Information Processing Systems Research Articles

Application of neural network algorithm in computer data information processing system

In order to solve the problem that the data processing frequency of the traditional centralized data processing system is low, which leads to the poor feedback effect of massive data, this paper proposes a computer data information processing system based on neural network algorithm. Based on the original system hardware, the system replaces the data processor and increases the total number of the processor, so as to realize the distributed synchronous processing of massive data. In the aspect of software design, the interaction between system units and modules is formed through the protocol to improve the data communication mode of the system; Calculate the Euclidean distance and set the distributed processing mode of the system; According to the definition of cloud computing, the classification function is used to determine the constraints, establish the processing frequency equation, and realize the rapid processing of massive data. The experimental results show that the processing frequency of the system designed in this paper is more than 50% higher than that of the traditional system, which solves the problem of low processing frequency caused by weak analysis ability and slow response speed in the traditional system. Conclusion: compared with the traditional system, the system designed in this paper has faster processing frequency for massive data and better feedback effect to users.

The comparison of hot and cold executive functions in patients with bipolar II disorder, borderline personality disorder, and healthy individuals.

Differential diagnosis of bipolar II disorder (BD-II) and borderline personality disorder (BPD) has always been challenging for clinicians due to symptoms' overlap. This study aimed to compare hot and cold executive functions (EFs) in BD-II patients, as well as BPD and healthy controls (HCs), in order to differentiate these two disorders. In the present study, 30 BD-II and 30 BPD patients undergoing the drug therapy with mood stabilizers, and 30 HC were examined using EFs evaluated tests. The data were then analyzed using ANOVA and Tukey post hoc test. The BD-II Patients performed significantly less in all cold EFs than the HC. Also, BPD patients had meaningfully lesser performance compared to HC in all cold EFs except sustained attention. No significant difference was perceived between the two patient groups in the cold EFs. In BD-II patients, the risky decision-making as a hot EFs' component was not significantly different from HC; nevertheless, its amount was significantly higher in BPD than in the HC and BD-II patients. These findings underline the differences between the two mentioned disorders based on the hot EFs, which may indicate further disorder in the emotional information processing system among the BPD patients.

Iterative kernel regression with preconditioning

Kernel methods are popular in nonlinear and nonparametric regression due to their solid mathematical foundations and optimal statistical properties. However, scalability remains the primary bottleneck in applying kernel methods to large-scale data regression analysis. This paper aims to improve the scalability of kernel methods. We combine Nyström subsampling and the preconditioned conjugate gradient method to solve regularized kernel regression. Our theoretical analysis indicates that achieving optimal convergence rates requires only [Formula: see text] memory and [Formula: see text] time (up to logarithmic factors). Numerical experiments show that our algorithm outperforms existing methods in time efficiency and prediction accuracy on large-scale datasets. Notably, compared to the FALKON algorithm [A. Rudi, L. Carratino and L. Rosasco, Falkon: An optimal large scale kernel method, in Advances in Neural Information Processing Systems (Curran Associates, 2017), pp. 3891–3901], which is known as the optimal large-scale kernel method, our method is more flexible (applicable to non-positive definite kernel functions) and has a lower algorithmic complexity. Additionally, our established theoretical analysis further relaxes the restrictive conditions on hyperparameters previously imposed in convergence analyses.

Valley Pseudospin Polarized Evanescent Coupling between Microwave Ring Resonator and Waveguide in Phononic Topological Insulators.

A coupled ring-waveguide structure is at the core of bosonic wave-based information processing systems, enabling advanced wave manipulations such as filtering, routing, and multiplexing. However, its miniaturization is challenging due to momentum conservation issues in rings with larger curvature that induce significant backscattering and radiation leakage and hampering stable operation. Here, we address it by taking an alternative approach of using topological technology in wavelength-scale and microwave ring-waveguide coupled systems built in nanoengineered phononic crystals. Our approach, which leverages pseudospin conservation in valley topological systems, eliminates phonon backscattering and achieves directional evanescent coupling. The resultant hypersonic waves in the tiny ring exhibit robust transport and resonant circulation. Furthermore, the ring-waveguide hybridization enables critical coupling, where valley-dependent ring-waveguide interference blocks the transmission. Our findings reveal the capability of topological phenomena for managing ultrahigh-frequency phonons in nano/microscale structures and pave the way for advanced phononic circuits in classical and quantum signal processing applications.

LED light sources with a sun-like emission spectrum for children’s institutions

The article looks more like a scientific-theoretical than an experimental one, so it is proposed to remove the IMRAD structure, especially since it is given only in the summary, but not in the article itself.
 “In Russia, under the national project “Education”, a large-scale program for the construction of schools is underway. About 700 schools have already been built, and if in general for all programs, this is 900 schools..... Many schools have swimming pools, modern canteens...” noted the head of the relevant ministry at a meeting with the President of the Russian Federation Vladimir Putin at the beginning of 2023. In total, about 750 billion rubles were allocated to finance the program for the construction of new schools. (it includes 454 billion from the federal budget). In total, it is planned to build 1,300 educational institutions, which will have more than 1 million places. In addition to the construction of new schools, the plan provides for the implementation of a program of capital repairs and technical renovation of existing general education institutions by the end of 2026: it will include 7,300 buildings. The pace of capital renovations has also accelerated in 2022–2023: three thousand buildings will be renovated, mainly in rural areas. By 2024, all 27 thousand rural schools, according to modern requirements, will be equipped with modern equipment. In modern schools, it is planned to equip computer classes with modern computing equipment, and energy saving plans provide for the widespread use of LED lighting. The reasons for the negative effects of the light spectrum of LED lighting and personal computer monitors on the health 
 of children and adolescents, in particular the increase in myopia, have not yet been sufficiently studied.
 Analytical, sociological, and statistical methods were used.
 The relationship between physiological and behavioural factors that may lead to decreased vision is described. The restructuring of the work of the visual analyzer, associated with the selection of information in accordance with the models proposed in the social environment has been suggested to contribute to the formation 
 of myopia; with a decrease in one’s own search activity with increased myopia; with an increase in the functioning of internal information processing systems and 
 a decrease in the systems of perception and implementation of actions.
 Limitations. The study was limited to the area of study of the subject of research, materials from the Scopus, Web of Science, MedLine, The Cochrane Library, EMBASE, Global Health, CyberLeninka, RSCI databases and our own experiments.
 Conclusion. The spectral composition of artificial light and its intensity give rise to the prerequisites for the development of myopia or another functional-structural response in the variety of ganglion, amacrine cells, and receptors in the visual analyzer of multicellular animals. The narrow and incomplete spectrum of light from domestic LED lamps cannot be a good choice for the prevention of myopia in children. Considering the diversity of opsins in the human visual analyzer, we have developed and manufactured an artificial, light source using LEDs and phosphors, the spectrum of which considers the spectral photosensitivity of opsins in the human eye and is close as possible to the spectrum of sunlight at a correlated colour temperature of about 4000 and 3000 K. The first one has now been manufactured a batch of lamps, the spectral composition of the emitted light of which has no analogues and is ahead of the world’s best samples in terms of spectrum composition and efficiency level. The spectrum of this light source was demonstrated in a presentation at the Erisman Readings 2023. To elucidate the biological mechanisms of the development of myopia in children, additional efforts are needed within the framework of a new scientific direction - evolutionary hygiene. This will make it possible to establish how small changes in the composition of the light spectrum (emission in the region of 410–450 nm, dip in the region of 480 nm and absence of 380 nm) of artificial sources influenced catastrophic (chaotic) changes at the genetic level of humans and the entire living world.

A wideband, high-resolution vector spectrum analyzer for integrated photonics

The analysis of optical spectra—emission or absorption—has been arguably the most powerful approach for discovering and understanding matter. The invention and development of many kinds of spectrometers have equipped us with versatile yet ultra-sensitive diagnostic tools for trace gas detection, isotope analysis, and resolving hyperfine structures of atoms and molecules. With proliferating data and information, urgent and demanding requirements have been placed today on spectrum analysis with ever-increasing spectral bandwidth and frequency resolution. These requirements are especially stringent for broadband laser sources that carry massive information and for dispersive devices used in information processing systems. In addition, spectrum analyzers are expected to probe the device’s phase response where extra information is encoded. Here we demonstrate a novel vector spectrum analyzer (VSA) that is capable of characterizing passive devices and active laser sources in one setup. Such a dual-mode VSA can measure loss, phase response, and dispersion properties of passive devices. It also can coherently map a broadband laser spectrum into the RF domain. The VSA features a bandwidth of 55.1 THz (1260–1640 nm), a frequency resolution of 471 kHz, and a dynamic range of 56 dB. Meanwhile, our fiber-based VSA is compact and robust. It requires neither high-speed modulators and photodetectors nor any active feedback control. Finally, we employ our VSA for applications including characterization of integrated dispersive waveguides, mapping frequency comb spectra, and coherent light detection and ranging (LiDAR). Our VSA presents an innovative approach for device analysis and laser spectroscopy, and can play a critical role in future photonic systems and applications for sensing, communication, imaging, and quantum information processing.

Coherent control of an optical tweezer phonon laser

The creation and manipulation of coherence continues to capture the attention of scientists and engineers. The optical laser is a canonical example of a system that, in principle, exhibits complete coherence. Recent research has focused on the creation of coherent, laser-like states in other physical systems. The phonon laser is one example where it is possible to amplify self-sustained mechanical oscillations. A single mode phonon laser in a levitated optical tweezer has been demonstrated through appropriate balance of active feedback gain and damping. In this work, coherent control of the dynamics of an optical tweezer phonon laser is used to share coherence between its different modes of oscillation, creating a multimode phonon laser. The coupling of the modes is achieved by periodically rotating the asymmetric optical potential in the transverse focal plane of the trapping beam via trap laser polarization rotation. The presented theory and experiment demonstrate that coherence can be transferred across different modes of an optical tweezer phonon laser, and are a step toward using these systems for precision measurement and quantum information processing.

Forecasting Maximum Water Level Data for Post Sangkuliman using An Artificial Neural Network Backpropagation Algorithm

Neural Network (NN) is an information processing system that has characteristics similar to biological neural networks. One of the algorithms in NN is Backpropagation Neural Network (BPNN). BPNN is an excellent method for dealing with complex pattern recognition problems. In this research, maximum water level forecasting was carried out at Sangkuliman Post using a Backpropagation Neural Network. This research aims to obtain modeling for forecasting maximum water level, as well as forecasting results using the best model. The research results show that the best model is five neurons in hidden layer 1 and 3 neurons in hidden layer 2 with the backpropagation algorithm, the activation function used is binary sigmoid, the learning rate is 0.001, and the maximum iteration is 10,000,000 with the smallest RMSE result being 1.816. The forecast results for the following 12 periods are 1.672, 1.779, 1.523, 1.271, 1.752, 1.692, 1.335, 1.479, 1.750, 1.779, 1.340, 1.269, and 1.754. Forecasting results can be used by various parties in decision-making and planning in multiple fields, as an example to see the patterns of biological and vegetable life around Sangkuliman Post. Based of forecasting results, certain months show an increase in maximum water levels. 

Competencies in Higher Education and the Labor Market: A Sociocognitive Analysis of the Problem of Integration

Introduction. Professional competencies developed by the education system do not provide the high degree of integration with the real economy at the Russian labor market. The sociocognitive approach to social institutions as information processing systems suggests that this may be partly due to different languages used by employers and educational structures for describing competencies. The purpose of this study is to test the hypothesis of this mismatch drawing on the example of the applied sociology sector. Materials and Methods. The case study method was applied to the material of the archive of correspondence on personnel issues of a company from the field of applied sociology, which worked in 2012–2019 (46 papers). The hypothesis that employers and educational system use a different language for describing competencies was tested. Content analysis method was applied to the largest Russian job portals: hh.ru, superjob.ru and Avito.Rabota. The hypothesis of non-use of educational standards for describing competencies in the labor market was tested. Results. Both hypotheses were confirmed. Based on the results of the correspondence archive analysis, it was proved that employers use a language different from that of the education system when describing requirements to employees (including their competencies). The results of content analysis revealed the phenomenon of almost complete isolation of the labor market from the formal standards of higher education (educational standards for describing the competencies of sociologists were not used in a single vacancy or a resumé out of more than 32 thousand found on the portals). Discussion and Conclusion. To overcome the lack of demand for graduates in the labor market, it is necessary to overcome the existing language gap between the education system and employers. To this end, the system of validation of competencies should be changed. The source of their description should not be the education system itself, the texts and ideas that are born in it, but the requirements of employers, verbalized by them in the description of vacancies. Descriptions of competencies that do not meet the widely accepted requirements of employers should be automatically excluded from professional education standards as invalid. The results contribute to searching critical problems in the educational system and adapting it to the current needs of the labor market.

Neuropsychology of Self-regulation : Attention Control Mechanism for Controlling Thinking and Other Cognitive Processes

This paper presents a comprehensive theoretical framework for understanding and consciously controlling the cognitive faculty of attention. It analyzes how language and the subject-object dichotomy fundamentally shape human thought processes. The pivotal role of attention in steering cognitive functions is examined, along with how it is influenced by cognitive biases. The brain is conceptualized as an information processing system, with attention serving as the navigational mechanism guiding cognitive faculties. The framework emphasizes the importance of articulation to effectively regulate attentional allocation. Innovative techniques are given, including a modified self-questioning method that leverages the linguistic basis of cognition to monitor and rectify attentional lapses. Grounded in neuroscience, psychology, and evolutionary theory, the paper elucidates neurological mechanisms behind conscious attentional control, including how to stop the thinking process. Potential applications range from improving cognitive performance and emotional regulation to facilitating goal attainment and overall well-being across domains.

The effects of food provisioning on the gut microbiota community and antibiotic resistance genes of Yunnan snub-nosed monkey.

Yunnan snub-nosed monkeys (Rhinopithecus bieti) are the highest elevation lived non-human primate, and their survival has been threatened for decades. To promote their population growth, a reserve provides a typical monkey population with supplemental food. However, the influences of this food provisioning on their gut microbiota and antibiotic resistance genes (ARGs) were unknown. Therefore, we investigated the gut microbiota and ARGs of the food-provisioned monkey population compared with another wild foraging population. We found that food provisioning significantly increased the gut microbiota diversity and changed the community composition, particularly increased both the Firmicutes abundance and Firmicutes/Bacteroidetes ratio. Meanwhile, the food provisioning decreased the complex and stable gut microbiota network. KEGG functions were also influenced by food provisioning, with wild foraging monkeys showing higher functions of metabolism and genetic information processing, especially the carbohydrate metabolism, while food-provisioned monkeys exhibited increased environmental information processing, cellular processes, and organismal systems, including valine, leucine, and isoleucine degradation. In addition, food provisioning increased the abundance of ARGs in the gut microbiota, with most increasing the abundance of bacA gene and changing the correlations between specific ARGs and bacterial phyla in each population. Our study highlights that even food provisioning could promote wildlife nutrient intake, and it is necessary to pay attention to the increased ARGs and potential effects on gut microbiota stability and functions for this human conservation measure.

Пропускная способность и информационная емкость ресурса: пространство, частота, время

Studies of the bandwidth of the resource: space, frequency, time during spatial multiplexing in information transmission, storage and processing systems have been carried out. Bandwidth estimation is relevant in the development of communication systems with spatial multiplexing, as well as in problems of information theory. Limitations in spatial multiplexing are investigated. Theorems for estimating the amount of information passing through a given linear and flat area of space at certain values of the time interval and frequency band are formulated and proved. A theorem for estimating the amount of information passing through a rectangular parallelepiped due to three beams of electromagnetic radiation through three mutually perpendicular faces of a rectangular parallelepiped is formulated and proved. As an example, the amount of information contained in one cubic meter of space filled with electromagnetic radiation of a certain type is estimated. Thus, for frequencies in the range from 3 •108 Hz to 6•1019 Hz, one cubic meter of space contains 3,207•1034 bits of information, which is equivalent to the amount of information contained due to quantum states in a substance weighing 1,444 g at 20 °C. Practical significance: the research results can be useful for the development of information theory and the practice of developing communication systems with spatial multiplexing.

Harmonizing Cross View Image Transformation Through Local and Global Insights- A Review

Hyperspectral and multispectral information processing systems and technologies have demonstrated their value in enhancing agricultural productivity and practices by providing farmers and crop managers with valuable information on factors influencing crop condition and growth. These technologies play a crucial role in various agricultural applications, such as crop management, crop yield forecasting, crop disease detection, and monitoring soil, water, and land usage. To enhance the process of agriculture through effective crop management and assistance to farmer, using an advanced image transformation techniques the study delves into the exploration of techniques for harmonizing cross-view image transformation, with a focus on integrating both local and global insights. Further the study proposes the application of the 2D-DWT (Two-Dimensional Discrete Wavelet Transform) technique for image data preprocessing and the Extreme Learning Machine (ELM) algorithm for image classification in the context of hyperspectral images. Hyperspectral information sensing allows for the coverage of the electromagnetic spectrum in a single acquisition with several hundred spectral bands, resulting in a data cube containing significant spectral and spatial information ELM is particularly effective for classification problems because of its quick training time and capacity to operate with hidden nodes whose parameters are randomly assigned rather than modified iteratively. This comprehensive review aims to provide valuable insights and a critical analysis of the suggested method, shedding light on its potential contributions to the advancement of image transformation techniques for agricultural development.

From integrated bridge system to marine bridge domain: A computational perspective

With the progressive advancement of ship intelligence, there has been a corresponding augmentation in the sensory, control, and other equipment within ship bridge systems. The accelerated expansion of both hardware and software components in ships poses formidable challenges to the existing bridge systems. The prevalent deployment format of ship bridge systems adheres to a traditional decentralized structure, limiting the system's computational prowess, equipment compatibility, and data fusion capabilities. Addressing these constraints and augmenting the ship bridge system's information processing, equipment compatibility, and functional integration represent pivotal objectives. Thus, this paper embarks on an analysis of the developmental trajectory, challenges, and predominant trends characterizing the current Integrated Bridge System (IBS) in ships. Subsequently, harnessing the inherent advantages of software and hardware decoupling, centralized computational capabilities, and seamless integration of data and functions, we propose a comprehensive maritime bridge domain architecture. This proposed architecture is meticulously delineated, encompassing aspects such as overall scheme design, hardware and software subsystems, and the mechanism of data service. In conclusion, the paper advocates a systematic approach to system development, encompassing implementation, testing, and evaluation of the proposed architecture. Rigorous testing and evaluation of the architecture, focusing on data collection, network transmission performance, functional availability, data distribution efficiency, and task processing capabilities, affirm its marked enhancements in computational proficiency, data service efficiency, and functional integration within the IBS. These results lay a robust foundation for the intelligent design of ship systems, paving the way for the evolution of intelligent ships.

A Distributed System Fault Diagnosis System based on Machine Learning

Now days distributed system becomes the mainstream system of information storage and processing. Compared with traditional systems, distributed systems are larger and more complex.However, the average probability of failure is higher and the difficulty, complexity of operation and maintenance are greatly increased. Therefore, it is necessary to use efficient methods to diagnose the system. Our aim is to use the trained model to diagnose the fault data of the distributed system, so we can obtain as high diagnostic accuracy as possible, and create a web side for users to use. The technique we proposed uses the integrated learning approach of Stacking to model the superposition of the raw data. To realize this, we trained with a dataset of 10,000 pieces of data and assessed accuracy every once in a while. Our best training results are about 80.69% accurate and can be used on the web side. By training data sets and analyzing distributed system faults with Stacking technology, a model with a test accuracy of 80.69% was obtained. Through this model and the web platform we built, the fault of distributed system can be diagnosed, and the diagnosis results are better than other models.

A mechanism for tuning proprioception proposed by research in Drosophila and mammals

Proprioception provides important sensory feedback regarding the position of an animal’s body and limbs in space. This interacts with a central pattern generator responsible for rhythmic movement, to adapt locomotion to the demands that an animal’s environment places on it. The mechanisms by which this feedback is enabled are poorly understood, which belies its importance: dysfunctional proprioception is associated with movement disorder and improving it can help reduce the severity of symptoms. Similarly, proprioception is important for guiding accurate robotic movement and for understanding how sensory systems capture and process information to guide action selection. It is therefore important to interpret research that investigates mechanisms of proprioception, to ask: what type of information do proprioceptive sensors capture, and how do they capture it? Work in mammalian models has made important progress towards answering this question. So too, has research conducted Drosophila. Fruit fly proprioceptors are more accessible than mammalian equivalents and can be manipulated using a unique genetic toolkit, so experiments conducted in the invertebrate can make a significant contribution to overall understanding. It can be difficult, however, to relate work conducted in different models, to draw general conclusions about proprioception. This review, therefore, explores what research in the fruit fly has revealed about proprioceptor function, to highlight its potential translation to mammals. Specifically, the present text presents evidence that differential expression of mechanoelectrical transducers contributes to tuning of fly proprioceptors and suggests that the same mechanism may play a role in tuning mammalian proprioceptors.

Special Issue on Robotic, Mechatronic and Information Systems for Decommissioning

The Fukushima Daiichi Nuclear Power Plant accident, triggered by the Great East Japan Earthquake and the tsunami, has had a major impact on societies across the world. The subsequent focus on decommissioning efforts has attracted worldwide attention. It has been consistently asserted since the aftermath of the accident that the decommissioning of the Fukushima Daiichi Nuclear Power Plant will take approximately 30 to 40 years. The promotion of decommissioning work means that we will continue to face the problems with uncertainties in the work, as sometimes referred to as Unknown Unknowns. Typical elemental technologies required in remotely operated robotic systems for decommissioning include mobile mechanisms and their control, handling mechanisms and their control, information communication, operation interface (information presentation and command input), shielding (radiation resistance) and so on. Although many tasks using remotely operated robotic systems have been carried out with noteworthy results, there are lingering issues yet to be clarified. To ensure the safe and effective execution of various types of decommissioning tasks over a period of several decades, continuous research and development of each elemental technology are imperative, and these technologies must be integrated into a system appropriately to the assumed tasks. In addition, human resource development and the transfer of knowledge and experience are also important issues. From such viewpoint, this special issue is titled “Robotic, Mechatronic and Information Systems for Decommissioning.” It contains papers and development reports on robotics, mechatronics, information processing, and information systems technologies relevant to decommissioning work. It also features recent activities of nuclear emergency response organizations. We hope this special issue will acquaint readers with the latest research and development results and organizational activities related to decommissioning. At the same time, we hope that we were able to provide readers interested in robots, mechatronics, and information technology with an opportunity to become aware of the issues and necessary perspectives related to decommissioning and nuclear disasters. Lastly, we would like to thank the editorial board of the Journal of Robotics and Mechatronics, the editorial team of Fuji Technology Press, and the reviewers for their support in the planning and publication of this special issue. Their dedicated efforts are deeply appreciated.

3D MODELLING AND VIRTUAL REALITY FOR MUSEUM HERITAGE PRESENTATION: CONTEXTUALISATION OF SCULPTURE FROM THE TANG ERA

Abstract. The present research concerns the contextualisation and presentation of eleven small statues from the Tang era dated from the XI and XII centuries CE today housed at the Asian Art Museum in Turin (MAO). A multidisciplinary group with expertise in Asian art, digital representation, and information processing systems, with the support of VR@POLITO and MOD Lab Arch of the Politecnico di Torino is involved in the work. The goal is to present together several Tang-era pottery models not belonging to the same funerary outfit within the spaces of a coeval, philologically compatible hypogeal tomb. With a pronounced storytelling intent, the reconstructive 3D model represents a virtual exhibition project summarizing Tang art’s architectural, pictorial, and sculptural features. The pipeline was developed through photogrammetric acquisition with Structure from Motion (SfM) technology and 3D modeling of the artworks, reconstructive modeling and texturing of a Tang tomb as the ideal space of the statues, and communication through a virtual reality (VR) experience augmented with a set of information.

TRANSFORMASI DIGITAL : MENINGKATKAN KUALITAS PELAYANAN PUBLIK MELALUI PENERAPAN E – GOVERNMENT DI KANTOR KECAMATAN JABUNG KABUPATEN MALANG

A sub-district is an administrative regional unit in Indonesia which is under the auspices of a district or city. An sub-district head heads the sub-district and divides it into several sub-districts or villages. The implementation of regional autonomyn policies has encouraged changes in the general structure of regional government, including structural, functional and cultural changes. One of the most influential changes relates to the position, authority, duties and responsibilities of a sub-district head. Along with technological advances and referring to Presidential Instruction no. 3 of 2003, E-Government was implemented to ensure the integration of electronic document and information management and processing systems. The focus is on developing a transparent public service system. Jabung District consists of 15 villages and has a population of 78,031 people with a male population of 39,873 while a female population of 38,158 people. This research aims to find out how E-Government is implemented and public service innovations in the Jabung District Office. This research uses descriptive qualitative methods. Data collection was carried out using observation, interviews and documentation techniques. The results of this research indicate that the implementation of E-Government and public service innovation in the Jabung District Office has been running well and in accordance with applicable Standard Operating Procedures (SOP). In implementing E-Government at the Jabung District Office, there are also several things that often make people confused in managing administrative needs, such as the absence of information regarding changes to forms or policies related to direct electronic based government administration or clear information via print or electronic media. so it can be said that it is still not optimal.

Coccyx Terminate by Artificial Intelligence

Being the most successful Artificial Intelligence automate mathematical used for human intelligence. This paper focuses on establishing the conceptual foundation of the structure and processes of human thinking systems. The conceptualization of component of the complexity-intelligence strategy. In this analysis, the human thinking system is perceived to be comprised of two components namely, the energy–matter subsystem and the physical symbol subsystem. The general procedure in which the human mind handles and exploits one or more physical symbol systems is analysed. Subsequently, the boundaries and objectives of human thinking systems as information processing systems, and the necessity of artificial information systems are conceived as four postulates. My research over on various Otsu algorithms and AI with Coccyx. Here i used information from the four human senses, vision, hearing, touch and think. Also some ways those sensory AI modalities mimic the senses, and offer benefits in both new and current applications. Key Words: Human Thinking system, intelligent microfluidic chip. Coccyx, Artificial Intelligence