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FORMULATION, DEVELOPMENT AND EVALUATION OF CHRONOTHERAPEUTIC DRUG DELIVERY SYSTEM FOR THE TREATMENT OF NOCTURNAL ASTHMA BY USING SALBUTAMOL SULPHATE MICROSPHERE
Asthma can show noticeable daily fluctuations. Patients usually have symptoms that appear mainly during sleep, and even when symptoms occur during the day, they usually worsen at night. Deaths from asthma also usually occur at night or in the early morning. The rational of this study is to design and evaluate an oral site-specific, pulsatile drug delivery system containing Salbutamol Sulphate, which can be targeted to colon in a pH and time dependent manner, to modulate the drug level in synchrony with the circadian rhythm of nocturnal asthma. In the present research work, we have attempted to develop a novel dosage form by using a chronopharmaceutical approach. A microsphere dosage form, taken at bed time with a programmed start of drug release early in morning hours, can prevent a sharp increase in the incidence of asthmatic attacks, during the early morning hours (nocturnal asthma), a time when the risk of asthmatic attacks is the greatest.
Systematic Analysis of Predictive Modeling Methods in Stock Markets
Stock Market Prediction is a challenging task due to the volatile, unpredictable and chaotic nature of the stock market. Global digitization has revamped SMP and trading techniques. Many researchers have employed Machine learning for predicting future value of stocks helping investors to make safe and wise financial decisions. This study systematically examines the traditional prediction methods and the modern approaches that utilize Artificial Intelligence and Machine Learning for the task of prediction. The study compares and contrasts various supervised and unsupervised techniques and Artificial Neural Networks that use temporal data for prediction. Performance of algorithms depends on the dynamic input data, and the nature of forecast. Data fitting is an important concern for identifying, analyzing and predicting future instances. Extensive research is required to build appropriate modules for data pre-processing, analysis, and prediction. Comparing the performance of ML algorithms with traditional methods is required to prove their effectiveness. The study explores the strengths of various ML algorithms to develop a basic understanding, and paves the way for further research in the field of Stock Market Prediction.
Comprehensive Analysis of Privacy Preserving Data Mining Algorithms for Future Develop Trends
The present trend of digitalization involves data sharing between various organizations such as hospitals, insurance firms, banks, stock market, and other businesses. Enormous amount of data is burgeoning at an exponential rate. Digitizing technology has entered every field, including various digital gadgets and applications used in our daily life. This data is used by analytics to aid in decision-making, understanding customer behavior, predicting market trends, etc. Despite the benefits offered by data mining and analysis, it presents some serious issues related to data privacy and security. Privacy Preserving Data Mining, PPDM, is an application of data mining that addresses these concerns. Various PPDM methods attempt to prevent sensitive data and identity disclosure by applying some transformations to the data. The main challenge is to maintain data quality for good classification accuracy while preserving data privacy. This study examines a number of privacy-related risks. In addition to this, concepts related to privacy preservation with data mining is the primary subject of this article. Understanding all of the findings presented will help one comprehend various challenges faced by PPDM techniques. Additionally, it will assist in learning and using the most appropriate strategy for any data scenario.
DESIGNING THE ROLE OF SETTLEMENTS IN URBAN AREAS TO INCREASE GROUNDWATER CONSERVATION EFFORTS
This article is based on research results that state that floods and droughts occur almost every year in many places in the biosphere. It happens because there is no proper water management. Rainwater is the primary water source in life; the balance between discharge and income (recharge) is not controlled. In this article, we try to manage rainwater by inviting the whole community with yard media, where every person in the world takes refuge in the yard. Data is taken from yards in the settlement of Surabaya, as a large city on the coast located in the lowlands, densely populated (100 inhabitants / Ha), prone to flooding and intrusion of seawater. They determined the size of the yard most inhabited by most people of Surabaya, namely the size of the land < 300m2, studied 40 yards as samples. The variables studied were: the land area of the yard, the site of the building, the canopy area of the trees, the size of ornamental plant headers, the scope of grass, the location of the open section, and the percentage of coarse grains (these six variables as predictors), rainfall (determined by intensity as a standard count), and runoff of water that comes out of the yard (as criterium). Results of analysis with multiple regressions; Successive yard variables are the area of the building, the location of grass, the site of open land, the scope of the tree canopy, gauze grains above the ground, and lastly, the area of ornamental plants. The six variables contributed to the surface runoff of 61.1%; thus, planning yard patterns in the city of Surabaya or other cities should pay attention to the role of these variables.
QUICKLY UNDERSTANDING VIDEO LEARNING BASE ON ENVIRONMENTAL SCIENCE TO IMPROVE ABILITY OF SENSITIVITY TO THE SITUATION OF CIVIL ENGINEERING STUDENTS
It takes the material in the form of global environmental issues such as human relationships with the environment, ecological principles, natural resources, environmental pollution, environmental ethics, and environmental impact analysis (AMDAL) (environmental impact assessment). This research aims to develop videos for the learning of civil engineering students to increase sensitivity to the environment. This research is development research with 4D model design, which is carried out up to the 3rd stage of the four existing steps: define, design, develop, and disseminate. The research object is a video-based learning medium in environmental science courses, and the research subjects are three validators and 30 students who program Environmental Science courses. Research instruments consist of 1). Validation sheet to measure the feasibility of video-based media containing 15 statement items with preferred Likert scale scores of 1 to 5 and score ranges of 1-75; 2). Test of learning results to measure the feasibility of video-based media after learning containing 20 questions with a score of 0 or 1 and a score range of 0-100. The results showed: first, video-based learning media used in learning activities in Environmental Science courses are categorized as very feasible. The assessment results of the three validators showed that the average value of video-based learning media eligibility of 4.73 with very proper wording. Details of aspects of the assessment include the presentation of material with an average score of 4.78, narrative quality of 4.67, writing the balance of 4.78, quality of music (back sound) of 4.56, the harmony of the colour of the average score of 4.89. Second, after applying video-based learning media in Environmental Science courses, student learning outcomes show "excellent" criteria. The average score of 30 students is 80.17, indicating that the video-based learning media in Environmental Science courses is feasible.
PCB DESIGN OF A SERVO MOTOR CONTROLLER UNDER STRICT COST CONSTRAINS – SIGNAL INTEGRITY AWARE DESIGN
This work comes within the scope of developing an automated linear axis that will be used in a novel production machine. The axis needs precise control over the linear movement, calling for a servo-controlled motor. There are many types of motors that can be used, starting from inexpensive stepper motors, up to expensive and performant multi pole permanent magnet synchronous motors. The project calls for a servo drive that will be able to deliver a power output within 200 to 600 Watts, with an efficiency of over 80%. Brushless DC motors offer many possibilities within this range of powers with outstanding price/performance ratios. Open source projects like TinyMovr, Vesc and ODrive propose highly performant software stacks that are used extensively within robotics communities. These open software solutions need adequate hardware platforms to perform. The scope of this work is the description of the steps taken to design the printed circuit boardon which the ODrive servo motor control firmware can be implemented, from the signal integrity point of view. Under normal cost constrains, the PCB would have been implemented using a minimum of four copper layers. It is the aim of this design to fulfil a stricter cost constrain that only allows for a two layer board to be used.
PCB DESIGN OF A SERVO MOTOR CONTROLLER UNDER STRICT COST CONSTRAINS –THERMAL AWARE COMPONENT LAYOUT
This work comes within the scope of developing an automated linear axis that will be used in a novel production machine. The axis needs precise control over the linear movement, calling for a servo-controlled motor. There are many types of motors that can be used, starting from inexpensive stepper motors, up to expensive and performant multi pole permanent magnet synchronous motors. The project calls for a servo drive that will be able to deliver a power output within 200 to 600 Watts, with an efficiency of over 80%. Brushless DC motors offer many possibilities within this range of powers with outstanding price/performance ratios. Open source projects like TinyMovr, Vesc and ODrive propose highly performant software stacks that are used extensively within robotics communities. These open software solutions need adequate hardware platforms to perform. The scope of this work is the description of the steps taken to design the printed circuit board on which the ODrive servo motor control firmware can be implemented, from the point of view of the thermal effects of its components. Under normal cost constrains, the PCB would have been implemented using a minimum of four copper layers. It is the aim of this design to fulfil a stricter cost constrain that only allows for a two layer board to be used.
PREDICTION OF ANXIETY DISORDER OF THE CORONAVIRUS PANDEMIC USING ARTIFICIAL INTELLIGENCE TECHNOLOGY
Emerging reports indicate heightened anxiety among university students during the Corona pandemic. Implications of which can impact their academic performance. Artificial intelligence (AI) through machine learning can be used to predict which students are more susceptible to anxiety which can inform closer monitoring and early intervention. To date, there are no studies that have explored the efficacy of AI to predict anxiety among college students. Data was collected using an online survey that included general information; Covid-19 stressors and (GAD-7). This scale categorizes level of anxiety to none, mild, moderate, and severe. We received several survey answers. Several machine learning classifiers were used to develop the best fit model to predict student level of anxiety. In order to overcome this problem and to ensure the Mental Well-being of university students by developing best fit model to predict anxiety and to rank the most important factors affecting anxiety. And suggesting after care such as Meditation, yoga and breathing exercises etc., According to the level they fall in from the scale 1 to 10 which are categorized into Mild, moderate and severe.
OPTIMIZATION OF GAS PIPELINE UTILIZATION FOR SECTION 2 PEMPING-TANJUNG UNCANG WITH THE PROVISION OF MINI LNG PLANT FOR KARIMUN REGENCY
Investment evaluation is a crucial part of investment decisions to measure will the project generate profit for the company. There is four Capital Budgeting technique used to measure this investment evaluation in this project Net Present Value (NPV), Internal Rate Return (IRR), Discounted Probability Index (DPI), and Payback Period (PBP). From the evaluation, it was obtained that a positive NPV of 280.649, an IRR of 8,10% greater than the WACC of 4,21%, while the DPI of 1.25 and PBP of 3,25 years was faster than the duration of the 5 (five) year contract. Monte Carlo simulation used 1.000 times to calculate Probability NPV<0 with result Probability NPV<0 in this project is 0,17% meanwhile probability NPV>0 is 99,83%.In the sensitivity analysis, it is found that the increase in the cost of capital and the duration of the agreement are factors that are sensitive to project feasibility. From the results of the above calculations, it can be concluded that Optimization Of Gas Pipeline Utilization For Section 2 Pemping – Tanjung Uncang With The Provision Of Mini LNG Plant For Karimun Regency is Eligible to be accepted.
THE EFFECT OF LAND USE UTILIZATION ON TRAFFIC PERFORMANCE ON THE NATIONAL ROAD SEGMENTIN PALU CITY
Economic improvement in Palu City has an impact on changes in the structure and general view of transportation facilities, by technological advances, as well as engineering in the field of transportation, so that the public's need for transportation can provide maximum service. This study aims to analyze the degree of saturation and identify the use of land use, as well as to analyze the influence of land use development along the National Road Corridor Jalan Jenderal Sudirman – Pelabuhan Pantoloan? The results of the study show that the development of land use will cause attraction and generation from an area, increasing accessibility and intensity of traffic flow using this road corridor with the largest degree of saturation in Segment 3 - Jl. Yos Sudarso is 0.65 and Segment 5 - Kebonsari – Tawaeli is 0.63. It is found that the generation of movement, residential areas, gives a figure of 1737 smp/hour. As for the pull of movement, it is strongly influenced by the trade and service area with 2041 smp/hour. In the Office Area for attraction of movement of 838 junior high school/hour, Education Area of 22 junior high school/hour and Health Area of 26 junior high school/hour. Almost all of these interactions are carried out with trips that will result in traffic flow, thus causing a problem with increasing traffic volume along the road which causes the performance of the road segment to decrease.
THE NUMERICAL STUDY OF DYNAMIC SUSCEPTIBILITY OF THE LAYERED FERROELECTRIC STRUCTURE
In this study, we focused on the structure where a ferroelectric material (FE b) is sandwiched by the other type of ferroelectric material (FE a). The susceptibility is an important parameter which is determining the response of the materials to the external fields. In the numerical study, the susceptibility of the layered structure is obtained by applying the effective medium approach. The layered structure which is consisted of two or more different materials can be treated as one unit material which possesses effective susceptibility. This effective susceptibility is required when we study the optical behaviour of the layered structure. Here, we used entire-cell effective medium approximation. In this approximation, each layer of the ferroelectrics is considered to be comprised of several lattices. Then, by considering Maxwell continuity of fields across the lattices, the Landau-Khalatnikov (LK) equations of motion for each lattice are solved simultaneously to get the effective susceptibility of the layered system. In the calculation, we use parameters for FE which illustrates BaTiO3 while parameters for FE b are randomly vary. We found that the number of lattices in each layer affect the value of the effective susceptibility. We also found that an effective medium with two close resonance frequencies can be obtained when the difference of two resonance frequencies of the composed materials is around one percent of the higher frequency.
PCB DESIGN OF A SERVO MOTOR CONTROLLER UNDER STRICT COST CONSTRAINS – PI AWARE DESIGN
This work comes within the scope of developing an automated linear axis that will be used in a novel production machine. The axis needs precise control over the linear movement, calling for a servo-controlled motor. There are many types of motors that can be used, starting from inexpensive stepper motors, up to expensive and performant multi pole permanent magnet synchronous motors. The project calls for a servo drive that will be able to deliver a power output within 200 to 600 Watts, with an efficiency of over 80%. Brushless DC motors offer many possibilities within this range of powers with outstanding price/performance ratios. Open source projects like TinyMovr, Vesc and ODrive propose highly performant software stacks that are used extensively within robotics communities. These open software solutions need adequate hardware platforms to perform. The scope of this work is the description of the steps taken to design the printed circuit boardon which the ODrive servo motor control firmware can be implemented, from the point of view of the power integrity of its energy supply means. Under normal cost constrains, the PCB would have been implemented using a minimum of four copper layers. It is the aim of this design to fulfil a stricter cost constrain that only allows for a two layer board to be used.
LOCAL CONTENT CURRICULUM PLANNING BASED LIFE SKILL AT ASKHABUL KAHFI VOCATIONAL SCHOOL
This work comes within the scope of developing an automated linear axis that will be used in a novel production machine. The axis needs precise control over the linear movement, calling for a servo-controlled motor. There are many types of motors that can be used, starting from inexpensive stepper motors, up to expensive and performant multi pole permanent magnet synchronous motors. The project calls for a servo drive that will be able to deliver a power output within 200 to 600 Watts, with an efficiency of over 80%. Brushless DC motors offer many possibilities within this range of powers with outstanding price/performance ratios. Open source projects like TinyMovr, Vesc and ODrive propose highly performant software stacks that are used extensively within robotics communities. These open software solutions need adequate hardware platforms to perform. The scope of this work is the description of the steps taken to design the printed circuit board on which the ODrive servo motor control firmware can be implemented, from the point of view of the thermal effects of its components. Under normal cost constrains, the PCB would have been implemented using a minimum of four copper layers. It is the aim of this design to fulfil a stricter cost constrain that only allows for a two layer board to be used.
A SURVEY ON TEXT PRE-PROCESSING AND FEATURE EXTRACTION TECHNIQUES FOR SENTIMENT ANALYSIS OF TWITTER DATA
Natural Language Processing (NLP) is a popular branch of Artificial Intelligence (AI) that is concerned with how machines comprehend and interpret human language. A computer can only comprehend information in the form of numbers, not words. As a result, it's critical to research what preprocessing and feature extraction techniques are required to implement on a human language so that when it's transformed to machine-readable form, the computer can understand it. Text classification plays a vital role in NLP jobs, with applications in web search, document categorization, chatbots, virtual assistants, and other areas. Sentences and writings that lack structure are naturally difficult to convert to a machine-readable format. Pre-processing techniques have been given special attention since they serve as a precursor to the following stages of information retrieval strategies. Any errors in the early preprocessing approaches are passed on to the NLP pipeline's later stages. In addition, the order in which techniques like tokenization, StopWords elimination, and lemmatization are used is carefully considered. Information retrieval systems are particularly concerned with how efficiently textual input is cleaned and filtered to remove noisy material that does not add to efficiency and, moreover, leads to incorrect results. This survey work emphasizes the importance of effective text preprocessing approaches, as well as information retrieval using Natural Language Processing feature extraction techniques.
A PERUSAL STUDY OF METHODS FOR ENERGY EFFICIENT MULTI OBJECT TRACKING IN WIRELESS SENSOR NETWORKS
Wireless sensor networks (WSNs) has various applications in different areas such as object detection and target tracking, industrial process monitoring, environmental monitoring, wildlife monitoring, Robot control and security applications for buildings. In WSNs, Energy efficiency is one of the important research issues, as it determines the lifetime of the sensor network deployed for the specific applications. Object tracking is one of the dominant applications of wireless sensor networks and many energy-efficient multi object tracking algorithms are used for precise or exact object tracking. The main focus this paper is the perusal study of all different energy-efficient object tracking methods and algorithms for Wireless Sensor Network.
NETWORK IMPLEMENTATION AND OPTIMIZATION FOR QUALITY OF SERVICE MANAGEMENT BASED ON SEMANTIC INTENTIONS
Data transmitted over the Internet is much more vulnerable than when it travels over an organization's internal network.A good compromise is to use the Internet as a transmission medium using a protocol that allows data to be transmitted in an encrypted manner. We then speak of a private network. This system therefore makes it possible to obtain a secure connection at a lower cost, and which is based on an encapsulation protocol (tunneling which uses cryptographic protection services, security and dynamic key management, these foundations guarantee both power and flexibility in protecting communications between computers on this network.
A SYSTEMATIC REVIEW OF HEART DISEASE USING ARTIFICIAL NEURAL NETWORK
The human cerebrum is the main organ; however the heart comes in at a nearby second. The heart is answerable for coursing blood all through the body. The medical field's work to anticipate the beginning of heart disease is significant. Medical focuses can profit from data examination since it considers the expectation of a more extensive scope of diseases from a bigger pool of data. A pile of patient data is recorded and refreshed consistently. The gathered data might act as a solid reason for gauging the development of new diseases. Artificial Neural Networks (ANNs), Choice Trees, Fuzzy Logic (FL), K-Nearest Neighbours (KNNs), Generalized Regression Neural Network (GRNN), Feed forward Back progation Neural Network (FFBP) and Support Vector Machines (SVMs) are just not many of the data mining and machine learning approaches used to foresee cardiovascular disease. This paper sums up past examination and offers new experiences into the ongoing calculation.
ATTENTION BASED IMAGE CAPTIONING USING DEEP LEARNING
The process of deriving written descriptions from a picture based on the items and behaviours portrayed is known as image caption generation. The resulting description will represent what is in the image and the interactions among the objects. However, like with any other image processing challenge, recreating this characteristic in an artificial system is a difficult feat, and so the adoption Deep Learning procedures can help to tackle the problem. The main goal of this project is to generate an image captioning model that can provide a concise and relatable description of the picture by incorporating an attention mechanism. Ideally, the model can be separated into two components – one is called Encoder and the other is a Decoder. The encoder used here is a Google InceptionV3 pre-trained model. And the decoder is a language-based model, Gated Recurrent Unit (GRU) to translate the characteristics and objects provided by the encoder into natural sentences. Furthermore, the model's effectiveness is aided by the attention mechanism. To conclude, the model is trained on a subset of the MS COCO dataset, which contains about 80,000 pictures with at least five descriptions each and evaluated based on the BLEU score. To reduce the loss, the model weights are tuned using the categorical cross-entropy loss function. The results of the model are promising and competitive.
A REVIEW ON HPLC APPROACHES FOR SIMULTANEOUSLY DETERMINING ANTIHYPERTENSIVE DRUG COMBINATIONS
Recent demand for high-throughput analyses with high sensitivity and selectivity to molecules and drugs in different classes with different physical-chemical properties and a reduction in analysis time is a major milestone for novel methodologies, especially when analytical procedures are applied to clinical purposes. Multi-drug therapy are used to treat multiple diseases to prevent high doses of a single medicine that could produce negative effects. In recent years, fast approaches for analysing mixed compounds have been in high demand. New procedures and devices were created to meet these needs. Complex matrices can slow sample preparation and processing. Quantitative drug association profiles face issues with components, matrices, compounds, and physical-chemical complexity. We discuss HPLC methods for the determination of different combination of Benidipine hydrochloride, Metoprolol succinate, Azelnidipine, Bisoprolol Fumarate, and Cilnidipine. This study covers recently optimised procedures such as chromatographic separation, as well as methodologies that have improved accuracy, sensitivity, and selectivity in quantitative drug association analyses.
CHROMATOGRAPHIC STUDY AND BEHAVIOURAL STUDY OF KSHIRBALA TAILA
Kshirbala taila is a known Ayurvedic remedy for Rheumatoid Arthritis. Its basic physico-chemical evaluation profile is reported in Ayurvedic Pharamcopoiea of India. Detailed analysis was the objective of study. The formulation was prepared using Sida cordifolia roots, sesame oil and cow milk according to literature. The formulation was then subjected to various chemical investigations. Unsaponifiable matter was studied for preliminary phytochemical screening and chemoprofiling of expected phyto-constituents using chromatographic techniques. TLC confirmed presence of sesamin, b-sitosterol, lupeol and ephedrine presence. The pre and post treatment behavioral studies were also studied and reports revealed that pain induced stress symptoms are severe in untreated arthritic rats while treated rats show significantly less frequency of occurrence compared to negative control group.