Une plate-forme sans fil pour electrochimique spectroscopie d'impédance

Avec l’émergence soutenue de capteurs et de dispositifs électrochimiques innovants, la spectroscopie d'impédance électrochimique est devenue l'un des outils les plus importants pour la caractérisation et la modélisation de la matière ionique et de l'interfaçage des capteurs. La capacité de détecter automatiquement, à l’aide de dispositifs électrochimiques peu couteux, les caractéristiques physiques et chimiques de la matière ionique ouvre une gamme d’application très variée pour la compréhension et l’optimisation des procédés ou interviennent les processus électrochimiques. Cette thèse décrit le développement d’une plate-forme microélectronique miniaturisée, connectée, multiplexée, et à faible coût pour la spectroscopie d'impédance diélectrique (SID) conçue pour les mesures électrochimiques in-situ et adaptée aux architectures de réseau sans fil. La plate-forme développée durant ce travail de maitrise a été testée et validée au sein d’une maille ZigBee et a été en mesure d'interfacer jusqu'à trois capteurs SID en même temps et de relayer l'information à travers le net Zigbee pour l'analyse de données et le stockage. Le système a été construit à partir de composants microélectroniques disponibles commercialement et bénéficie des avantages d'une calibration système on-the-fly qui effectue la calibration du capteur de manière aisée. Dans ce mémoire de maitrise, nous rapportons la modélisation et la caractérisation de senseurs électrochimiques de nitrate; notamment nous décrivons la conception microélectronique, la réponse d'impédance de Nyquist, la sensibilité et la précision de la mesure électrochimique, et les résultats de tests de la plate-forme pour les applications de spectroscopie d'impédance relatives à la détection du nitrate, de la détection de la qualité de l'eau, et des senseurs tactiles.The emergence of the various applications of electrochemical sensors and devices, electrochemical impedance spectroscopy became one of the most important tools for characterizing and modeling of the material and interfacing the sensors. The ability to sense in an automatic manner enables a wide variety of processes to be better understood and optimized cost-effectively. This thesis describes the development of a low-cost, miniaturized, multiplexed, and connected platform for dielectric impedance spectroscopy (DIS) designed for in-situ measurements and adapted to wireless network architectures. The platform has been tested and used as a DIS sensor node on a ZigBee mesh and was able to interface up to three DIS sensors at the same time and relay the information through the Zigbee net for data analysis and storage. The system was built from commercial microelectronics components and benefits from an on-the-fly calibration system that makes sensor calibration easy. The thesis reports characterizing and modeling of two electro-chemical devices (i.e. nitrate sensor and optically-transparent electrically-conductive glasses) and also describes the microelectronics design, the Nyquist impedance response, the measurement sensitivity and accuracy, and the testing of the platform for in-situ dielectric impedance spectroscopy applications pertaining to fertilizer sensing, water quality sensing, and touch sensing

Statistical Hardware Design With Multi-model Active Learning

With the rising complexity of numerous novel applications that serve our modern society comes the strong need to design efficient computing platforms. Designing efficient hardware is, however, a complex multi-objective problem that deals with multiple parameters and their interactions. Given that there are a large number of parameters and objectives involved in hardware design, synthesizing all possible combinations is not a feasible method to find the optimal solution. One promising approach to tackle this problem is statistical modeling of a desired hardware performance. Here, we propose a model-based active learning approach to solve this problem. Our proposed method uses Bayesian models to characterize various aspects of hardware performance. We also use transfer learning and Gaussian regression bootstrapping techniques in conjunction with active learning to create more accurate models. Our proposed statistical modeling method provides hardware models that are sufficiently accurate to perform design space exploration as well as performance prediction simultaneously. We use our proposed method to perform design space exploration and performance prediction for various hardware setups, such as micro-architecture design and OpenCL kernels for FPGA targets. Our experiments show that the number of samples required to create performance models significantly reduces while maintaining the predictive power of our proposed statistical models. For instance, in our performance prediction setting, the proposed method needs 65% fewer samples to create the model, and in the design space exploration setting, our proposed method can find the best parameter settings by exploring less than 50 samples.Comment: added a reference for GRP subsampling and corrected typo

Analysis of the role of internal control in performing the responsibility of managers of public sector

Accounting information system is necessary for the success of governmental agencies in long terms. The quality of Governmental agencies cannot be evaluated without suitable supervision tools. All Governmental agencies should evaluate the impact of various incidents of controlled resources. Accounting information system plays important role in Governmental agencies in acceptance and survival of a strategic situation. Accounting information system needs suitable and effective internal control system to perform properly and to be away from risks. One of the main responsibilities of managers is to analyze the effectiveness of internal control. Managers should be responsible for their performance and clarify information and enforce financial discipline and fight against economic and financial corruption which is necessary for the effective internal control in Governmental agencies and organizations that the establishment of strong and effective internal controls leads to transparency of financial reporting and promotion of financial and operational capacity. Since the government is considered as the public sector, the impacts of strong internal control in this sector and its impact on the amount of responsibility of managers' accountability gets special importance. In this article, besides describing internal control, we try to discuss its relationship with the responsibility of managers' accountability

Analysis of the role of internal control in performing the responsibility of managers of public sector

Accounting information system is necessary for the success of governmental agencies in long terms. The quality of Governmental agencies cannot be evaluated without suitable supervision tools. All Governmental agencies should evaluate the impact of various incidents of controlled resources. Accounting information system plays important role in Governmental agencies in acceptance and survival of a strategic situation. Accounting information system needs suitable and effective internal control system to perform properly and to be away from risks. One of the main responsibilities of managers is to analyze the effectiveness of internal control. Managers should be responsible for their performance and clarify information and enforce financial discipline and fight against economic and financial corruption which is necessary for the effective internal control in Governmental agencies and organizations that the establishment of strong and effective internal controls leads to transparency of financial reporting and promotion of financial and operational capacity. Since the government is considered as the public sector, the impacts of strong internal control in this sector and its impact on the amount of responsibility of managers' accountability gets special importance. In this article, besides describing internal control, we try to discuss its relationship with the responsibility of managers' accountability

Analysis of the role of internal control in performing the responsibility of managers of public sector

Accounting information system is necessary for the success of governmental agencies in long terms. The quality of Governmental agencies cannot be evaluated without suitable supervision tools. All Governmental agencies should evaluate the impact of various incidents of controlled resources. Accounting information system plays important role in Governmental agencies in acceptance and survival of a strategic situation. Accounting information system needs suitable and effective internal control system to perform properly and to be away from risks. One of the main responsibilities of managers is to analyze the effectiveness of internal control. Managers should be responsible for their performance and clarify information and enforce financial discipline and fight against economic and financial corruption which is necessary for the effective internal control in Governmental agencies and organizations that the establishment of strong and effective internal controls leads to transparency of financial reporting and promotion of financial and operational capacity. Since the government is considered as the public sector, the impacts of strong internal control in this sector and its impact on the amount of responsibility of managers' accountability gets special importance. In this article, besides describing internal control, we try to discuss its relationship with the responsibility of managers' accountability

CNN2Gate: an implementation of convolutional neural networks inference on FPGAs with automated design space exploration

ABSTRACT: Convolutional Neural Networks (CNNs) have a major impact on our society, because of the numerous services they provide. These services include, but are not limited to image classification, video analysis, and speech recognition. Recently, the number of researches that utilize FPGAs to implement CNNs are increasing rapidly. This is due to the lower power consumption and easy reconfigurability that are offered by these platforms. Because of the research efforts put into topics, such as architecture, synthesis, and optimization, some new challenges are arising for integrating suitable hardware solutions to high-level machine learning software libraries. This paper introduces an integrated framework (CNN2Gate), which supports compilation of a CNN model for an FPGA target. CNN2Gate is capable of parsing CNN models from several popular high-level machine learning libraries, such as Keras, Pytorch, Caffe2, etc. CNN2Gate extracts computation flow of layers, in addition to weights and biases, and applies a “given” fixed-point quantization. Furthermore, it writes this information in the proper format for the FPGA vendor’s OpenCL synthesis tools that are then used to build and run the project on FPGA. CNN2Gate performs design-space exploration and fits the design on different FPGAs with limited logic resources automatically. This paper reports results of automatic synthesis and design-space exploration of AlexNet and VGG-16 on various Intel FPGA platforms

Neural Evidence for Compromised Mental Imagery in Individuals With Chronic Schizophrenia

Mental imagery impairment has been reported in schizophrenia. The present study aimed to investigate the neural evidence for mental imagery impairment in patients with schizophrenia. The study participants included 20 patients with chronic schizophrenia and 18 healthy control subjects. Event-related potentials were recorded during a mental hand rotation task, in which participants were instructed to judge the laterality of hands displayed in different orientations. The performances of patients were significantly less accurate and slower than control subjects on hand rotation task. Moreover, the patients showed significantly reduced rotation-related negativity amplitude for mental rotation effect. The results demonstrate mental imagery impairment in patients with schizophrenia at both the behavioral and neural level

Predictors of Leisure Participation in 6 -14 Years Old Children with Cerebral Palsy: Structural Equation Modeling

AbstractObjective: The aim of this study was to test a model of child,family and environment and identify factors affecting intensity of leisure participation by children with cerebral palsy (CP).Materials & Methods: in this cross-sectional study,232 children with cerebral palsy (141 boys and 91 girls), age range 6 to 14 years and their parents were selected from 4 schools with special needs and 5 rehabilitation center through available sampling in Shiraz city. To evaluate leisure participation, we used the Persian version of Children’s Assessment of Participation and Enjoyment (CAPE) completed by participants. Demographic questionnaires, Craig Hospital Inventory of Environmental Factors (CHIEF), Strengths and Difficulties Questionnaire (SDQ), Family Environmental Scale (FES), SPARCLE cognitive level and parent's version of Gross Motor Function Classification System, Manual Ability Classification System and Communication Function Classification System were send to parents with some necessary explanations and completed. Structural equation modeling was used to test the model hypothesis. SPSS18 and AMOS16 were used for statistical data analysis. Results: Comparative fit index indicated a moderate to good fit model. The presented model explains 44% of the variance for intensity of participation. Constructs such as Family Activity Orientation with standardized total effect of (.31) and path coefficients P< .05 has shown most significant direct effect on participation, after that higher gross motor function (-.26), higher manual ability (-.19), communication function (-.17), higher cognitive level (-.16), more brothers and sisters in family (.15) and less emotional- behavioral problems (-.15) have shown direct effect on intensity of participation. Family Structures & Relationships (.17) and unsupportive environment constructs (-.14) have shown indirect but significant effect (P< .05). The relationship between family education level and income with participation were not significant (P>.05).Conclusion: Intensity of CP children participation is influenced by child, family and environmental factors. Parent's knowledge of recreational activities and their preferences to participation in leisure and recreations give children more opportunities to participate. higher gross motor function, manual ability, and communication function have an important role in participation. Family structure means family cohesion, roles organization, and conflicts between family members and also encountering physical, attitudinal and structural barriers in the home and community change children participation pattern indirectly. This study suggests therapists to support children’s behavior, family relationships and involvement in community activities and optimizing physical function for children who have limitations in self-mobility to enhance their participation