Miracle-dz/UniFAR-FTUs huggingface dataset:
ENVIRONMENT FRIENDLY MODEL OF BASEMENT PARKING SPACE CONTROL (Study Shopping Center Building area South of Jakarta To Environmental Sustainability)

Limitations of land to make the parking area that unites with building. Parking area cause emissions motor vehicle which could affect human health that are directly involved in the parking area. During this control is technical and they did not put in the human behavior. The research is aimed at creating a model control basement parking space environment-friendly, by combining technical aspects to include the role human behavior. This research uses quasi experimental with mixed approach methods (quantitative and qualitative research). Shopping center building population is the region South of Jakarta had the facility, which amount parking area 11 fruit. Samples taken with purposive sampling 2 building shopping centers. From 2 building was there are 150 officers parking lot, who are all made samples or (samples saturated). Data Collection in a manner: 1. Measurements concentration pollutants in the air space parking area; 2. A medical check-up parking officer basement; 3. Filling questionnaire on environment-friendly; 4. Making model control basement parking space environment-friendly. Data Analysis with descriptive and structural equation modeling (SEM). Results of the study showed that: 1) Based on the result analysis of pollutants concentration in the air space parking area is obtained all parameters to fulfill the requirement to The threshold in the regulation of the Minister of Manpower and Transmigration and Conditions in the regulation of the Minister of Health, except the dust total that exceeded maximum concentration in the regulation of the Minister of Health Care; 2) Based on the result analysis of health officials in parking area also Trigger the Syndrome are with the parameter obtained by 30% complain and 70 percent normal lung function; there is trouble gained 17 percent and 83 percent normal; and CO blood provided by 46 percent are female and 54 percent normal. 3) Based on the determining factor on environment-friendly environment-friendly found that the behavior is determined by the attention to behave, while attention is influenced by norma subjective, attitude, and the perception. 4) Based on the structural model research, I make a model for the parking area environmentally-friendly consists of 3 routes to be on environment-friendly, namely a. Norma subjective affected attention and attention influence on ; b. The attitude affected attention and attention influence on; c. Perception influence the, the attitude affected attention and attention influence behavior. From 3 path is that the most powerful its significance is the role norms subjective to levers to influence attention and made on environment-friendly. Keyword : Control parking area and environment friendly shopping center, environmental sustainability.
Running title: Canopy foliage water 18 O enrichment

Leaf water O enrichment is an important factor controlling the H2 O, COO and OO exchanges between the biosphere and the atmosphere. At present, there is limited capacity to explain the enrichment mechanisms in field conditions. In this study, three models of varying complexity were used to simulate the leaf water O enrichment at the canopy scale. Comparisons were made among the models and with high-frequency isotopic measurements of ecosystem water pools in wheat and corn. The results show that the steady state assumption was a better approximation for ecosystems with lower canopy resistance, that it is important to consider the effect of leaf water turnover in modeling the enrichment and not necessary to deal with time changes in leaf water content, and that the leaf-scale Péclet effect was incompatible with the big-leaf modeling framework for canopy-air interactions. After turbulent diffusion has been accounted for in an apparent kinetic factor parameterization, the mean O composition of the canopy foliage water was a well-behaved property predictable according to the principles established by leaf-scale studies, despite substantial variations in the leaf water enrichment with leaf and canopy positions. In the Appendices we provided a discussion on the observed variability of leaf water O composition with leaf and canopy positions and on the procedure for correcting isotopic measurements for organic contamination.
International Journal of Advance Research in Computer Science and Management Studies

A major problem of today is the record linkage. The record linkage problem occurs when there are multiple representations of the same real-world entity. In record linkage problem, record matching is done because of that we can find out duplicate records from the system, and the duplication detection is the process of finding duplicate records which having different representations. Data integration is the important step for data duplication detection. To eliminate duplicate records from the database data cleaning is needed which the important phase in data is warehousing. It improves the data quality to provide better decisions support system. This paper provides the thorough survey on data duplication detection and elimination using several methods which reduced the record linkage problem, record comparison and elimination time in single and multiple the databases. Section V shows the implementation of securing the database in encrypted format.
International Journal of Advance Research in Computer Science and Management Studies

Transport Control Protocol (TCP) incast congestion happens when number of senders work in parallel with the same receiver where the high bandwidth and low latency network problem occurs. For many data center network application such as many to one, heavy traffic is present on such server. Incast congestion degrades the performance as the packets are lost at server side due to buffer overflow and hence the response time will be more. To improve the performance, main idea is to design an incast congestion Control for TCP (ICTCP) scheme on the receiver side by implementing grid computing for process allocation as well as sub server scheduling to achieve flow shop scheduling process (FSSP). Mobile agent is used to handle failures thus the specific part of failed file will be transmitted rather than whole part to be sent. Hashing technique is used for message integrity and in order to improve the quality of service fault tolerance system is used. To avoid the packet loss the ICTCP algorithm has been implemented.
International Journal of Advance Research in Computer Science and Management Studies

: Fashion coordination is one of the self-expressions which have been always in demands. Searching for perfect attire, is a time consuming task as well as many factors need to be kept in mind. In this paper we are introducing a “Tailoring Measurement and Virtual Try-on (TMVT)”. This is an innovative Virtual shopping infrastructure, enabling customers to visualize themselves wearing garments present in traditional stores, as well as online (in internet shops). This is done by mining of the user image, alignment of models and skin colour detection of image (clicked from a fix distance). The major reimbursement of the TMVT include, saving time of the customer/user by avoiding don and doffing at the time of shopping, where both the virtual and physical worlds are combined. This application will be able to fill a big gap between customer and seller by showing clothes of varying size. Finally the model is superimposed on the user in real time with some manual adjustment.
International Journal of Advance Research in Computer Science and Management Studies

Social media is increased in presence and importance in society. A social network service consists of a representation of each user. Social networking sites allow users to communicate with people in the network by sharing thoughts, pictures, status, posts, activities and products. It has become one of the biggest forums to express ones opinion. The majority of earlier work in Rating Prediction and Recommendation of products mainly takes the star ratings of users on products. However, most reviews are written in a free-text format which is difficult for computer systems to understand, analyze and aggregate. The proposed system is able to collect useful information from the social website and efficiently perform sentiment analysis of the reviews on product. The work focuses on identifying the sentiment information from freeform text reviews and using that information to rank the product. The sentiment of the user reviews is predicted using a well trained effective Naive Byes classifier. The result shows that using textual information given by the users is classified as positive negative and neutrals.
Comparison and Analysis of Several Common Water Extraction Methods Based on TM Image

With the rapid development of remote sensing technology,using remote sensing data for water resources monitoring,investigation and analysis has become an inevitable trend.The fast and accurate extraction of water information from remote sensing imagery is an important method and means of the investigation and monitoring of water resources.Currently,there are many ways to extract water information from remote sensing imagery.This paper selected three common water extraction methods,that is the single-band threshold method,the multi-band spectral relationship method based on threshold and the normalized difference water index method based on threshold,then selected the typical plain area,Wuhan city,and the typical mountainous area,Yichang country,as experimental area,and then selected the Landsat5 TM image as research data to analyze and compare the strength and the weaknesses of three methods in the plain and mountainous area respectively by experiment.
Systematic Literature Review: How Teachers Instill Critical Thinking Character During the Pandemic

Critical thinking is an important ability for students in the 21st century. Learners who are less able to think critically will have difficulty when faced with a problem. The purpose of this study is to reveal; 1. What are the learning methods for instilling critical thinking characters in Indonesia during the pandemic, 2.What critical thinking indicators are developed in the learning model, 3.What are the results of the methods used in instilling critical thinking skills. The review method used in this paper is a systematic literature review. The search for articles on the Google scholar uses the help of the Publish or perish application because using the benefit of an application will make it easier to find articles. The selection and screening stages were carried out by analysing the article title, keywords, abstract, background of the problem, author's question, and results and discussion. The results of this study showed that (1) Teachers use varied learning methods during the pandemic, such as e-learning, online class, and blended learning. (2) The critical thinking indicators developed are formulating problems, analysing, concluding, evaluating, building basic skills, providing a further explanation, and managing strategies. (3) The learning methods used during the pandemic can instil students' critical thinking characteristics based on several indicators. However, several learning methods still need help instilling critical thinking skills. The implications of this study are: First, teachers must be skilled in using learning methods with a suitable learning model to instil critical thinking skills in students. This study reveals how teachers instil students' critical thinking skills during the pandemic.
International Journal of Advance Research in Computer Science and Management Studies

: Image re-ranking, as an effective way to improve the results of online image search, has been adopted by traditional search engines. Given a query, a pool of images are first fetch by the search engine based on textual information. By asking the user to select a query image from the data, the remaining images are re-ranked based on their visual similarities with the selected image. A major problem is that the similarities of visual features do not correlate with images semantic meanings which shows users search intention. On the other hand, learning a universal visual semantic space to characterize images from the web is diﬃcult. In this paper, we propose image re-ranking framework, which automatically oﬄine learns semantic spaces for diﬀerent query’s. The visual features of images are shows into their related semantic spaces to get semantic signatures. At the online part, images are re-ranked by comparing their semantic signatures obtained from the semantic space specified by the query. The new approach significantly improves both the accuracy and eﬃciency of image re-ranking. Experimental results show that 20 - 30 percentage improvement has been achieved on re-ranking precisions compared with the traditional methods.
International Journal of Advance Research in Computer Science and Management Studies

: Face Recognition System (FRS) is a computer application, which can detect, verify and recognize the faces. This paper gives the literature survey of the related work. The area is still an active area of research and new algorithms are being published with increased accuracy and reduced recognition time. All FRS algorithms have the same objective of achieving high accuracy in face recognition and use different methods for this purpose. A FRS should be good enough to recognize from face images which have different lighting conditions, poses and expressions. Since face recognition system plays a vital role in security and authentication it is important to use a system, which can provide high accuracy. In this paper an overview of different FRS algorithms is presented. Also, this paper presents a new approach based on Particle Swarm Optimization (PSO) method and Eigen Filtration. Eigen filtration is used for extracting feature points (white points) from canny edge detected image. PSO will iteratively search for best candidate solution among the population in the search space. In this approach uses 200 CMU face images from UCI machine Learning Laboratory.
UvA-DARE (Digital Academic Repository) SimPhospho: a software tool enabling confident phosphosite assignment

Motivation: Mass spectrometry combined with enrichment strategies for phosphorylated peptides has been successfully employed for two decades to identify sites of phosphorylation. However, unambiguous phosphosite assignment is considered challenging. Given that site-speciﬁc phosphorylation events function as different molecular switches, validation of phosphorylation sites is of utmost importance. In our earlier study we developed a method based on simulated phospho-peptide spectral libraries, which enables highly sensitive and accurate phosphosite assignments. To promote more widespread use of this method, we here introduce a software implementation with improved usability and performance. Results: We present SimPhospho, a fast and user-friendly tool for accurate simulation of phospho-peptide tandem mass spectra. Simulated phosphopeptide spectral libraries are used to validate and supplement database search results, with a goal to improve reliable phosphoproteome identi-ﬁcation and reporting. The presented program can be easily used together with the Trans-Proteomic Pipeline and integrated in a phosphoproteomics data analysis workﬂow. Availability and implementation: SimPhospho is open source and it is available for Windows, Linux and Mac operating systems.
Effectiveness of emergency department-based and initiated youth suicide prevention interventions: A systematic review

Objective This systematic review examined the effectiveness of Emergency Department-based and initiated youth suicide prevention interventions for suicide attempts, suicidal ideation, hospitalization, family system functioning, and other mental health symptoms. Methods We searched five databases for randomized controlled trial (RCT) studies that examined Emergency Department-based and initiated suicide prevention interventions among youth aged 10 to 18 years old between May 2020 to June 2022. Using Cohen’s d and 95% confidence interval as our standardised metrics, we followed the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) and Synthesis Without Meta-Analysis in Systematic Reviews (SWiM) guidelines when synthesizing, interpreting, and reporting the findings of this review. Results Five studies were included in this review. Findings were first synthesized according to the targeted population of the study intervention and this review’s outcomes. Two interventions were effective for decreasing depressive symptoms, hospitalization recidivism, and/or increasing family empowerment. There were no interventions that reduced subsequent suicide attempts. A meta-analysis was not conducted due to the heterogeneity of the data. Conclusion A need exists to develop and evaluate Emergency Department-based and initiated youth suicide prevention interventions that can be successfully and sustainably implemented in practice. Future research should focus on evaluating the components of interventions that effectively mitigate suicide risk among high-risk youth.
Combination of Spaceborne, Airborne and Surface Gravity in Support of Arctic Ocean Sea-Ice and MDT Mapping

Improved knowledge of the gravity field in the Arctic is a key to the utilization of satellite altimetry to determine sea-ice thickness and mean dynamic topography (MDT). In the paper we outline the construction of a new gravity field of the Arctic Ocean region, combining new GRACE and ICESat observations with earlier compilations of airborne, surface, and submarine gravity data from the Arctic Gravity Project. We compare the corresponding geoid model to a mean sea surface (MSS) model derived from ICESat lowest-level filtered laser altimetry and retracked radar altimetry, to allow for a consistent estimate of the Arctic Ocean MDT. Results are compared to oceanographic models, and show an overall absolute consistency is achieved at the decimeter-level. Arctic Ocean sea ice freeboard heights (and thus ice thickness) are an integral part of these investigations, and ICESatderived freeboard heights show a good correlation to multi-year ice distribution as determined from Quikscat. The investigations represent the core of the ongoing ESA project "ArcGICE". One of its major objectives is to provide a practical algorithm for the estimation of sea surface heights including the associated errors. These parameters can further be used for example as a reference for Cryosat-2 measurements of sea ice freeboard. The ArcGICE study includes detailed error estimates and covariance studies, and it is clear that the inclusion of GOCE data will significantly enhance ice thickness and MDT mapping from e.g. CryoSat-2.
ATLAS document

Constraints on the Higgs boson self-coupling are set by combining the single Higgs boson analyses targeting the γγ, Z Z∗, WW∗, τ+τ− and bb̄ decay channels with the double Higgs boson analyses in the bb̄bb̄, bb̄τ+τ− and bb̄γγ decay channels, using data collected at √ s = 13 TeV with the ATLAS detector at the LHC. The data used in these analyses correspond to an integrated luminosity of up to 79.8 fb−1 for single Higgs boson analyses and up to 36.1 fb−1 for the double Higgs boson analyses. With the assumption that new physics affects only the Higgs boson self-coupling (λHHH ), values outside the interval −2.3 < λHHH/λ HHH < 10.3 are excluded at 95% confidence level. Results with less stringent assumptions are also provided, introducing additional coupling modifiers for the Higgs boson interactions with the other Standard Model particles.
APPLICATION OF 3-D VELOCITY MODELS AND RAY TRACING IN DOUBLE DIFFERENCE EARTHQUAKE LOCATION ALGORITHMS: APPLICATION TO THE MYGDONIA BASIN (NORTHERN GREECE)

In the past years there has been a growing demand for precise earthquake locations for seismotectonic and seismic hazard studies. Recently this has become possible because of the development of sophisticated location algorithms, as well as hardware resources. This is expected to lead to a better insight of seismicity in the near future. A well-known technique, which has been recently used for relocating earthquake data sets is the double difference algorithm. In its original implementation it makes use of a one-dimensional ray tracing routine to calculate seismic wave travel times. We have modified the implementation of the algorithm by incorporating a three-dimensional velocity model and ray tracing in order to relocate a set of earthquakes in the area of the Mygdonia Basin (Northern Greece). This area is covered by a permanent regional network and occasionally by temporary local networks. The velocity structure is very well known, as the Mygdonia Basin has been used as an international test site for seismological studies since 1993, which makes it an appropriate location for evaluating earthquake location algorithms, with the quality of the results depending only on the quality of the data and the algorithm itself. The new earthquake locations reveal details of the area's seismotectonic structure, which are blurred, if not misleading, when resolved by standard (routine) location algorithms.
LOW FREQUENCY OSCILLATIONS IN SERIES OF REFERENCE ON DAILY MAXIMUM AND MINIMUM TEMPERATURE IN SOUTH AMERICA. INFERENCE ABOUT PERIODS, LONGITUDE AND INPUT CIRCULATIONS

In order to detect temporal changes in temperature structure, particularly trends, series of maximum and minimum daily surface temperatures were analyzed at 8 reference stations in the south east of South America during variable periods and the longest existing periods (around 100 years). To make a correct diagnosis of the secular variations, a previous analysis was made of the different inhomogeneities existing in the temporal series. To study the evolution of the temperature series and reduce the number of parameters, an algorithm of nonhierarchical cluster analysis was used. This algorithm assigns each day to one of the four groups (i.e. each day is represented by one group only). These groups were classified as Warm, Wet, Cold and Dry. The study shows low frequency variations in the groups which were analyzed through specific properties such as persistence changes, dynamic entropy and circulation structure. The association between the series of groups obtained in the clusters and precipitation was also studied.
Developing an Embodied Pedagogical Agent With and For Young People with Autism Spectrum Disorder

This paper describes how we developed an embodied pedagogical agent (EPA) with and for young people with autism spectrum disorder (ASD). ASD is characterised by impairments in social communication, imagination, and perspective-taking, which can compromise design and collaboration. However, if an ASD preference for visual processing can be supported by providing images of design ideas as they develop, these difficulties may be overcome. We describe a methodology that successfully supports the visualisation and development of EPAs using our prototype visualisation tool (EPA DK), enabling ASD users to function as active design participants.