A Study of Factors Affecting the Personlaity Using Weighted Multi Expert Neural Networks System

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Personality is a dynamic organization of psychological system within an individual that will determine one’s adaptation to the environment. Dynamic Organization means an integration and connection between various aspects of personality. Personality can change, expand and is not statistical. ‘Psychophysical system’ is the habit, attitude, values, beliefs, emotional state, sentiment and motive in the form of psychology but posses physical basis in the nerve system, glands and body in general. Personality as behavior of individuals that are displayed in their everyday lives, this implies that every work or activity done in individual can provide an impression of their true personality. Sometimes our different perceptions are a cause of conflict and misunderstanding in our family, work and social lives in the environment, some of the factors affecting the personality, such as, food, peers, friends, education, upbringing genetics (depression and diseases), traumatic experiences in childhood, self-image, previous experiences in life, attitude and choices about those experiences, medication and bullying. In this paper we analyzed, main factors affecting the personality using weighted multi expert neural network system

Science

International Journal of Computing Algorithm, Vol 3(2), June 2014
ISSN(Print):2278-2397
Website: www.ijcoa.com
A Study of Factors Affecting the Personlaity Using
Weighted Multi Expert Neural Networks System
M.Clement Joe Anand1
, A.Victor Devadoss1
, M.Edal Anand2
1
Department of Mathematics, Loyola College, Chennai
2
M.E Communication Systems, Rajalakshmi Engineering College, Thandalam, Chennai
E-mail: edalanand@gmail.com
Abstract
Personality is a dynamic organization of psychological system within an individual that will
determine one’s adaptation to the environment. Dynamic Organization means an integration
and connection between various aspects of personality. Personality can change, expand and
is not statistical. ‘Psychophysical system’ is the habit, attitude, values, beliefs, emotional
state, sentiment and motive in the form of psychology but possess physical basis in the nerve
system, glands and body in general. Personality as behavior of individuals that are displayed
in their everyday lives, this implies that every work or activity done in individual can provide
an impression of their true personality. Sometimes our different perceptions are a cause of
conflict and misunderstanding in our family, work and social lives in the environment, some
of the factors affecting the personality, such as, food, peers, friends, education, upbringing
genetics (depression and diseases), traumatic experiences in childhood, self-image, previous
experiences in life, attitude and choices about those experiences, medication and bullying. In
this paper we analyzed, main factors affecting the personality using weighted multi expert
neural network system.

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Test Suite Reduction is an optimization technique to identify the minimally sized subset of test cases with enforced constraints involved. The main purpose of test suite reduction is to deduce increased number of test cases that in turn increase the time and cost involved in execution. Fault Detection is the method of identifying the faults that affect the outcome of the system either logically or syntactically. This paper focuses on the reduction of the test suite that has high fault identification rates and also incurs low cost of execution of test cases. The proposed approach includes a new parameter Fault Detection Effectiveness to identify fault rates of test suite; an algorithm for test suite reduction based on priority of requirements; a low cost framework to identify the execution of test cases with minimum budget. Thus, the proposed work defines a test suite that has high fault detection effectiveness providing maximum coverage to requirements at minimum cost of execution.

Test Suite Reduction Based on Fault Detection with Cost Optimization

ijcoa

As the e-commerce is gaining popularity various customer surveys of objects are currently accessible on the Internet. These surveys are frequently disordered, prompting challenges in knowledge discovery and object assessment. This article proposes an object feature positioning skeleton, which consequently recognizes the critical features of an object from online customer surveys. The critical object features are recognized focused around two perceptions: 1) they are normally commented extensively by customers and 2) customer suppositions on the critical feature significantly impact their general assessments on the object. Specifically, given the customer surveys of an item, we first extract the object feature by a shallow reliance parser and focus customer suppositions on these features through an opinion characterizer. We then create a probabilistic object feature positioning calculation to identify the criticalness of perspectives by at the same time considering feature recurrence and the impact of customer opinion given to every feature over their general opinion. The experimental results on 3 popular products demonstrate the effectiveness of our approach.

Artifact Facet Ranking and It’s Applications

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What cause to the neurons of the human brain cells when they are damaged. They become inactive. So damage to subthalamiuc nucleus (STN) neurons of the human brain causing larger involuntary movements and thereby attacking the Parkinson’s disease (PD). Deep brain stimulation (DBS) of bilateral sub thalamic nuclei (STN) is an efficient method of rehabilitation technique in subjects with advanced idiopathic Parkinson’s (or Parkinson) disease. Accurate targeting of STN neurons and placement of microelectrodes/ (neurosensors) are paramount importance for optimal results after STN-DBS method.In this paper, microminiaturized electrode recordings (MER) of STN neurons were detected in a mean of 3.5 ±1.1 channels on right hemisphere and 3.6 ±1.04 on left hemisphere.Final channel selected were most commonly central seen in 42.3% followed by anterior in 33.7%. When a high current is delivered to STN or GPi neurons of basal ganglia (a component of human brain), causing their inhibition and improved indication of symptoms. It is now known that there is a significant change in the firing pattern and a reorganization of the entire basal ganglia circuit with DBS. The MER of STN neurons has identified a specific high frequency irregular larger amplitude firing patterns seen only in disease states and hence used to detect the neurons of ST nucleus during functional surgery. Microelectrode recording is so useful to confirm the right path but has to be taken in consideration with effects on macro stimulation.

Micro-Neuro-Sensor Recording of STN Neurons of the Human Brain

ijcoa

The focus of this paper is to get a bird's eye view of the various factors that could be analyzed to present schools and governments timely indicators of school dropouts. With the help of EDM, one could have access to enormous amounts of data. The crux of the matter would be to identify the data in line with plans and ideas that would eventually lead to the formulation of policies that enhance the teaching and learning process.

EDM: Finding Answers to Reduce Dropout Rates in Schools

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Agile software development has been gaining popularity and replacing the traditional methods of developing software. However, estimating the size and effort in Agile software development still remains a challenge. Measurement practices in agile methods are more important than traditional methods, because lack of appropriate an effective measurement practices will increase the risk of project. This paper discuss about traditional and agile effort estimation model, and analysis done on how the metrics are used in estimation process. The paper also suggeststo use object point and use case point to improve accuracy of effort in agile software development.

Analysis of Effort Estimation Model in Traditional and Agile (USING METRICS ...

ijcoa

Artificial Intelligence (AI) is one of most emerging field in the research field and has given boost to the most growing technology known as Expert System (ES). An ES is a computer based program that is built to solve the problems in specialized domain. There are various expert systems in diversified areas like medical, engineering, agriculture, science etc. have been developed over the last five decades. Stock market is also one of the most important growing areas which shows the country’s economic growth and also shows the need of expert system. This paper mainly highlights the need of expert system in stock market as well as rule based expert system approach for particular stock selection.

Rule Based Approach for Stock Selection: An Expert System

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The thermal continuum emission observed from accreting black holes across X-ray bands has the potential to be leveraged as a powerful probe of the mass and spin of the central black hole. The vast majority of existing ‘continuum fitting’ models neglect emission sourced at and within the innermost stable circular orbit (ISCO) of the black hole. Numerical simulations, however, find non-zero emission sourced from these regions. In this work, we extend existing techniques by including the emission sourced from within the plunging region, utilizing new analytical models that reproduce the properties of numerical accretion simulations. We show that in general the neglected intra-ISCO emission produces a hot-and-small quasi-blackbody component, but can also produce a weak power-law tail for more extreme parameter regions. A similar hot-and-small blackbody component has been added in by hand in an ad hoc manner to previous analyses of X-ray binary spectra. We show that the X-ray spectrum of MAXI J1820+070 in a soft-state outburst is extremely well described by a full Kerr black hole disc, while conventional models that neglect intra-ISCO emission are unable to reproduce the data. We believe this represents the first robust detection of intra-ISCO emission in the literature, and allows additional constraints to be placed on the MAXI J1820 + 070 black hole spin which must be low a• < 0.5 to allow a detectable intra-ISCO region. Emission from within the ISCO is the dominant emission component in the MAXI J1820 + 070 spectrum between 6 and 10 keV, highlighting the necessity of including this region. Our continuum fitting model is made publicly available.

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This edition of our Newsletter is a testament to our collective dedication and the exciting progress we’ve achieved. The completion of our first Periodic Report marks a significant milestone, and the advancements in tetrahedrite mineral-based thermoelectric materials are not just promising -they are a lap towards a sustainable future. We’re excited to share updates on our ongoing activities, our synergistic collaborations with the EHRASE cluster and THERMOS project, and insightful technical information on thermoelectric generators. But that’s not all, join us on the Consortium Tour, where this time SGUDS and IGME-CSIC take centre stage. Plus, don’t miss the insightful interview with Doug Crane from our Scientific Advisory Board, whose expertise enriches our understanding of thermoelectrics. This edition also features the fascinating adventures of Starty, exploring the practical uses of thermoelectric devices in a narrative that’s both educational and engaging. Looking ahead, we eagerly anticipate your visit to the START booth at the upcoming 40th International and 20th European Thermoelectric Conference, ICT/ECT 2024, in Krakow. We hope this Newsletter serves not only as a source of information but also as an inspiration for continued excellence. Stay connected with us for more exciting updates from START on our website and social media channels.

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ManganesehasbeenobservedonMarsbytheNASACuriosityroverinavarietyofcontextsand isanimportantindicatorofredoxprocessesinhydrologicsystemsonEarth.WithintheMurrayformation,an ancientprimarilyfine‐grainedlacustrinesedimentarydeposit inGalecrater,Mars,haveobservedupto45× enrichmentinmanganeseandupto1.5×enrichmentinironwithincoarsergrainedbedrocktargetscomparedto themeanMurraysedimentcomposition.Thisenrichment inmanganesecoincideswiththetransitionbetween twostratigraphicunitswithintheMurray:SuttonIsland, interpretedasalakemarginenvironment,andBlunts Point,interpretedasalakeenvironment.OnEarth,lacustrineenvironmentsarecommonlocationsofmanganese precipitationduetohighlyoxidizingconditionsinthelakes.Here,weexplorethreemechanismsfor ferromanganeseoxideprecipitationatthislocation:authigenicprecipitationfromlakewateralongalakeshore, authigenicprecipitationfromreducedgroundwaterdischargingthroughporoussandsalongalakeshore,and earlydiageneticprecipitationfromgroundwaterthroughporoussands.All threescenariosrequirehighly oxidizingconditionsandwediscussoxidantsthatmayberesponsiblefortheoxidationandprecipitationof manganeseoxides.Thisworkhasimportant implicationsforthehabitabilityofMarstomicrobesthatcould haveusedMnredoxreactions,owingtoitsmultipleredoxstates,asanenergysourceformetabolism.

Manganese‐RichSandstonesasanIndicatorofAncientOxic LakeWaterConditionsinGale...

Sérgio Sacani

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In the Nice model of solar system formation, Uranus and Neptune undergo an orbital upheaval, sweeping through a planetesimal disk. The region of the disk from which material is accreted by the ice giants during this phase of their evolution has not previously been identified. We perform direct N-body orbital simulations of the four giant planets to determine the amount and origin of solid accretion during this orbital upheaval. We find that the ice giants undergo an extreme bombardment event, with collision rates as much as ∼3 per hour assuming km-sized planetesimals, increasing the total planet mass by up to ∼0.35%. In all cases, the initially outermost ice giant experiences the largest total enhancement. We determine that for some plausible planetesimal properties, the resulting atmospheric enrichment could potentially produce sufficient latent heat to alter the planetary cooling timescale according to existing models. Our findings suggest that substantial accretion during this phase of planetary evolution may have been sufficient to impact the atmospheric composition and thermal evolution of the ice giants, motivating future work on the fate of deposited solid material.

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In-Pond Raceway Systems (IPRS) represent a cutting-edge method in pond aquaculture, effectively combining the advantages of confining fish in a restricted area within the pond with the efficiency of a flowing water system. This innovative approach facilitates water circulation within the pond, mimicking the natural flow found in riverine environments. By creating this dynamic water movement, IPRS significantly enhances the pond's productivity potential. The core principle of IPRS involves the installation of specific components that work in concert to circulate and refresh the water within the pond, all while preventing any discharge into the surrounding environment. This setup effectively utilizes a dividing partition, or baffle, to create a circular water flow pattern. As a result, the water undergoes continuous mixing and movement, optimizing conditions for fish growth and minimizing stagnation.

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Presenter: Andrew Schroeder, PhD. Project Manager & Senior Data Curator, 4D Nucleome Data Coordination and Integration Center (4DN-DCIC), Park Lab, Department of Biomedical Informatics, Harvard Medical School Abstract The Common Fund 4D Nucleome program, currently in its 9th year, is a consortium of researchers that aims to understand the principles behind the three-dimensional organization of the nucleus and how this organization can change over time to affect a variety of cellular processes. The 4DN Data Portal (data.4dnucleome.org) is an expanding resource hosting data generated by the 4DN Network and other reference nucleomics data sets. The portal provides tools for search, exploration, visualization, and download. An overview of the data portal, highlighting available data, how it can be found, visualized and used for analyses will be presented. The top 3 key questions that the 4DN data portal can answer: 1. Are there significant sites of long-range chromatin contacts near my gene or region of interest? 2. What omics datasets are available for my tissue of interest? 3. Are there imaging datasets available that are relevant to my tissue of interest? Upcoming webinars schedule: https://dknet.org/about/webinar

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Studying the escaping atmospheres of highly irradiated exoplanets is critical for understanding the physical mechanisms that shape the demographics of close-in planets. A number of planetary outflows have been observed as excess H/He absorption during/after transit. Such an outflow has been observed for WASP-69b by multiple groups that disagree on the geometry and velocity structure of the outflow. Here, we report the detection of this planet’s outflow using Keck/NIRSPEC for the first time. We observed the outflow 1.28 hr after egress until the target set, demonstrating the outflow extends at least 5.8 × 105 km or 7.5 Rp This detection is significantly longer than previous observations, which report an outflow extending ∼2.2 planet radii just 1 yr prior. The outflow is blueshifted by −23 km s−1 in the planetary rest frame. We estimate a current mass-loss rate of 1 M⊕ Gyr−1 . Our observations are most consistent with an outflow that is strongly sculpted by ram pressure from the stellar wind. However, potential variability in the outflow could be due to time-varying interactions with the stellar wind or differences in instrumental precision.

WASP-69b’s Escaping Envelope Is Confined to a Tail Extending at Least 7 Rp

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Large language models (LLMs) are in the spotlight. Laypeople are aware of and are using the LLMs such as OpenAI’s ChatGPT and Google’s Gemini on a daily basis. While companies are exploring new business opportunities, researchers have gained access to an unprecedented scientific playground that allows for fast experimentation with limited resources and immediate results. In this talk, using concrete examples from requirements engineering, I am going to put forward several research opportunities that are enabled by the advent of LLMs. I will show how LLMs, as a key example of modern AI, unlock research topics that were deemed as too challenging until recently. Then, I will critically discuss the perils that we face when it comes to planning, conducting, and reporting on credible research results following a rigorous scientific approach. This talk will stress the inherent tension between the exciting affordances offered by this new technology, which include the ability to generate non-factual outputs (fiction), and our role and societal responsibility as information scientists.

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A Study of Factors Affecting the Personlaity Using Weighted Multi Expert Neural Networks System

1. International Journal of Computing Algorithm, Vol 3(2), June 2014 ISSN(Print):2278-2397 Website: www.ijcoa.com A Study of Factors Affecting the Personlaity Using Weighted Multi Expert Neural Networks System M.Clement Joe Anand1 , A.Victor Devadoss1 , M.Edal Anand2 1 Department of Mathematics, Loyola College, Chennai 2 M.E Communication Systems, Rajalakshmi Engineering College, Thandalam, Chennai E-mail: edalanand@gmail.com Abstract Personality is a dynamic organization of psychological system within an individual that will determine one’s adaptation to the environment. Dynamic Organization means an integration and connection between various aspects of personality. Personality can change, expand and is not statistical. ‘Psychophysical system’ is the habit, attitude, values, beliefs, emotional state, sentiment and motive in the form of psychology but possess physical basis in the nerve system, glands and body in general. Personality as behavior of individuals that are displayed in their everyday lives, this implies that every work or activity done in individual can provide an impression of their true personality. Sometimes our different perceptions are a cause of conflict and misunderstanding in our family, work and social lives in the environment, some of the factors affecting the personality, such as, food, peers, friends, education, upbringing genetics (depression and diseases), traumatic experiences in childhood, self-image, previous experiences in life, attitude and choices about those experiences, medication and bullying. In this paper we analyzed, main factors affecting the personality using weighted multi expert neural network system.

A Study of Factors Affecting the Personlaity Using Weighted Multi Expert Neural Networks System

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