Autism Spectrum Disorder Detection in Children using the Efficacy of Machine Learning Approaches

Tariq Rafiq,Zafar Iqbal,Tahreem Saeed,Yawar Abbas Abid,Muneeb Tariq,Urooj Majeed,Akasha International Journal of Computer ScienceNetwork S 2023 International journal of computer science and netw Vol.23 No.4

For the future prosperity of any society, the sound growth of children is essential. Autism Spectrum Disorder (ASD) is a neurobehavioral disorder which has an impact on social interaction of autistic child and has an undesirable effect on his learning, speaking, and responding skills. These children have over or under sensitivity issues of touching, smelling, and hearing. Its symptoms usually appear in the child of 4- to 11-year-old but parents did not pay attention to it and could not detect it at early stages. The process to diagnose in recent time is clinical sessions that are very time consuming and expensive. To complement the conventional method, machine learning techniques are being used. In this way, it improves the required time and precision for diagnosis. We have applied TFLite model on image based dataset to predict the autism based on facial features of child. Afterwards, various machine learning techniques were trained that includes Logistic Regression, KNN, Gaussian Naïve Bayes, Random Forest and Multi-Layer Perceptron using Autism Spectrum Quotient (AQ) dataset to improve the accuracy of the ASD detection. On image based dataset, TFLite model shows 80% accuracy and based on AQ dataset, we have achieved 100% accuracy from Logistic Regression and MLP models.

Areca Nut Chewing and the Risk of Re-hospitalization and Mortality Among Patients With Acute Coronary Syndrome in Pakistan

Muhammad Tariq Karim,Sumera Inam,Tariq Ashraf,Nadia Shah,Syed Omair Adil,Kashif Shafique 대한예방의학회 2018 Journal of Preventive Medicine and Public Health Vol.51 No.2

Objectives: Areca nut is widely consumed in many parts of the world, especially in South and Southeast Asia, where cardiovascular disease (CVD) is also a huge burden. Among the forms of CVD, acute coronary syndrome (ACS) is a major cause of mortality and morbidity. Research has shown areca nut chewing to be associated with diabetes, hypertension, oropharyngeal and esophageal cancers, and CVD, but little is known about mortality and re-hospitalization secondary to ACS among areca nut users and non-users. Methods: A prospective cohort was studied to quantify the effect of areca nut chewing on patients with newly diagnosed ACS by categorizing the study population into exposed and non-exposed groups according to baseline chewing status. Cox proportional hazards models were used to examine the associations of areca nut chewing with the risk of re-hospitalization and 30-day mortality secondary to ACS. Results: Of the 384 ACS patients, 49.5% (n=190) were areca users. During 1-month of follow-up, 20.3% (n=78) deaths and 25.1% (n=96) re-hospitalizations occurred. A higher risk of re-hospitalization was found (adjusted hazard ratio [aHR], 2.05; 95% confidence interval [CI], 1.29 to 3.27; p=0.002) in areca users than in non-users. Moreover, patients with severe disease were at a significantly higher risk of 30-day mortality (aHR, 2.77; 95% CI, 1.67 to 4.59; p<0.001) and re-hospitalization (aHR, 2.72; 95% CI, 1.73 to 4.26; p<0.001). Conclusions: The 30-day re-hospitalization rate among ACS patients was found to be significantly higher in areca users and individuals with severe disease. These findings suggest that screening for a history of areca nut chewing may help to identify patients at a high risk for re-hospitalization due to secondary events.

Biosorption of Cu(II) from aqueous solution onto immobilized Ficus religiosa branch powder in a fixed bed column: Breakthrough curves and mathematical modeling

Madiha Tariq,Umar Farooq,Makshoof Athar,Muhammad Salman,Muqaddas Tariq 한국화학공학회 2019 Korean Journal of Chemical Engineering Vol.36 No.1

We investigated the adsorption potential of powdered branches from Ficus religiosa, an abundantly available plant, for the removal of Cu(II) from aqueous solution via column studies. Biomass was used as silica immobilized form and characterized using available techniques, including Fourier transformed infrared spectroscopy (FTIR) and scanning electron microscope (SEM). Breakthrough curve approach was used to explain removal capacity of biomass in a continuous flow mode, using different operating parameters like bed height (5-30 cm), inlet metal concentration (100-300mg/L) and pH (3-5) of the solution, at a fixed flow rate of 2mL/min. Biosorption of Cu(II) favored with increased service time (breakthrough and exhaust time) of the column with an increase in pH of inlet solution. Maximum biosorption capacity (17.5mg/g) for Cu(II) was achieved at 5 cm bed height, pH 5 and 300 mg/L influent Cu(II) concentration. Findings suggested that Ficus religiosa branch powder takes less service time and thus triggers fast removal of metal ions. Bed depth service time (BDST), Thomas and Yoon-Nelson models were effectively applied to the breakthrough data. The study indicated that the immobilized powdered branches could be used for the effective removal of Cu(II) ions in a continuous flow mode.

Areca Nut Chewing and the Risk of Re-hospitalization and Mortality Among Patients With Acute Coronary Syndrome in Pakistan

Karim, Muhammad Tariq,Inam, Sumera,Ashraf, Tariq,Shah, Nadia,Adil, Syed Omair,Shafique, Kashif The Korean Society for Preventive Medicine 2018 Journal of Preventive Medicine and Public Health Vol.51 No.2

Objectives: Areca nut is widely consumed in many parts of the world, especially in South and Southeast Asia, where cardiovascular disease (CVD) is also a huge burden. Among the forms of CVD, acute coronary syndrome (ACS) is a major cause of mortality and morbidity. Research has shown areca nut chewing to be associated with diabetes, hypertension, oropharyngeal and esophageal cancers, and CVD, but little is known about mortality and re-hospitalization secondary to ACS among areca nut users and non-users. Methods: A prospective cohort was studied to quantify the effect of areca nut chewing on patients with newly diagnosed ACS by categorizing the study population into exposed and non-exposed groups according to baseline chewing status. Cox proportional hazards models were used to examine the associations of areca nut chewing with the risk of re-hospitalization and 30-day mortality secondary to ACS. Results: Of the 384 ACS patients, 49.5% (n=190) were areca users. During 1-month of follow-up, 20.3% (n=78) deaths and 25.1% (n=96) re-hospitalizations occurred. A higher risk of re-hospitalization was found (adjusted hazard ratio [aHR], 2.05; 95% confidence interval [CI], 1.29 to 3.27; p=0.002) in areca users than in non-users. Moreover, patients with severe disease were at a significantly higher risk of 30-day mortality (aHR, 2.77; 95% CI, 1.67 to 4.59; p<0.001) and re-hospitalization (aHR, 2.72; 95% CI, 1.73 to 4.26; p<0.001). Conclusions: The 30-day re-hospitalization rate among ACS patients was found to be significantly higher in areca users and individuals with severe disease. These findings suggest that screening for a history of areca nut chewing may help to identify patients at a high risk for re-hospitalization due to secondary events.

The Influence of Transformational Leadership on Employees’ Innovation in Universities of UAE: Mediating Effect of Technological Diversity

Tariq Humaid ALMASKARI,Effendi MOHAMAD,Siti Norbaya YAHAYA,Muhammad Farhan JALIL 한국유통과학회 2021 The Journal of Asian Finance, Economics and Busine Vol.8 No.7

This study seeks to empirically investigate the impact of transformational leadership on employees’ innovation with the mediating effect of technological diversity. Employees have evolved into leaders in organizing work within institutions over the last few decades. This shift presents new demands for leaders, who are forced to reinvent individual workers while also improving workplace innovation. This research proposes a conceptual model for considering transformational leadership and the impact of technological diversity on innovation. Structured questionnaire is used in the study and the analysis of the data from 633 employees of universities in the United Arab Emirates uses stratified sampling technique and hypotheses verified through Structural Equations Modelling (AMOS-21). According to the results, transformational leadership has a big effect on employees’ innovation. Furthermore, in the relationship between transformational leadership and workforce innovation, technological diversity has a partial mediation impact. This research adds to the growing body of knowledge about how transformational leadership influences employees’ innovation and how it affects employees’ success, especially in the context of UAE-based universities. Overall, this research contributes to the previous studies wherein transformational leadership plays a critical role in influencing the innovative performance of employees and that, in turn, will promote diversification of technology in the organization.

A Survey on Trajectory Data Warehouse

Tariq Alsahf,Mousa Almotairi,Ramez Elmasri 대한공간정보학회 2020 Spatial Information Research Vol.28 No.1

Advanced technologies in location acquisition allow us to track the movement of moving objects (people, planes, vehicles, animals, ships, ...) in geographical space. These technologies generate a vast amount of trajectory data (TD). Several applications in different fields can utilize such TD, for example, traffic management control, social behavior analysis, wildlife migrations and movements, ship trajectories, shoppers behavior in a mall, facial nerve trajectory, location-based services and many others. Trajectory data can be mainly handled either with Moving Object Databases (MOD) or Trajectory Data Warehouse (TDW). In this paper, we aim to review existing studies on storing, managing, and analyzing TD using data warehouse technologies. We propose a framework that aims to provide the requirements for building the TDW. Furthermore, we discuss different applications using the TDW and how these applications utilize the TDW. We address some issues with existing TDWs and discuss future work in this field.

Role of CD10 Immunohistochemical Expression in Predicting Aggressive Behavior of Phylloides Tumors

Tariq, Muhammad Usman,Haroon, Saroona,Kayani, Naila Asian Pacific Journal of Cancer Prevention 2015 Asian Pacific journal of cancer prevention Vol.16 No.8

Background: Phylloides tumors are rare breast neoplasms with a variable clinical course depending on the tumor category. Along with histologic features, the role of immunohistochemical staining has been studied in predicting their behavior. Objectives: Our aim was to evaluate the role of CD 10 immunohistochemical staining in predicting survival, recurrence and metastasis in phylloides tumor. We also evaluated correlations of other clinicopathological features with overall and disease-free survival. Materials and Methods: CD10 expression was studied in 82 phylloides tumors divided into recurrent/metastatic and non-recurrent/non-metastatic cohorts. The Chi-square test was applied to determine the significance of differences in CD10 expression between outcome cohorts. Uni and multivariate survival analyses were also performed using log-rank test and Cox regression hazard models. Results: All 3 metastatic cases, 5 out of 6 (83.3%) recurrent cases and 37out of 73 (50.7%) non-recurrent and non-metastatic cases expressed significant (2+ or 3+) staining for CD10. This expression significantly varied between outcome cohorts (p<0.03). Tumor category and histological features including mitotic count and necrosis correlated significantly with recurrence and metastasis. A significant decrease in overall and disease free survival was seen with CD10 positivity, malignant category, increased mitoses and necrosis. Neither CD10 expression nor any other clinicopathologic feature proved to be an independent prognostic indicator in multivariate analysis. Conclusions: CD10 immunohistochemical staining can be used as a predictive tool for phylloides tumor but this expression should be interpreted in conjunction with tumor category.

Kashmir: Self-Determination versus State Terrorism

( Tariq Osman Hyder ) 한국국방연구원 2002 The Korean Journal of Defense Analysis Vol.14 No.1

The unprecedented and condemnable terrorist strikes of September 11 have united the world community to counter this menace. In combating terrorism, the causes of terrorism must also be addressed. The international community has already found the political will, expressed through the UN Security Council, to condemn and actively intervene in grave breaches of human rights, in Rwanda, Bosnia and Kosovo. International tribunals were set up. No state and no state official can now plead sovereign immunity for grave human rights violations within any country, let alone within an occupied territory. Therefore the world community can no longer close its eyes to grave violations, however important and powerful the offending state. The campaign against terrorism must not be used to perpetuate oppression and human rights abuses against oppressed and occupied peoples who retain the right to armed struggle to further their right of self-determination in the face of such oppression. Occupied Kashmir, where 13 million Kashmiris have waited for 53 years to gain their UN Security Council-sanctioned right of self-determination, and have lost 80,000 precious lives since 1990, and where self determination is pitted against state terrorism, constitutes the most important global test case for the sincerity of the world community to actively and effectively intervene to end this humanitarian crisis, which constitutes a threat to international peace and security, and to bring about a dialogue between India and Pakistan leading to a peaceful resolution of this dispute on the basis of the aspirations of the Kashmiri people and the United Nations resolutions.

Clean Dhaka Master Plan: An Experience of ODA in Municipal Solid Waste Management

( Tariq Bin Yousuf ) 한국폐기물자원순환학회 2011 ISWA Vol.2011 No.0

The Government of Japan has supported for improvement of Solid Waste Management in Dhaka City in a comprehensive way. JICA started technical co-operation on SWM with Dhaka City Corporation (DCC) in 2000. During the period (November2003 to March 2005), a development study was conducted. Clean Dhaka Master Plan (2005-2010) was formulated that covers all aspects of SWM, including public awareness, primary collection, secondary collection and transportation, final disposal as well as administration and financial management. For the development of capacity building of DCC, JICA has extended technical cooperation support, while for physical infrastructure development; Government of Japan has rendered support on grant basis. Institutionalization of community based waste collection services, introduction of 100 modern waste collection vehicles including 35 compactors, two sanitary landfills, setting up of waste management department and financial management system are the major outputs of the project. The implementation of the master plan started from 2005 and in the year 2010 an evaluation was done by JICA appointed experts. In the mid-period of the master plan, a revised master plan is also prepared based on the practical experiences and the gaps analysis. Eight good practices obtained through implementation of the project. These good practices were selected through consideration of four criteria such as approach, challenges, sustainability and replicability. This paper will share the challenges as well as achievements of the municipal solid waste master plan implementation in Dhaka City.

Deep Learning-based Colorectal Cancer Detection in Endoscopic Images

Tariq Rahim,Arslan Musaddiq,Dong Seong Kim 한국통신학회 2021 한국통신학회 학술대회논문집 Vol.2021 No.6

Colorectal cancer (CRC) is the most prevalent cancer found in the small bowel of the human gastrointestinal (GI) tract. Polyps are antecedents to CRC and are detected in approximately half of the people at age 50 within the GI. In this paper, an improved version of You Only Live Once (YOLO) is presented for the detection of polyp within the endoscopic images. We have improved the YOLOv3-tiny model by adding more convolutional layers to extract enriched and deeper features. For fair benchmarking, the efficacy of the proposed model is evaluated against the default version of YOLOv3-tiny in terms of recall, precision, F1-score, and F2-score.