during the evacuation, or perhaps these rest areas were closed. This may suggest that truckers are driving longer distances and possibly longer hours before hurricanes. Another significant finding of this research was that changes in traffic patterns for commercial-use vehicles occurred earlier and lasted longer than changes for personal-use vehicles. This finding suggests that commercial vehicles are perhaps evacuating in a fashion different from personal use vehicles. This paper may serve as the foundation for future research into commercial travel during evacuations and explore additional factors that may influence freight movements during evacuations.

Keywords: evacuation, freight, travel time, evacuation

Procedia PDF Downloads 41
24480 Design, Construction and Performance Evaluation of a HPGe Detector Shield

Authors: M. Sharifi, M. Mirzaii, F. Bolourinovin, H. Yousefnia, M. Akbari, K. Yousefi-Mojir

Abstract:

A multilayer passive shield composed of low-activity lead (Pb), copper (Cu), tin (Sn) and iron (Fe) was designed and manufactured for a coaxial HPGe detector placed at a surface laboratory for reducing background radiation and radiation dose to the personnel. The performance of the shield was evaluated and efficiency curves of the detector were plotted by using of the various standard sources in different distances. Monte Carlo simulations and a set of TLD chips were used for dose estimation in two distances of 20 and 40 cm. The results show that the shield reduced background spectrum and the personnel dose more than 95%.

Keywords: HPGe shield, background count, personnel dose, efficiency curve

Procedia PDF Downloads 427
24479 Toxicity of Solenstemma Argel (Hargal ) on Nubian Goats

Authors: Amna B. Medani, M. A. Elbadwi Samia, Hassan A. Khalid

Abstract:

In our study, nine Nubian goat kids were obtained, allotted into three groups, and healthily adapted in pens within the premises of the Veterinary Teaching Hospital, University of Khartoum to be given the oral doses of the dried herb shoots at daily doses of 1 and 5 gm/kg/day with drinking water, while the kids of the control group were left undosed. All goats were slaughtered,if not died, after 35 days. S. argel at the given doses caused signs of arched posture, ruffled hair, shivering and paralysis of limbs. On post mortem, lesions were seen to be hepatic fatty changes, renal necrosis, congested lungs and inflamed intestines. Serum chemistry investigations revealed significant increase (P< 0.05-0.01) in the activities of ALP(alkaline phosphates) and AST( aspartate-aminotransferase) in goats dosed with 5 gm /kg/ day. Also observed were significant increases in inorganic phosphorus and urea concentrations (P < 0.05-0.01) in both dosed goat groups. .Other investigations including the activity of GGT( gamma glutamyltransferase), creatinine, calcium, total protein and albumin illustrated no significant difference from that of the undosed controls. On haematological evaluation , the goat kids dosed with 5 gm/kg/dayshowed a decrease in haemoglobin concentration and red blood cells count of (P < 0.05-0.01).Both groups of dosed goats showed a higher packed cell volume values of (P < 0.05) when compared to the control goats .Mean corpuscular haemoglobin values were not different from those of the control kids. S. argel at the given doses caused signs of arched posture, ruffled hair, shivering and paralysis of limbs. On post mortem, lesions were seen to be hepatic fatty changes, renal necrosis, congested lungs and inflamed intestines. Serum chemistry investigations revealed significant increase (P < 0.05-0.01) in the activities of ALP(alkaline phosphates) and AST( aspartate-aminotransferase) in goats dosed with 5 gm /kg/ day. Also observed were significant increases in inorganic phosphorus and urea concentrations (P < 0.05-0.01) in both dosed goat groups. .Other investigations including the activity of GGT( gamma-glutamyltransferase), creatinine, calcium, total protein and albumin illustrated no significant difference from that of the undosed controls. calcium, total protein and albumin illustrated no significant difference from that of the undosed controls. On haematological evaluation , the goat kids dosed with 5 gm/kg/dayshowed a decrease in haemoglobin concentration and red blood cells count of (P < 0.05-0.01).Both groups of dosed goats showed a higher packed cell volume values of (P < 0.05) when compared to the control goats .Mean corpuscular haemoglobin values were not different from those of the control kids. Data obtained were then discussed to find S. argel irritable to intestines , toxic to the kidney and liver and a haematological mild toxin.Suggestions for future were forwarded.

Keywords: hargal, nubian goats, solenstemma argel, toxicity

Procedia PDF Downloads 294
24478 A Goal-Driven Crime Scripting Framework

Authors: Hashem Dehghanniri

Abstract:

Crime scripting is a simple and effective crime modeling technique that aims to improve understanding of security analysts about security and crime incidents. Low-quality scripts provide a wrong, incomplete, or sophisticated understanding of the crime commission process, which oppose the purpose of their application, e.g., identifying effective and cost-efficient situational crime prevention (SCP) measures. One important and overlooked factor in generating quality scripts is the crime scripting method. This study investigates the problems within the existing crime scripting practices and proposes a crime scripting approach that contributes to generating quality crime scripts. It was validated by experienced crime scripters. This framework helps analysts develop better crime scripts and contributes to their effective application, e.g., SCP measures identification or policy-making.

Keywords: attack modelling, crime commission process, crime script, situational crime prevention

Procedia PDF Downloads 104
24477 Algorithms used in Spatial Data Mining GIS

Authors: Vahid Bairami Rad

Abstract:

Extracting knowledge from spatial data like GIS data is important to reduce the data and extract information. Therefore, the development of new techniques and tools that support the human in transforming data into useful knowledge has been the focus of the relatively new and interdisciplinary research area ‘knowledge discovery in databases’. Thus, we introduce a set of database primitives or basic operations for spatial data mining which are sufficient to express most of the spatial data mining algorithms from the literature. This approach has several advantages. Similar to the relational standard language SQL, the use of standard primitives will speed-up the development of new data mining algorithms and will also make them more portable. We introduced a database-oriented framework for spatial data mining which is based on the concepts of neighborhood graphs and paths. A small set of basic operations on these graphs and paths were defined as database primitives for spatial data mining. Furthermore, techniques to efficiently support the database primitives by a commercial DBMS were presented.

Keywords: spatial data base, knowledge discovery database, data mining, spatial relationship, predictive data mining

Procedia PDF Downloads 430
24476 A Study on the Measurement of Spatial Mismatch and the Influencing Factors of “Job-Housing” in Affordable Housing from the Perspective of Commuting

Authors: Daijun Chen

Abstract:

Affordable housing is subsidized by the government to meet the housing demand of low and middle-income urban residents in the process of urbanization and to alleviate the housing inequality caused by market-based housing reforms. It is a recognized fact that the living conditions of the insured have been improved while constructing the subsidized housing. However, the choice of affordable housing is mostly in the suburbs, where the surrounding urban functions and infrastructure are incomplete, resulting in the spatial mismatch of "jobs-housing" in affordable housing. The main reason for this problem is that the residents of affordable housing are more sensitive to the spatial location of their residence, but their selectivity and controllability to the housing location are relatively weak, which leads to higher commuting costs. Their real cost of living has not been effectively reduced. In this regard, 92 subsidized housing communities in Nanjing, China, are selected as the research sample in this paper. The residents of the affordable housing and their commuting Spatio-temporal behavior characteristics are identified based on the LBS (location-based service) data. Based on the spatial mismatch theory, spatial mismatch indicators such as commuting distance and commuting time are established to measure the spatial mismatch degree of subsidized housing in different districts of Nanjing. Furthermore, the geographically weighted regression model is used to analyze the influencing factors of the spatial mismatch of affordable housing in terms of the provision of employment opportunities, traffic accessibility and supporting service facilities by using spatial, functional and other multi-source Spatio-temporal big data. The results show that the spatial mismatch of affordable housing in Nanjing generally presents a "concentric circle" pattern of decreasing from the central urban area to the periphery. The factors affecting the spatial mismatch of affordable housing in different spatial zones are different. The main reasons are the number of enterprises within 1 km of the affordable housing district and the shortest distance to the subway station. And the low spatial mismatch is due to the diversity of services and facilities. Based on this, a spatial optimization strategy for different levels of spatial mismatch in subsidized housing is proposed. And feasible suggestions for the later site selection of subsidized housing are also provided. It hopes to avoid or mitigate the impact of "spatial mismatch," promote the "spatial adaptation" of "jobs-housing," and truly improve the overall welfare level of affordable housing residents.

Keywords: affordable housing, spatial mismatch, commuting characteristics, spatial adaptation, welfare benefits

Procedia PDF Downloads 83
24475 Production and Evaluation of Physicochemical, Nutritional, Sensorial and Microbiological Properties of Mixed Fruit Juice Blend Prepared from Apple, Orange and Mosambi

Authors: Himalaya Patir, Bitupon Baruah, Sanjay Gayary, Subhajit Ray

Abstract:

In recent age significant importance is given for the development of nutritious and health beneficial foods. Fruit juices collected from different fruits when blended that improves not only the physicochemical and nutritional properties but also enhance the sensorial or organoleptic properties. The study was carried out to determine the physico-chemical, nutritional, microbiological analysis and sensory evaluation of mixed fruit juice blend. Juice of orange (Citrus sinensis), apple (Malus domestica), mosambi (Citrus limetta) were blended in the ratio of sample-I (30% apple:30% orange:40% mosambi), sample-II ( 40% apple :30% orange :30% mosambi), sample-III (30% apple :40% orange :30% mosambi) , sample-IV (50% apple :30% orange :20% mosambi), sample-V (30% apple:20% orange:50% mosambi), sample-VI (20% apple :50% orange :30% mosambi) to evaluate all quality characteristics. Their colour characteristics in terms of hue angle, chroma and colour difference (∆E) were evaluated. The physico-chemical parameters analysis carried out were total soluble solids (TSS), total titratable acidity (TTA), pH, acidity (FA), volatile acidity (VA), pH, and vitamin C. There were significant differences (p˂0.05) in the TSS of the samples. However, sample-V (30% apple: 20% orange: 50% mosambi) provides the highest TSS of 9.02gm and significantly differed from other samples (p˂0.05). Sample-IV (50% apple: 30% orange: 20% mosambi) was shown the highest titratable acidity (.59%) in comparison to other samples. The highest value of pH was found as 5.01 for sample-IV (50% apple: 30% orange: 20% mosambi). Sample-VI (20% apple: 50% orange :30% mosambi) blend has the highest hue angle, chroma and colour changes of 72.14,25.29 and 54.48 and vitamin C, i.e. Ascorbic acid (.33g/l) content compared to other samples. The nutritional compositions study showed that, sample- VI (20% apple: 50% orange: 30% mosambi) has the significantly higher carbohydrate (51.67%), protein (.78%) and ash (1.24%) than other samples, while sample-V (30% apple: 20% orange: 50% mosambi) has higher dietary fibre (12.84%) and fat (2.82%) content. Microbiological analysis of all samples in terms of total plate count (TPC) ranges from 44-60 in 101 dilution and 4-5 in 107 dilutions and was found satisfactory. Moreover, other pathogenic bacterial count was found nil. The general acceptability of the mixed fruit juice blend samples were moderately liked by the panellists, and sensorial quality studies showed that sample-V (30% apple: 20% orange: 50% mosambi) contains highest overall acceptability of 8.37 over other samples and can be considered good for consumption.

Keywords: microbiological, nutritional, physico-chemical, sensory properties

Procedia PDF Downloads 148
24474 Data Stream Association Rule Mining with Cloud Computing

Authors: B. Suraj Aravind, M. H. M. Krishna Prasad

Abstract:

There exist emerging applications of data streams that require association rule mining, such as network traffic monitoring, web click streams analysis, sensor data, data from satellites etc. Data streams typically arrive continuously in high speed with huge amount and changing data distribution. This raises new issues that need to be considered when developing association rule mining techniques for stream data. This paper proposes to introduce an improved data stream association rule mining algorithm by eliminating the limitation of resources. For this, the concept of cloud computing is used. Inclusion of this may lead to additional unknown problems which needs further research.

Keywords: data stream, association rule mining, cloud computing, frequent itemsets

Procedia PDF Downloads 474
24473 Factors Contributing to Building Construction Project’s Cost Overrun in Jordan

Authors: Ghaleb Y. Abbasi, Sufyan Al-Mrayat

Abstract:

This study examined the contribution of thirty-six factors to building construction project’s cost overrun in Jordan. A questionnaire was distributed to a random sample of 350 stakeholders comprised of owners, consultants, and contractors, of which 285 responded. SPSS analysis was conducted to identify the top five causes of cost overrun, which were a large number of variation orders, inadequate quantities provided in the contract, misunderstanding of the project plan, incomplete bid documents, and choosing the lowest price in the contract bidding. There was an agreement among the study participants in ranking the factors contributing to cost overrun, which indicated that these factors were very commonly encountered in most construction projects in Jordan. Thus, it is crucial to enhance the collaboration among the different project stakeholders to understand the project’s objectives and set a realistic plan that takes into consideration all the factors that might influence the project cost, which might eventually prevent cost overrun.

Keywords: cost, overrun, building construction projects, Jordan

Procedia PDF Downloads 73
24472 Intelligent Control of Bioprocesses: A Software Application

Authors: Mihai Caramihai, Dan Vasilescu

Abstract:

The main research objective of the experimental bioprocess analyzed in this paper was to obtain large biomass quantities. The bioprocess is performed in 100 L Bioengineering bioreactor with 42 L cultivation medium made of peptone, meat extract and sodium chloride. The reactor was equipped with pH, temperature, dissolved oxygen, and agitation controllers. The operating parameters were 37 oC, 1.2 atm, 250 rpm and air flow rate of 15 L/min. The main objective of this paper is to present a case study to demonstrate that intelligent control, describing the complexity of the biological process in a qualitative and subjective manner as perceived by human operator, is an efficient control strategy for this kind of bioprocesses. In order to simulate the bioprocess evolution, an intelligent control structure, based on fuzzy logic has been designed. The specific objective is to present a fuzzy control approach, based on human expert’ rules vs. a modeling approach of the cells growth based on bioprocess experimental data. The kinetic modeling may represent only a small number of bioprocesses for overall biosystem behavior while fuzzy control system (FCS) can manipulate incomplete and uncertain information about the process assuring high control performance and provides an alternative solution to non-linear control as it is closer to the real world. Due to the high degree of non-linearity and time variance of bioprocesses, the need of control mechanism arises. BIOSIM, an original developed software package, implements such a control structure. The simulation study has showed that the fuzzy technique is quite appropriate for this non-linear, time-varying system vs. the classical control method based on a priori model.

Keywords: intelligent, control, fuzzy model, bioprocess optimization

Procedia PDF Downloads 293